Reorganization of Bankrupt Firms in France - Biblioweb

UNIVERSITE DE CERGY-PONTOISE
E.D. ECONOMIE, MANAGEMENT, MATHEMATIQUES CERGY
LABORATOIRE DE RECHERCHE THEMA
Reorganization of Bankrupt Firms in France:
Financial and Econometric Analysis
DISSERTATION
by
Rim AYADI-BEN LAKHAL
Presented on 05/12/2011 in Cergy
to obtain the degree of
DOCTEUR EN SCIENCES DE GESTION
DE L’UNIVERSITE DE CERGY-PONTOISE
Doctoral Jury
M. Jocelyn Martel, Principle Supervisor
Professor, ESSEC Business School, Cergy, France
M. Régis Renault, Co-supervisor
Professor, Université de Cergy-Pontoise, Cergy, France
M. Régis Blazy
Professor, Université de Strasbourg, France
M. Timothy Fisher
Professor, University of Sydney, Australia
M. Laurent Vilanova
Professor, Université Lumière Lyon 2, France
L’université de Cergy-Pontoise, n’entend donner
aucune approbation ou improbation aux opinions
émises dans cette thèse. Ces opinions doivent être
considérées comme propres à leur auteur.
Acknowledgements
It is a pleasure to thank those who made this thesis possible.
First of all, I would like to express my gratitude to my supervisors, who accepted me as
their Ph.D student without any hesitation. I am deeply indebted to my principle supervisor,
Professor Jocelyn Martel, for his thoughtful guidance, invaluable expertise, intellectual
support, encouragement, and lots of good ideas throughout the period of my study. I would
have been lost without him. I am also deeply grateful to my co-supervisor, Professor Régis
Renault, who has provided me with invaluable suggestions, comments and constructive
discussions. I assume, of course full responsibility for any remaining errors.
I would like to thank the reading committee for spending their valuable time on this
thesis (Professors Régis Blazy, Timothy Fisher, and Laurent Vilanova).
Special thanks are also given to Professor Thomas Brodaty for having his door open to
any of my questions and econometric problems.
I am grateful to the president of the commercial Court of Paris, Mrs Roy, for providing me
with the data I required for my research. I would like to express my sincere thanks to
Michel who provided me with assistance in the data collection.
I remain grateful to all members of the University of Cergy-Pontoise for their support and
encouragement. I am thankful to the secretaries and to the university's library staff for
assisting me in many different ways. Malika deserves special mention. I would like also to
thank all my friends and colleagues at the University of Cergy-Pontoise for their great
friendship and for providing a good working atmosphere.
I owe my heartfelt thanks to my parents, Mohamed and Tatiana, for believing in me and
being there for me. They raised me, supported me, taught me, and loved me. I would like to
express my most sincere gratitude, respect, and love to them. I would like to extend my
sincere thanks to my little sister, Sondra, for her patience, and her invaluable support
during some of the most challenging moments of the writing and editing of the thesis. I
wish her good luck with the rest of her studies.
I remain thankful to my extended family, the Khanfir's family, and my friends for
providing a loving environment for me. I am also grateful to my parents-in-law for their
kindness and understanding.
Last but not least, I would like to express my gratitude and endless love to my devoted
husband, Riadh, who continually encouraged me to keep going and not to give up. He has
always been patient and caring, giving me all the strength I have needed especially during
the final stages of this thesis.
Thank you.
I dedicate this thesis to my parents, my sister, and my husband with all my love.
Reorganization of Bankrupt Firms in France:
Financial and Econometric Analysis
Abstract
This thesis provides an empirical analysis of the reorganization of bankrupt firms in the French context.
On the one hand, we use an original data set from the commercial Court of Paris to study the particularity of
the French bankruptcy law which consists in providing bankrupt firms with two forms of reorganization
(continuation versus sale). Empirical results indicate that the probability of confirming a continuation plan
increases with the firm’s profitability and the fraction of intangible assets while it decreases with the size of
the firm and the amount of secured debt relative to assets. Moreover, some causes of default have a
significant impact on the reorganization form. On the other hand, we investigate the performance of the
reorganized firms according to three criteria. First, we examine the consummation of the reorganization
plans. We find that the age of the firm, the percentage of the plan's first payout, the relative size of banking
claims, and the firms' industry profitability increase the probability of plans' consummation. Second, we
assess accounting measures of performance prior to filing and following confirmation. In particular, logistic
results show that larger firms with higher profitability and firms operating in profitable industries at the
confirmation year are most likely to continue their operations for at least four years following confirmation.
Third, we investigate the future prospects of reorganized firms using survival analysis techniques. The
estimation of time-varying Cox model indicates that company's profitability, liquidity, and the industry
profitability have positive effect on survival while leverage has a negative threshold effect.
Key words: Bankruptcy, reorganization, continuation, sales, logit model, survival analysis
Redressement des Entreprises en Difficultés en France:
Analyse Financière et Econométrique
Résumé
L’objet de cette thèse est de mener une étude empirique sur le redressement des entreprises en
difficultés en France. Dans un premier temps, nous utilisons une base de données originale construite à
partir de dossiers de redressement ouverts au tribunal de commerce de Paris pour identifier les
déterminants de l’issue de la procédure de réorganisation (continuation versus cession). Les résultats
empiriques indiquent que la rentabilité de l’entreprise augmente la probabilité de continuation alors que la
taille des actifs, le montant des créances privilégiées par rapport au montant des actifs et la proportion des
actifs tangibles augmentent la probabilité d’une cession. Nous trouvons également que certaines causes de
défaut influencent significativement l’issue de la procédure. Dans un deuxième temps, nous examinons la
performance des entreprises réorganisées et ses déterminants. Premièrement, nous nous intéressons à
l’exécution des plans de redressement. Nous montrons que la probabilité de succès d’un plan augmente avec
l’âge de l’entreprise, la concentration des créances bancaires, le pourcentage du premier versement et la
rentabilité du secteur d’activités. Deuxièmement, nous utilisons des mesures comptables pour évaluer la
performance. En particulier, les résultats montrent que la taille des actifs de l’entreprise et sa rentabilité
durant l’année de confirmation augmentent la probabilité qu’elle reste active pendant au moins quatre ans
après la confirmation. Troisièmement, nous examinons la survie des entreprises réorganisées. Le modèle Cox
estimé avec des variables dépendantes montre que la rentabilité de l’entreprise, sa liquidité et la rentabilité
du secteur on un impact positif sur la survie alors que l’endettement a un effet de seuil négatif.
Mots clés: Défaillances, redressement, continuation, cession, modèle logit, analyse de survie
Table of Contents
Page
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
iv
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Chapter
1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11
2
The Economics of Corporate Bankruptcy . . . . . . . . . . .
15
2.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . .
15
2.2
Corporate bankruptcy: a literature review . . . . .
15
2.3
Overview of the French bankruptcy law . . . . . . .
42
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
63
3
Reorganization of Bankrupt Firms in France Descriptive
Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
69
3.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . .
69
3.2
Data and Sample . . . . . . . . . . . . . . . . . . . . . . .
70
3.3
Status of Cases . . . . . . . . . . . . . . . . . . . . . . .
72
3.4
Firm characteristics variables . . . . . . . . . . . . . .
74
3.5
Claims variables . . . . . . . . . . . . . . . . . . . . . . .
80
3.6
Continuations . . . . . . . . . . . . . . . . . . . . . . . .
83
i
ii
3.7
Sales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
85
3.8
Reasons for filing for reorganization . . . . . . . . .
87
3.9
Time in reorganization . . . . . . . . . . . . . . . . . . .
90
3.10 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . .
94
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
4
Reorganization of Bankrupt Firms in France Continuation versus Sale . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
4.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 111
4.2
The reorganization versus sale debate
4.3
Determinants of reorganization outcome . . . . . . . 117
4.4
Data and sampling . . . . . . . . . . . . . . . . . . . . . . 124
4.5
Empirical implementation . . . . . . . . . . . . . . . . . 127
4.6
Empirical results . . . . . . . . . . . . . . . . . . . . . . 132
4.7
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 137
. . . . . . . . 113
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
5
Do Continuation Plans Succeed in France? . . . . . . . . . . 151
5.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 151
5.2
Plan’s consummation: prior research . . . . . . . . . . 153
5.3
Sample and consummation rate . . . . . . . . . . . . . . 155
5.4
Determinants of plan’s consummation . . . . . . . . . 161
5.5
Empirical analysis . . . . . . . . . . . . . . . . . . . . . . 165
5.6
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
iii
6
Performance of Reorganized Firms in France . . . . . . . . 188
6.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 188
6.2
Review of prior research . . . . . . . . . . . . . . . . . 190
6.3
Data and sample . . . . . . . . . . . . . . . . . . . . . . . 195
6.4
Measure of post-confirmation performance . . . . . 197
6.5
Successful versus failing reorganizations . . . . . . . 201
6.6
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 205
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
7
Survival of Reorganized Firms in France . . . . . . . . . . . 215
7.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 215
7.2
Literature review . . . . . . . . . . . . . . . . . . . . . . 217
7.3
Survival analysis methodology . . . . . . . . . . . . . . 222
7.4
Data and explanatory variables . . . . . . . . . . . . . 229
7.5
Empirical implementation . . . . . . . . . . . . . . . . . 233
7.6
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 241
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
List of Tables
1.1 Répartition des Défaillances selon la Procédure et son Issue entre 1995
et 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.2 Répartition des Défaillances selon la Procédure et son Issue entre 2006
et 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1 Distribution of Continuation Cases by Year and Status . . . . . . . . 97
3.2 Distribution of Reorganized Firms by Legal Structure . . . . . . . . . 97
3.3 Distribution of Reorganized Firms by Industry . . . . . . . . . . . . . 98
3.4 Distribution of Reorganized Firms by Business Type . . . . . . . . . 98
3.5 Characteristics of Firms in Reorganization . . . . . . . . . . . . . . . 99
3.6 Characteristics of Firms by Reorganization Form . . . . . . . . . . . 99
3.7 Distribution of Reorganized Firms by Assets and Debts
. . . . . . . 99
3.8 Distribution of Reorganized by Turnover . . . . . . . . . . . . . . . . 100
3.9 Distribution of Reorganized Firms by Number of Employees . . . . . 100
3.10 Distribution of Reorganized Firms based on SME De…nition . . . . . 100
3.11 Debts-to-Assets Ratio Assets’Amounts . . . . . . . . . . . . . . . . . 101
3.12 Claims’Characteristics of Firms in Reorganization . . . . . . . . . . . 101
3.13 Characteristics of Firms by Reorganization Form . . . . . . . . . . . 102
3.14 Characteristics of Continuation Proposals . . . . . . . . . . . . . . . . 103
3.15 Payments to Creditors by Continuation Cases’Status . . . . . . . . . 103
3.16 Variables Speci…c to Sales . . . . . . . . . . . . . . . . . . . . . . . . 103
iv
v
3.17 The Five most Reported Reasons for Filing for Reorganization . . . . 104
3.18 Time in the Reorganization Process by Reorganization Form . . . . . 105
3.19 Time in Continuation by Final Outcome . . . . . . . . . . . . . . . . 105
3.20 Opening to Con…rmation Interval by Legal form and Reorganization
Form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
3.21 Opening to Con…rmation by Claims Level and Reorganization Form . 106
3.22 Opening to Con…rmation by Assets Level and Reorganization Form . 106
4.1 De…nition of the Explanatory Variables and Expected Signs . . . . . 143
4.2 Summary Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
4.3 Determinants of the Form of Reorganization (Continuation vs Sale as
going-concern) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
5.1 Characteristics of Firms Plan’s Outcome . . . . . . . . . . . . . . . . 178
5.2 Consummation Rate by Assets . . . . . . . . . . . . . . . . . . . . . . 178
5.3 Relation between the Consummation Rate and the Plan’s Duration . 179
5.4 Expected Payout Average by Plan’s Outcome . . . . . . . . . . . . . 179
5.5 De…nition of Explanatory Variables . . . . . . . . . . . . . . . . . . . 180
5.6 Summary of Logit Estimation Models . . . . . . . . . . . . . . . . . . 181
5.7 Correlation Matrice . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
5.8 Classi…cation Analysis of the Full Sample . . . . . . . . . . . . . . . . 182
5.9 Subgroups used in the Holdout Procedure . . . . . . . . . . . . . . . 182
5.10 Classi…cation Analyses for Estimation and Holdout Sample . . . . . . 183
6.1 Distribution of Failing Firms to Second Bankruptcy . . . . . . . . . . 210
6.2 Accounting Measures of Performance prior and Following Con…rmation210
6.3 Industry-adjusted Measures of Performance prior and Following Reorganization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
vi
6.4 Changes in Accounting Measures of Pro…tability . . . . . . . . . . . . 212
6.5 Post-con…rmation Pro…tability . . . . . . . . . . . . . . . . . . . . . . 212
6.6 Measures of Performance by Reorganization’s Outcome . . . . . . . . 213
6.7 De…nition of Explanatory Variables . . . . . . . . . . . . . . . . . . . 214
6.8 Determinants of Post-con…rmation Outcome . . . . . . . . . . . . . . 214
7.1 De…nition of Variables an Expected Signs . . . . . . . . . . . . . . . . 247
7.2 Kaplan-Meier Estimation . . . . . . . . . . . . . . . . . . . . . . . . . 247
7.3 Cox Proportional Hazards Models Estimation . . . . . . . . . . . . . 250
7.4 Testing the Proportional Hazards Assumption . . . . . . . . . . . . . 251
List of Figures
2.1 The French bankruptcy code before 2005 reform (Blazy et al., 2011) . 54
3.1 Listed Reasons for Filing Reorganization by Form and Grouping . . . 107
3.2 Listed Reasons for Filing Reorganization by Legal Structure . . . . . 107
5.1 ROC Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
7.1 Kaplan-Meier Survival Estimate . . . . . . . . . . . . . . . . . . . . . 252
7.2 Graph of Risk Scores by Firm Status . . . . . . . . . . . . . . . . . . 252
7.3 Graph of Survival Function . . . . . . . . . . . . . . . . . . . . . . . 253
7.4 Graph of Survival Function by Firm Status . . . . . . . . . . . . . . . 253
vii
Chapter 1
Introduction
Les défaillances d’entreprises représentent des mécanismes naturels d’allocation des
ressources des entreprises en di¢ cultés. Selon Hart (2000), trois alternatives sont
o¤ertes aux entreprises en di¢ cultés : la réorganisation, la reprise de l’activité par
une autre entité et la liquidation. L’alternative qui devrait être choisie est celle qui
permettrait de générer un maximum de valeur. Dans cette perspective, les défaillances jouent un rôle de régulation et d’apurement du tissu économique. Les entreprises les plus performantes poursuivent leurs activités et les entreprises les moins
performantes sont éliminées. En contrepartie de cet objectif d’e¢ cacité, les défaillances d’entreprises peuvent avoir des conséquences économiques et sociales dramatiques où di¤érentes parties sont impliquées: salariés, créanciers, actionnaires,
pouvoirs publics, dirigeants d’entreprise. . .
Gresse (2003) intègre trois composantes dans le processus de défaillance : la
défaillance économique, la défaillance …nancière et la défaillance juridique. La défaillance économique peut être dé…nie par des pertes structurelles et chroniques. Elle
signi…e que l’entité n’est plus rentable et qu’elle génère plus de charges que de produits. Une façon de détecter la non pro…tabilité d’un projet est d’utiliser l’excédent
brut d’exploitation. La défaillance …nancière se caractérise par une situation où
1
2
l’entreprise ne peut structurellement pas faire face à ses décaissements et son passif
à court terme est nettement supérieur à son actif réalisable. En…n, la défaillance
juridique est la sanction légale de la défaillance …nancière et la constatation juridique
de l’insolvabilité de l’entreprise qui la soumet au contrôle de justice.
Le traitement légal de la défaillance se re‡ète dans les procédures collectives
retenues. Il di¤ère d’un pays à un autre selon sa tradition juridique et selon le
contexte économique et politique du moment (Pochet, 2001). Il peut être plus ou
moins favorable aux débiteurs et aux créanciers. En e¤et, en matière de défaillances
d’entreprises, on distingue deux approches possibles en ce qui concerne les procédures collectives: la première consiste à privilégier les intérêts des créanciers (système
pro-créancier) et la deuxième consiste à privilégier le redressement de l’entreprise
a…n de minimiser les conséquences économiques et sociales des défaillances (système pro-débiteur). Chacune de ces approches conditionne l’e¢ cacité des décisions
de liquidation ou de redressement ainsi que les incitations et les comportements des
débiteurs et des créanciers.
Franken (2004) examine l’e¢ cacité ex ante et ex post des deux approches. D’une
part, il montre qu’un régime pro-créancier réduit ex ante les problèmes de sousinvestissement grâce à la protection des créanciers alors qu’un régime pro-débiteur
les accroît. D’autre part, un régime pro-créancier accroît ex post les problèmes de
sous-investissement dus à la liquidation d’entreprises viables alors qu’un régime prodébiteur les réduit en préservant un plus grand nombre d’entreprises viables.
Les dernières années ont été marquées, dans de nombreux Etats, par une refonte
plus ou moins profonde des règles applicables en matière de défaillance visant à
faciliter la sauvegarde des entreprises en di¢ cultés. Ce mouvement concerne plusieurs
Etats à travers le monde et plus spéci…quement les Etats membres de l’Union
Européenne. En particulier, la France est l’un des premiers pays à avoir réformé
3
le droit des entreprises en di¢ cultés à plusieurs reprises dans l’objectif de sauvegarder l’entreprise et de préserver les emplois. Premièrement, les réformes de 1984 et
1985 s’articulent autour de deux axes majeurs: la prévention et le traitement des
di¢ cultés des entreprises. Elles marquent la prééminence de l’entreprise qui passe en
premier plan avant les créanciers.1 Deuxièmement, la réforme de 1994 vise à renforcer
la prévention des di¢ cultés des entreprises et ce en accélérant la procédure d’alerte,
en accroissant les pouvoirs du juge et en élargissant le domaine d’application du
règlement amiable. En…n, la loi de sauvegarde de 2005 a pour objectif de renforcer
la prévention et d’instaurer une nouvelle procédure de sauvegarde destinée à faciliter
la réorganisation de l’entreprise à l’initiative du débiteur.
A la di¤érence de la plupart des législations en Europe et dans le monde, les considérations sociales en France sont fortement ancrées dans le droit des entreprises en
di¢ cultés. Le souci de limiter les conséquences sociales des défaillances est re‡été
dans di¤érentes mesures, qui font la spéci…cité de la législation française. La première particularité de la loi française est la place qu’elle accorde aux mécanismes
de prévention qui tendent à intervenir en amont de la cessation de paiements avant
que la situation de l’entreprise ne soit irrémédiablement compromise. La deuxième
particularité est la volonté a¢ chée du législateur de faciliter la sauvegarde des entreprises en di¢ cultés pour préserver l’emploi.2 La troisième particularité concerne le
pouvoir discrétionnaire accordé au juge tout au long de la procédure collective a…n
de répondre au mieux aux objectifs énoncés par la loi. En…n, une autre particularité
1 Suite
aux réformes de 1984 et 1985, les prérogatives des créanciers ont été réduites
principalement sur deux plans : d’une part, la décision relative au sort de l’entreprise ne
leur appartient plus, elle est con…ée au tribunal et d’autre part, les créanciers titulaires de
sûretés subissent comme les créanciers chirographaires les délais du plan et perdent leurs
droits de poursuite.
2 Les objectifs de la loi française sont successivement : le sauvetage de l’entreprise, la
préservation des emplois et l’apurement du passif.
4
de la législation française consiste à o¤rir deux solutions pour réorganiser l’entreprise
en di¢ cultés : la continuation et la cession.3
Si l’objectif de la législation française en matière de défaillance est de sauvegarder
l’entreprise, il convient de constater que les chi¤res nous montrent une réalité qui
est tout autre. En e¤et, les statistiques sur la période de notre étude (1995-2004)
indiquent qu’il y a près de 40000 défaillances d’entreprises par an en moyenne. En
plus, entre 1995 et 2004, les liquidations immédiates représentent près de 62% des
procédures collectives et environ 80% des entreprises redressées ont été liquidées à la
…n de la période d’observation, fait à priori surprenant pour une loi dont l’objectif
principal est le maintien de l’activité et de l’emploi (voir Tableau 1). Des statistiques
plus récentes sur la période (2006-2010) qui succède la réforme de 2005 montrent
des résultats encore plus mauvais qui pourraient être justi…és en partie par la crise.
En moyenne, près de 55000 jugements d’ouvertures de procédures ont été prononcés
par an, près de 67% des défaillances entre 2006 et 2010 conduisent à une liquidation immédiate et environ 75% des procédures de redressement aboutissent à une
liquidation à l’issue de la période d’observation (voir Tableau 2).
Dans ce contexte, nous pouvons nous interroger si la situation est encore pire à
cause des erreurs de sélection inhérentes à tout système de défaillance. En e¤et, un
système pro-débiteur qui favorise le redressement des entreprises viables engendrerait
inévitablement le redressement d’entreprises non-viables (erreur de sélection de Type
I) et un système pro-créancier qui favorise l’élimination des entreprises non viables
engendrerait inévitablement l’élimination d’entreprises viables (erreur de sélection
de Type II) [White (1989, 1994a, 1994b), Mooradian (1994), Fisher et Martel (1995,
2004)].
3 La
loi n 2005-845 du 26 juillet 2005 de sauvegarde des entreprises a intégré la cession
globale de l’entreprise dans la procédure de liquidation (Art. 97).
5
Etant donné que le système français favorise clairement la sauvegarde des entreprises (système pro-débiteur), nous pouvons nous interroger sur l’existence d’un biais
envers la réorganisation des entreprises non pro…tables et si …nalement, même les
20% des entreprises pour lesquelles un plan de réorganisation a été con…rmé ne
seraient pas liquidées peu de temps après.
Au vu de ce qui précède, il apparaît que la législation française en matière de
défaillances présente un cadre d’analyse à la fois intéressant et original d’autant
plus que peu d’études ont été e¤ectuées sur les redressements judiciaires en France.
L’objet de cette thèse est de combler ce manque en menant une étude empirique sur
la réorganisation judiciaire des entreprises en di¢ cultés dans le contexte français.
Dans un premier temps, nous examinons un aspect particulier de la loi française
qui consiste à permettre la réorganisation de l’entreprise par voie de cession comme
alternative à la réorganisation par voie de continuation. Dans un deuxième temps,
nous nous interrogeons sur l’e¢ cacité ex post de la procédure de réorganisation et
plus spéci…quement sur la performance des entreprises réorganisées et ses déterminants. La performance sera évaluée selon trois critères : 1) l’exécution du plan de
continuation, 2) la performance comptable et 3) la survie des entreprises réorganisées.
Compte tenu de la problématique, il est possible de formuler les questions de
recherche suivantes :
1. Existe-t-il une di¤érence entre les entreprises réorganisées par voie de continuation et les entreprises réorganisées par voie de cession ? (Chapitre 3)
2. Quels sont les facteurs qui déterminent l’issue de la procédure de réorganisation
(continuation versus cession) ? (Chapitre 4)
3. Quels sont les déterminants de succès des plans de réorganisation con…rmés
par le juge? (Chapitre 5)
6
4. Est-ce que la procédure de réorganisation permet à des entreprises non profitables de continuer leurs opérations ? (Chapitre 6)
5. Quelles sont les variables …nancières qui déterminent le «succès» ou l’«échec»
de l’entreprise réorganisée ? (Chapitre 6)
6. Comment peut-on modéliser l’aspect dynamique de la survie des entreprises
réorganisées ? Quelles sont les déterminants de la survie des entreprises réorganisées?
(Chapitre 7)
Nous proposons de présenter nos travaux, nos résultats et notre contribution à
travers sept chapitres.
Le premier chapitre est cette introduction qui a pour objectif de présenter la
motivation et la problématique ainsi que les questions de la recherche et une brève
description des chapitres qui composent cette thèse.
Le deuxième chapitre dresse une revue de la littérature tant théorique qu’empirique
autour des concepts de défaillances, réorganisation et liquidation. Notre présentation
des travaux antérieurs s’organise autour de cinq thèmes principaux : la nécessité
d’une législation en matière de défaillances, les objectifs des procédures de réorganisation et de liquidation, l’évaluation de l’e¢ cacité des lois de faillite selon un certain
nombre de critères, les mécanismes alternatifs à la loi de faillite et une brève revue
de travaux antérieurs menés autour de la défaillance dans le contexte français.4 Dans
ce chapitre, nous présentons également le droit français des entreprises en di¢ cultés.
L’accent est mis sur la législation sur laquelle porte l’étude (1995-2004).
Le troisième chapitre présente une description détaillée des entreprises réorganisées par voie de continuation ou de cession. Nous utilisons une base de données
originale construite à partir de 500 dossiers de redressement ouverts entre 1995 et
4 Les
critères que nous avons utilisés pour juger l’e¢ cacité d’une loi de faillite sont les
suivants : les erreurs de sélection, les coûts de faillite, la lenteur des procédures, le respect
de la règle de priorité absolue et le taux de recouvrement des créances.
7
2004 au tribunal de commerce de Paris et ayant abouti à la con…rmation d’un plan
de continuation ou de cession. Toutes les données de cette base ont été collectées
manuellement et ont permis de fournir de l’information détaillée sur les caractéristiques des entreprises (forme, secteur, âge, taille, solvabilité) et de leurs créances selon
l’issue de la procédure de réorganisation (continuation ou cession). Nous présentons
également dans ce chapitre des données spéci…ques aux continuations et aux cessions.
Une autre section est consacrée aux causes de défaillances signalées par le débiteur
au moment du dépôt de la déclaration de cessation des paiements. En…n, nous nous
intéressons à la durée des di¤érentes étapes de la réorganisation selon l’issue de la
procédure.
Ce chapitre consacré à la description des données montre que près de 99% des
entreprises dans l’échantillon sont des petites et moyennes entreprises, les entreprises
cédées étant plus grandes. Nous observons également que la plupart des entreprises
sont fortement endettées à l’ouverture de la procédure et que les taux de recouvrement des créances sont très faibles pour les cessions et dépendent du résultat de
l’exécution du plan pour les continuations. Nous remarquons que le remboursement
des créances est souvent étalé sur plusieurs années dans les plans de continuation.
Dans le quatrième chapitre, nous nous intéressons aux deux possibilités o¤ertes
au tribunal pour assurer le redressement de l’entreprise à savoir la continuation et
la cession. A travers une brève revue de la littérature, nous présentons les avantages et les limites de chacune des deux alternatives. Ensuite, nous procédons à
l’identi…cation des facteurs susceptibles d’in‡uencer l’issue de la procédure de réorganisation (continuation ou cession) en se basant sur des recherches antérieures et
sur les spéci…cités de la législation française. Dans la partie empirique de ce chapitre,
nous estimons des modèles LOGIT en utilisant la base de données décrite dans le
chapitre précédent et en tenant compte des caractéristiques de l’échantillon estimé.
8
Les résultats de l’estimation montrent que la rentabilité de l’entreprise augmente
la probabilité d’une réorganisation par voie de continuation alors que la taille des
actifs de l’entreprise, le montant des créances privilégiées par rapport au montant
des actifs et la proportion des actifs tangibles augmentent la probabilité d’une réorganisation par voie de cession. Nous trouvons également que certaines causes de
défaut in‡uencent signi…cativement l’issue de la procédure.
Le cinquième chapitre examine l’e¢ cacité de la procédure de redressement selon
l’issue du plan de continuation (succès ou échec). En se basant sur la dé…nition
juridique, nous considérons qu’un plan est réussi si tous les engagements prévus par
le plan ont été respectés. Cette dé…nition nous permet de déterminer le taux de
réussite des plans de continuation dans notre échantillon. La partie économétrique
de ce chapitre vise à construire un modèle LOGIT permettant d’identi…er les déterminants de succès d’un plan de continuation. Nous utilisons un échantillon constitué
d’entreprises réorganisées par voie de continuation et dont l’issue du plan (succès ou
échec) est connue. Dans la dernière partie du chapitre nous examinons le pouvoir de
prédiction du modèle obtenu.
Nous trouvons que, seulement 44% des entreprises réussissent à exécuter le plan
de continuation. Les estimations indiquent que la probabilité de succès d’un plan
augmente avec l’âge de l’entreprise, la concentration des créances bancaires, le pourcentage du premier versement aux créanciers prévu par le plan et la rentabilité du
secteur d’activités de l’entreprise. Le modèle estimé permet de classer près de 71%
des entreprises dans l’échantillon estimé.
Dans le sixième chapitre, nous abordons l’e¢ cacité de la procédure de redressement à travers l’évaluation de la performance des entreprises réorganisées. Le choix
des mesures de performance est guidé par des recherches antérieures. La performance
des entreprises est mesurée aussi bien avant le jugement d’ouverture de la procédure
9
de redressement qu’après la con…rmation du plan de réorganisation. Nous estimons
également un modèle LOGIT pour examiner l’impact de certaines mesures …nancière
de l’entreprise sur la probabilité de succès de la réorganisation. Dans ce chapitre,
nous considérons que la réorganisation de l’entreprise est réussie si l’entreprise reste
active pendant au moins quatre ans après la con…rmation du plan de continuation.5
Les résultats de l’estimation montrent que la taille des actifs de l’entreprise et
la rentabilité des actifs de l’entreprise (mesurées durant l’année de con…rmation)
augmentent la probabilité que l’entreprise reste active pendant au moins quatre ans
après la con…rmation du plan de continuation.
Finalement, dans le septième chapitre, nous appliquons les techniques de l’analyse
de survie aux entreprises réorganisées pour examiner l’endurance des entreprises réorganisées. L’analyse de survie porte sur deux modèles: un modèle non paramétrique
(le modèle de Kaplan-Meier) et un modèle semi-paramétrique (le modèle de Cox).
Nous commençons par estimer le modèle Cox avec des variables mesurées à une
date …xe. Ensuite, nous estimons le modèle avec des variables dépendantes du temps
pour prendre en compte l’évolution des variables …nancières au cours du temps.
L’estimation du modèle permet d’identi…er les déterminants de la survie des entreprises réorganisées et de représenter la probabilité de survie au-delà d’un laps de
temps donné.6
Le modèle Cox estimé avec des variables dépendantes du temps identi…e trois variables ayant un impact positif sur la survie de l’entreprise réorganisée : la rentabilité
de l’entreprise, sa liquidité et la rentabilité du secteur d’activités de l’entreprise.
5 Les
données utilisées dans ce chapitre concernent 152 entreprises réorganisées par voie
de continuation dont la procédure de redressement a été ouverte entre 2001 et 2004 au
tribunal de commerce de Paris et dont les états …nanciers sont contenus dans la base de
données DIANE.
6 Les données utilisées dans ce chapitre concernent 131 entreprises réorganisées par voie
de continuation dont la procédure de redressement a été ouverte entre 2001 et 2004 au
tribunal de commerce de Paris et dont les états …nanciers sont contenus dans la base de
données DIANE.
10
Nous montrons également que l’endettement a un e¤et de seuil sur la survie de
l’entreprise. Plus précisément, le fait qu’une entreprise «insolvable» devienne «solvable» au cours du temps a un e¤et positif sur la survie de l’entreprise réorganisée.
Bibliography
[1] Domens J. (2007), Les Défaillances d’Entreprises entre 1993 et 2004,
PME/TPE en Bref, Ministère de l’économie, des …nances et de l’emploi.
[2] Fisher T.C.G. et Martel J. (1995), “The Creditors’ Financial Reorganization
Decision: New Evidence from Canadian Data”, Journal of Law, Economics and
Organization, Vol. 11, pp. 112-126.
[3] Fisher T.C.G. et Martel J. (2004), “Empirical Estimates of Filtering Failure in
Court-Supervised Reorganization”, Journal of Empirical Legal Studies, Vol. 1,
No. 1, pp. 143-164.
[4] Franken S. (2004), “Creditor and Debtor Oriented Corporate Bankruptcy
Regimes Revisited”, European Business Organization Law Review, Vol. 5, No.
4, pp. 645-676.
[5] Gresse C. (2003), Les Entreprises en di¢ cultés, 2eme ed., Paris, Economica.
[6] Mooradian R. M. (1994), “The E¤ect of Bankruptcy Protection on Investment:
Chapter 11 as a Screening Device”, Journal of Finance, Vol. 49, No. 4, pp.
1403-1430.
[7] Pochet C. (2001), “Traitement Légal de la défaillance et Gouvernance: une
Comparaison Internationale”, Revue Internationale de Droit Economique, Vol.
15, No. 4, pp. 465-488.
11
12
[8] White M. J. (1989), “The Corporate Bankruptcy Decision”, Journal of Economic Perspectives, Vol. 3, No. 2, pp. 129-151.
[9] White M. J. (1994a), “Does Chapter 11 Save Economically Ine¢ cient Firms?”,
Washington University Law Quarterly, Vol. 72, No. 3, pp. 1319-1340.
[10] White M. J. (1994b), “Corporate Bankruptcy as a Filtering Device: Chapter 11
Reorganizations and out-of-court Debt Restructurings”, Journal of Law, Economics and Organization, Vol. 10, No. 2, pp. 268-295.
56,22%
% Défaillances
Source: Altares / Deloitte
28729
15,15%
Liquidations immédiates
% Redressement
3389
84,85%
% Redressement
dont réorganisations
18980
22369
43,78%
Redressements
% Défaillances
dont liquidations
51098
1995
Défaillances
Année
59,61%
30535
16,89%
3495
83,11%
17193
40,39%
20688
51223
1996
62,77%
31317
18,04%
3352
81,96%
15226
37,23%
18578
49895
1997
62,31%
27016
17,58%
2873
82,42%
13466
37,69%
16339
43355
1998
63,29%
24917
17,14%
2477
82,86%
11974
36,71%
14451
39368
1999
64,57%
23789
17,45%
2278
82,55%
10776
35,43%
13054
36843
2000
63,72%
22605
18,44%
2373
81,56%
10499
36,28%
12872
35477
2001
64,07%
23648
22,19%
2943
77,81%
10317
35,93%
13260
36908
2002
64,03%
24742
25,42%
3534
74,58%
10366
35,97%
13900
38642
2003
Tableau 1 : Répartition des Défaillances selon la Procédure et son Issue entre 1995 et 2004
64,17%
25511
29,80%
4245
70,20%
9998
35,83%
14243
39754
2004
62,19%
262809
19,38%
30959
80,62%
128795
37,81%
159754
422563
1995-2004
65,93%
% Défaillances
Source: Domens (2007)
31045
27%
4332
73%
Liquidation immédiate
% Redressement
dont réorganisations
% Redressement
11714
16046
34,07%
Redressement
% Défaillances
dont liquidations
47091
2006
Défaillances
Année
65,58%
32690
22%
3775
78%
13385
34,42%
17160
49850
2007
67,59%
37962
24%
4368
76%
13832
32,41%
18200
56162
2008
68,49%
42189
22%
4463
77%
14943
31,51%
19406
61595
2009
68,21%
40024
30%
5595
70%
13055
31,79%
18650
58674
2010
67,27%
183910
25%
22533
75%
66929
32,73%
89462
273372
2006-2010
Tableau 2 : Répartition des Défaillances selon la Procédure et son Issue entre 2006 et 2010
Chapter 2
The Economics of Corporate Bankruptcy
2.1
Introduction
This chapter comprises two major sections. Section 2.2 presents a review of the
literature on bankruptcy. It outlines the issues surrounding the followings topics: the
rationale for a bankruptcy law, the objectives of bankruptcy, the economic e¢ ciency
aspects of bankruptcy law, the alternative mechanisms to bankruptcy, and a brief
review of empirical evidence on bankruptcy in the French context. The second major
section of this chapter (Section 2.3) presents an overview of the main features of the
French legislation on bankruptcy. In this section, particular focus is placed on the
legislation in e¤ect at the time of the study (1995-2004).
2.2
2.2.1
Corporate bankruptcy: a literature review
The rationale for a bankruptcy law
The role of a formal bankruptcy proceeding is to provide a collective procedure for
resolving problems that occur when a …rm is unable to pay its debts. In this section, we examine the impediments to the informal resolution of …nancial distress to
15
16
justify the necessity of bankruptcy mechanism in any economy. Much of the subsequent literature identi…es four impediments to private reorganization mechanisms:
(a) contract incompleteness; (b) coordination and free rider problem; (c) con‡icts of
interest; and (d) information asymmetry.
a- Contract incompleteness
In an ideal world, there would be no need for bankruptcy law since debtors and
creditors would anticipate the possibility of default and specify the contract accordingly. That is, investors who pool their assets may divide rights of payout, control,
withdrawal, and priority among themselves (Baird, 1986). In such a world, bankruptcy law has only a limited role; it comes into play when multiple withdrawal
rights are triggered and the exercise of these rights by individual investors is costly
and interferes with the deployment of the …rm’s assets (Bradley and Rosenzweig,
1992).
Aghion et al. (1992) argue that, in practice, writing such contracts is likely to
be very di¢ cult and costly especially when there are many creditors. Moreover, the
debtor may acquire di¤erent types of assets and new creditors as time passes, and it
may be very hard to specify how the division process should change as a function of
such developments. Finally, even if a substantial number of parties choose to make
their own arrangements, those parties that make no arrangements at all still need
the bankruptcy mechanism provided by the state.
b- Coordination and free rider problem
Under non-bankruptcy law, each creditor has an incentive to be the …rst to sue
the debtor for payment if the …nancial situation becomes precarious. Uncoordinated
debt collection by the various creditors can be very costly. First, creditors will expend
resources trying to be …rst to seize their collateral or to obtain a judgment against
17
the debtor. Second, this race by creditors to be …rst may lead to the dismantlement
of the …rm’s assets and to a loss of value for all creditors if the …rm is worth more as
a whole than as a collection of pieces [White (1984), Aghion et al. (1992)]. According
to Baird (1986), bankruptcy law prevents a costly and destructive race to the …rm’s
assets by o¤ering a collective proceeding that freezes the rights of all investors in a
…rm, values them, and then distributes these assets according to the priority scheme
that the parties agreed.
Besides, coordination among debtholders results in another impediment to the
resolution of …nancial distress through private mechanisms: the free rider problem.
Generally, informal public debt restructuring are accomplished through an exchange
o¤er. The old debt contract is replaced with a new contract that involves a reduction
in the interest payments or an extension of the maturity date. Exchange o¤ers grant
holders the right (but not the obligation) to participate, so some bondholders may
prefer to “holdout”hoping that the post-exchange o¤er value of their existing claim
will exceed the value of the tendering debtholders claims. Since all bondholders have
similar incentives, the exchange o¤er is likely to fail. Gertner and Scharfstein (1991)
present a model of a …nancially distressed …rm with outstanding bank debt and
public debt and focus on coordination problems among numerous public debtholders
as the main source of ine¢ ciency. The authors show that underinvestment tends to
be a problem with senior bank debt, short-term public debt, and when debt is
protected by seniority covenants. Overinvestment tends to be a problem with junior
bank debt, long-term public debt, and when a …rm can strip seniority covenants with
exit consents.
Brown (1989) and Gertner and Scharfstein (1991) show that the structure
imposed by the code mitigates the holdout problem created by the individual
claimant’s divergent incentives and increases investment. Particularly, the voting
procedure does not allow public debtholders to be treated di¤erently depending
18
on their vote, whereas tendering and non-tendering public debtholders are treated
di¤erently.
c- Con‡icts of interests and coalition formation
Brown (1989) examines the way in which con‡icts of interest among claimholders can
inhibit the resolution of …nancial distress through an informal reorganization. The
model shows that con‡icting incentives of the claimholders classes make unanimous
agreement on a plan di¢ cult to achieve. Each class has an incentive to reject any
proposed plan and to propose a more favourable plan. Consequently, the private
game is likely to result in a continuous proposal process during which resources are
dissipated.
In the same paper, Brown demonstrates that the bankruptcy code, by providing
rules governing the negotiation process, yields a unique solution to the reorganization
process. Speci…cally, in the formal game, the impairment rule on voting, the agenda
rule, and the cram down rule are the key elements that determine the outcome of
the reorganization.
Besides, con‡icts of interest can lead to the formation of coalitions in order to
extract concessions from other claimants.1 Bulow and Shoven (1978) and White
(1981) develop models that focus on the con‡icts of interest among three classes of
claimants: the bondholders, the bank lenders, and the equity holders. The authors
assume that bank creditors and equity may act as a coalition in determining whether
or not the …rm goes bankrupt. This assumption is motivated by the observation
that equity holders may be willing to compensate the bank up to the full value of
its claim to ensure that the …rm stays in operation. Bulow and Shoven (1978) and
White (1981) demonstrate that the actions of the bank plus the equity holders are
1 The
formation of coalitions can also arise in formal bankruptcy. But, the role of bankruptcy law is to minimize this problem.
19
not based on maximizing the total value of the …rm and may be taken at the expense
of the bondholders. Gertner and Scharfstein (1991) also examine the behaviour of
the coalition formed by equity holders and the bank. They show that a bank debt
restructuring origins a transfer that can be positive or negative from the bank and
equity holders to public debtholders. If the transfer is positive, the …rm will tend to
forego positive NPV (Net Present Value) projects. Otherwise, the …rm may adopt
negative NPV projects.
White (1984) also argues that a coalition of managers and equity holders may
…nd it desirable to undertake risky projects since the coalition gets the …rm’s high
earnings if a good outcome occurs. If a bad outcome occurs, limited liability allows
equity holders to avoid bearing the …rm’s losses, which are shifted to debt. Equity
holders and managers have also an incentive to avoid liquidation at all costs because
equity is inevitably wiped out and managers’jobs and shares are lost in liquidation.
Alternatively, if they expect that liquidation is inevitable, they may waste the …rm’s
resources.
d- Information asymmetry
The problem of designing and completing an informal debt restructuring is exacerbated in the case of …nancially distressed …rms by information asymmetries. Asymmetric information arises when one of the involved parties in the workout arrangement has more information than others. Asymmetric information concerns the type
of the …rm. Generally, managers know whether their …rms are viable or non-viable,
but creditors do not. According to Senbet and Seward (1995), the existence of asymmetric information in the case of …nancially distressed …rms emanates from two
possible sources. First, corporate insiders and outside investors may, based on their
di¤erential information, simply disagree about the value of the …rm. Second, when
20
the …rm is …nancially distressed, insiders may have an incentive to intentionally misrepresent value in order to convince bondholders to agree to exchange their existing
claims for lower valued securities.
Mooradian (1994) examines the e¤ect of both the collective action problem and
information asymmetry on the investment decision. The model shows that there
exist only pooling equilibriums in which either all …rms renegotiate and invest or all
…rms liquidate. Debt holders learn nothing about …rm type or …rm value from o¤ers
to renegotiate since bad …rms will always mimic the good …rms whenever liquidation
is the alternative.
Martel (2003) proposes a model of …nancial reorganization in the presence of
asymmetric information which exploits the information content of the proposal. The
…rm uses the structure of the reorganization contract to convey information to creditors about its own viability. In particular, …rst period payments are used to signal
the …rm’s level of viability. The author shows that there exists a separating equilibrium in which the proportion of cash payments increases with …rm’s type. In
addition, Martel (2003) presents empirical evidence consistent with the predictions
of the model. Based on a data set of 393 commercial reorganization proposals …led
in Canada, the author shows that the probability of success of a proposal increases
with the proportion of short term payments (within six months) to creditors.
2.2.2
The objectives of a bankruptcy law
There are two schools as to the objectives of a bankruptcy law: the free marketers
and the traditionalists. The …rst approach focuses exclusively on the maximisation of
the …rm’s value whereas the second approach includes economic and non-economic
objectives.
21
The free marketers approach
According to this approach, bankruptcy law should serve three objectives: (a) expost e¢ ciency; (b) ex-ante e¢ ciency; and (c) screening role.
a- Ex-post e¢ ciency
First, a good bankruptcy procedure should deliver an ex-post e¢ cient outcome,
that is, it should maximize the total value available to be divided between the
di¤erent claimants. A …rm should be reorganized, sold for cash as a going concern,
or closed down and liquidated piece-meal according to which of these alternatives
would generate the greatest total value (Hart, 2000). Speci…cally, Bebchuk (1998)
identi…es two elements to this objective in the case of reorganization. On the one
hand, it is desirable that as little value as possible will be dissipated during this
process. On the other hand, when the reorganization process ends, the company’s
assets should be allocated to their highest-valued use.
Second, a good bankruptcy procedure should ensure an optimal division of total
value. This ex-post division has important ex-ante consequences on incentives and
behaviour. Particularly, a basic question for the design of bankruptcy law concerns
whether value should be divided in accordance with absolute priority. That is, junior
creditors cannot receive any payments before the claims of senior creditors have
been fully paid and equity holders are last in the distribution of proceeds. As often
mentioned in the literature, the value should be divided according to the absolute
priority rule. However, a number of scholars have pointed out that some portion of
value should be reserved for shareholders; otherwise they will do anything to avoid
bankruptcy, including undertaking highly risky investment projects and delaying a
bankruptcy …ling (Hart, 2000).
22
b- Ex-ante e¢ ciency
The second goal concerns ex-ante e¢ ciency. A good bankruptcy procedure should
give the right incentives to debtors and managers before bankruptcy. It should preserve the bonding role of debt by penalizing managers and shareholders in bankruptcy states. If bankruptcy procedure treats managers too softly, debt would no
longer have any bonding role: management would have no incentive to pay their
debts since they have nothing to lose from default (Aghion et al., 1992).
c- Screening role
The bankruptcy law should give the right incentives to save economically viable
…rms and eliminate non-viable …rms. However, as pointed by White (1989, 1994b), it
might be impossible to meet simultaneously this objective. A bankruptcy law which
favours the reorganization of viable …rms is also likely to save non-viable …rms.
Conversely, a law which favours the elimination of non-viable …rms is also likely to
eliminate viable …rms.
The traditionalist approach
According to this approach, bankruptcy law should pursue simultaneously economic
and non-economic objectives. Speci…cally, the law should play a social role and protect even parties that do not hold claims against the …rm and may be a¤ected in the
future, i.e. employees, government, suppliers etc. The French bankruptcy law re‡ects
the importance attached to the social dimension. In fact, preserving employment
constitutes the second objective of the reorganization procedure and this objective
comes before the reimbursement of creditors.
23
2.2.3
The existing bankruptcy laws and e¢ ciency
In what follows, we shall examine the e¢ ciency characteristics of the courtsupervised methods of resolving bankruptcy and the available evidence. Speci…cally,
we will focus on …ltering failure errors, bankruptcy costs, length of proceedings,
absolute priority rule deviation, and creditors’repayment.
a- Filtering failure
White (1994a) and Fisher and Martel (1995) de…ne two types of error that may
occur in bankruptcy procedures: Type I error occurs if ine¢ cient …rms are allowed
to reorganize and Type II error occurs if e¢ cient …rms shut down in liquidation.
Type I and Type II errors are caused by the presence of asymmetric information
concerning the viability of the …rm.
Mooradian (1994) and White (1994a) examined Chapter 11 as a screening mechanism and developed theoretic models to evaluate the economic e¢ ciency of U.S.
bankruptcy procedures. The major conclusion of White’s model is that the presence
of asymmetric information in the context of bankruptcy law can give rise to …ltering
failure equilibrium. Filtering failure occurs because managers of e¢ cient …rms bene…t from pooling with ine¢ cient …rms since creditors accept lower compensation
than they would if they knew the …rm was e¢ cient, while managers of ine¢ cient
…rms bene…t from pooling in the sense that it would enable them to obtain the gains
from reorganization.
Mooradian (1994) shows that Chapter 11 reduces incentives for ine¢ cient …rms
to mimic e¢ cient …rms.2 More precisely, Chapter 11 increases e¢ ciency to the extent
that it allows e¢ cient …rms to renegotiate and continue where they would otherwise
2 Under
some conditions, there exists a separating equilibrium in which good …rms
renegotiate and invest and bad …rms …le for bankruptcy.
24
be liquidated. However, Chapter 11 decreases e¢ ciency to the extent that economically ine¢ cient …rms …le for bankruptcy rather than liquidate. The most important
prediction of this model is that a larger proportion of distressed …rms in Chapter 11
are ine¢ cient.
Some scholars investigated empirically the e¢ ciency of bankruptcy law as a
screening mechanism. For example, Kahl (2001) analyzes the process of …nancial
distress from its onset to its resolution for a sample of 95 …rms that enter …nancial
distress between 1979 and 1983 including …rms that never entered Chapter 11 as
well as …rms that entered Chapter 11 at some point during the process. The author
investigates the role played by Chapter 11 in the selection process. The results suggest that …ling for Chapter 11 has a negative e¤ect on a …rm’s survival chances,
it leads to a longer process of …nancial distress and allows somewhat less viable
…rms to emerge from …nancial distress (Type I error). In another empirical study,
Fisher and Martel (2004) present the …rst empirical estimates of …ltering failure in
a court-supervised reorganization procedure using a sample of 303 …rms attempting
reorganization in Canada during the 1977-1988 period. Two methods were proposed
for measuring …ltering failure. An ex post measure is derived using observed outcomes for …rms in reorganization and an ex ante measure is constructed using a logit
model. The results of the study indicate that creditors are four times more likely to
accept proposals from non-viable …rms than reject proposals from viable …rms and
that the incidence of …ltering failure is between 18% and 41% for ex post estimates
and between 22% and 53% for ex ante estimates.
Other studies assess the post-bankruptcy performance of reorganized …rms to
measure Type I errors since a poor post-bankruptcy performance supports the presence of a bias towards the reorganization of ine¢ cient …rms.3
3 See
Chapter 6 for more details.
25
b- Bankruptcy costs
Bankruptcy costs are generally divided into direct and indirect costs. In this section,
we review empirical evidence on formal bankruptcy proceedings costs.
Direct costs include legal, accounting, …ling, and other administrative costs.
There have been several empirical studies attempting to establish the level of direct
bankruptcy costs. Altman (1984) measures direct bankruptcy costs for a sample
of 19 bankrupt companies from 1974 to 1978. He …nds an average ratio of direct
bankruptcy costs to …rm value of 6.2% measured just prior to bankruptcy and 4.3%
measured at 3 years prior to bankruptcy.4 Weiss (1990) studies a sample of 37 …rms
that …led for bankruptcy between 1979 and 1986. He …nds that, on average, the
direct costs of bankruptcy represent 20.6% of the market value of equity, 3.1% of the
book value of debt plus the market value of equity, and 2.8% of the book value of
total assets. Bris et al. (2006) study a sample of 225 Chapter 11 cases and 61 Chapter
7 cases …led in Arizona and Southern New York from 1991 to 2001. The authors …nd
a mean (median) ratio of about 8.1% (2.5%) for Chapter 7 and 16.9% (1.9%) for
Chapter 11 when direct costs are measured as a fraction of pre-bankruptcy assets
and a mean (median) ratio of about 2.9% (0.4%) for Chapter 7 and 11.5% (1.4%) for
Chapter 11 when direct costs are measured as a fraction of total liabilities. With the
latter measure, Chapter 7 seems to be cheaper than Chapter 11. Tucker and Moore
(1999) examine the factors that in‡uence direct bankruptcy costs. Regression results
indicate that the size of the case and the number of claimants in the proceeding
complexity increase direct bankruptcy costs and that Chapter 7 is more costly than
4 The
total value of the …rm was measured by adding the market value of equity to
the market value of debt plus the book value of other debt plus the capitalized value of
…nancial leases.
26
Chapter 11.5 Fisher and Martel (2005) measure direct costs of bankruptcy using a
sample of 622 commercial bankruptcies …led under Canadian Law during the 19771988 period. The data indicate that the administrative costs/debt ratios are similar
for reorganizing and liquidating …rms: the mean (median) values are 5.1% (3%) for
reorganizing …rms and 5% (3.4%) for liquidating …rms. When measured relative to
total assets, administration costs are substantially larger for liquidating …rms: the
mean (median) values are 18.4% (7.3%) for reorganizing …rms and 54.9% (47.2%)
for liquidating …rms. Fisher and Martel (2005) also investigate the factors a¤ecting
the amount of direct costs. Consistent with Tucker and Moore (1999), the results
indicate that direct costs depend on …rm size, on the complexity of the case, and on
the ability of the bankrupt …rm to pay. An important …nding in Fisher and Martel
(2005) is that 40% of the …rms opted for reorganization or liquidation even though
it was the most expensive alternative on terms of administration costs. This …nding
suggests that …rms may base their bankruptcy decision on factors other than direct
bankruptcy costs. There are many empirical studies attempting to identify these
factors.
Indirect costs arise in the form of opportunity costs, resulting from ine¢ cient
functioning during the …nancial distress: on the one hand, the management decisions
during the process are likely to be distorted because management’s incentives during
the process are generally not well aligned with the maximization of reorganization
value; on the other hand, customers, suppliers, and employees may undertake suboptimal actions in response to …nancial distress or may be reluctant to deal with the
company or may demand favourable terms. The fundamental di¢ culty in empiricism
arises from an inability to distinguish these costs from those that would have arisen
5 The
explanatory variables of the model include an indicator variable representing the
Chapter of the Bankruptcy under which the …rm …le. The coe¢ cient estimate for this
variable is found to be positive and signi…cant.
27
from pure business dislocation and distress. Altman (1984) is the …rst to present
a proxy methodology for measuring indirect costs based on the foregone sales and
pro…ts concept. Precisely, expected pro…ts for the period up to three years prior
to bankruptcy were compared to actual pro…ts (losses) to determine the amount
of bankruptcy costs (unanticipated pro…ts or losses). Altman (1984) presents two
ways in estimating pro…ts. The …rst is a regression procedure based on industry
sales. The second involves the use of experts’ expectations of …rm pro…ts for the
years prior to bankruptcy. Using the …rst method, Altman (1984) …nds that indirect
bankruptcy costs amount, on average, to 10.5% or 8.1% of the …rm value depending
on whether they are measured at the time of bankruptcy or three years prior to
bankruptcy. Indirect costs ratios as measured by the second method are found to
be more important ranging from 18% just prior to bankruptcy to 22% for the three
annual statements prior to …ling. As pointed by Opler and Titman (1994), an important problem with Altman’s approach is that he attributes sales drops to …nancial
distress. However, one can also argue that unexpected declines in sales are likely to
have contributed to …nancial distress. Opler and Titman (1994) examine the indirect
costs of …nancial distress in a way that minimizes the problem of causality using a
sample of 46,799 publicly-traded …rms over the 1972-1992 period. Their approach
consists in identifying industries that have experienced economic distress rather than
distressed …rms and in investigating the relationship between …rms’performance in
those industries and their leverage ratios prior to the distressed period.6 The evidence indicates that during industry downturns, more highly leveraged …rms tend
to lose market share and experience lower operating pro…ts than their competitors.
Another criticism addressed to Altman’s approach is that indirect costs are mea6 The
intuition behind this approach is that highly leveraged …rms will have the greatest
operating di¢ culties in a downturn, if …nancial distress is costly. Alternatively, if …nancial
distress bene…ts …rms, then we would expect the opposite.
28
sured prior to bankruptcy. Kalay et al. (2007) estimate indirect bankruptcy costs by
measuring changes in the …rm’s industry-adjusted and normalized operating income
over the bankruptcy period based on a sample of 459 …rms …ling for Chapter 11 over
the 1991-1998 period. Contrary to previous studies, empirical evidence is inconsistent with the hypothesis that Chapter 11 results in net indirect costs. Particularly,
Kalay et al. (2007) indicate that sample …rms experience signi…cant improvements in
their operating performance during Chapter 11. Moreover, inconsistent with Opler
and Titman (1994), …rms with higher debt ratios experience greater improvements
in operating performance. Bris et al. (2006) use two “noisy”measures of the indirect
costs of bankruptcy: the change in reported assets value during bankruptcy and the
time in bankruptcy.
c- Length of proceedings
The length of time companies remain in bankruptcy is very important. Franks and
Torous (1994) and Bris et al. (2006) argue that it can be used as a (very noisy)
proxy for indirect bankruptcy costs. LoPucki (1993) gives a detailed description
of the ine¢ ciencies associated with prolonged proceedings. First, managers of an
insolvent company may have inappropriate incentives toward high risk investment
and therefore undertake poor investment policies. Second, the longer the case is,
the higher the fees would be. Third, insolvent companies generally perform poorly
because partners are reluctant to deal with them and managers spend a lot of time
in legal matters instead of tendering to operations. Fourthly, a common strategy
for a debtor who cannot avoid default is to suspend payments to all its creditors.
Such a suspension of payments by one debtor often forces creditors of that debtor
into bankruptcy, creating a domino e¤ect. Lastly, the lengthening of the time may
increase wealth transfers between di¤erent classes of creditors.
29
White (1984) studies a sample of 64 …rms that …led for bankruptcy under Chapter
11 in Manhattan, during the 1980-1982 period. Based on a sample of 26 con…rmed
plans, the author estimates an average time in reorganization of 17 months.7 Franks
and Torous (1989) estimate that the average time is about 44 months for a sample of
30 …rms that emerged from Chapter 11 during the 1970-1984 period. Flynn (1989)
…nds an average time in reorganization of 25 months and a median time of 22 months.
the author reports that 18% of con…rmations happen less than one year after …ling,
43% between one and two years, 22% between two and three years, and 17% after
more than three years from …ling. However, the study shows substantial di¤erences
between the 15 study districts.8 Consistent with Flynn (1989), Jensen-Conklin (1992)
…nds that the average time for con…rmation was 22 months for a sample of 45 cases.
More recently, Denis and Rodgers (2007) study duration according to the outcome
of 224 Chapter 11 …lings during the 1985-1994 period. They …nd that the median
…rm spends approximately 17 months in Court. The median …rm that is liquidated
spends 9.2 months in Court; this is signi…cantly less time than the median …rm that
is either acquired (16.9 months) or reorganized (19.9 months). In addition, Denis
and Rodgers (2007) investigate the determinants of the time spent in Chapter 11.
The results indicate that larger …rms and …rms with higher liability ratios spend
more time in Chapter 11 while …rms that reorganize in higher margin industries
and having a better relative performance spent less time in Chapter 11. Contrary
to previous studies, Bris et al. (2006) de…ne time in bankruptcy as the time spent
from …ling to the closure of the case and they identify three phases for Chapter 11:
from …ling to plan, from plan to con…rmation, and from con…rmation to closure.
7 Typically,
in the U.S., the time in reorganization is de…ned as the time between the
…ling of the proposal and con…rmation by the bankruptcy court and the time in liquidation
is the time required to liquidate the …rm’s assets.
8 The average time from …ling to con…rmation ranged from 531 to 996 days and the
median time ranged from 461 to 906 days.
30
They …nd that Chapter 11 procedure takes a total of about 29 months and Chapter
7 procedure takes a total of about 22 months on medians. More interestingly, the
authors examine the determinants of the overall time spent in bankruptcy and of
the time spent in each phase. First, …rms with less secured creditors and …rms where
managers own a majority of shares take more time to …le a plan. Second, …rms
with less unsecured creditors and …rms that have an unsecured creditors’committee
take less time to con…rm the plan. Finally, the identity of the judge matters for
all three phases. In Canada, Fisher and Martel (1999) …nd that the average time
between …ling and voting by unsecured creditors is about one month and a half
(50 days). Moreover, they report that 60% of the proposals are voted within one
month, 84% within 2 months, and 90% within 3 months. The authors also estimate
an average time between …ling and con…rmation of 80 days. Thus, the results suggest
that Canadian reorganization system is quicker at con…rming plans than is Chapter
11. In a more recent study, Fisher and Martel (2009) report that the mean (median)
time between the …ling date and the discharge of the debtor by the Court is around
3.11 (2.64) years for a sample of 314 …rms undergoing reorganization.
Another set of empirical studies compare the time spent in reorganization process
and in other alternatives to reorganization. For example, Gilson et al. (1990) examine
169 …nancially distressed public companies that experienced extreme stock price
declines and for which a debt restructuring is mentioned in the Wall Street Journal
during the 1978-1987 period. The authors …nd that Chapter 11 cases take significantly longer time to restructure than successful private restructurings. Speci…cally, …rms that …le for Chapter 11 spend an average of 8.1 months (a median of 3)
attempting to restructure their debt before seeking bankruptcy protection, and an
average of 20.4 (a median of 18) additional months in Chapter 11; whereas …rms that
restructure their debt privately require an average of 15.4 months, and a median of 11
months to complete restructuring. Moreover, restructuring of publicly debt is com-
31
pleted in signi…cantly shorter time (an average of 6.6 months and a median of 2) than
restructuring of non-traded debt (an average of 15.9 months and a median of 10.5).
Franks and Torous (1994) compare time spent in distressed exchanges and Chapter
11 reorganizations for a sample of 45 distressed exchanges and 37 Chapter 11 reorganizations over the 1983-1990 period. They …nd that distressed exchanges require
signi…cantly less time than Chapter 11 reorganizations: a median of 17 months for
workouts, compared with a median of 27 months for Chapter 11 reorganizations.9
Lastly, Khal (2001) investigates the duration of …nancial distress. He shows that the
median time spent in …nancial distress is 35 months. In addition, …rms that avoid
Chapter 11 spend a much shorter time in …nancial distress (a median of 26.5 months)
than …rms that …le for Chapter 11 (a median of 45 months).10
d- Absolute priority rule deviations (APR)
Bebchuk (2002) developed a model to compare the e¢ ciency of corporate investment
decisions when APR is respected versus when there are deviations from the APR.
The model suggests that ex-post deviations from APR have negative e¤ects on exante decisions taken by shareholders. Such deviations aggravate the moral hazard
problem with respect to project choice, increasing the equity holders’ incentive to
favour risky projects as well as with respect to borrowing and dividend decisions.
However, Bebchuk argues that the results are reversed when …rms are already in
…nancial distress. Here, deviations from the APR reduce rather than increase equity’s
bias toward choosing risky investment projects. This is because when the project is
likely to fail and the …rm to …le for bankruptcy, equity’s main return comes from
9 The
period in informal reorganization is measured from the default date to the date
of exchange, and for a formal reorganization it is measured from the default date to the
date of con…rmation by the bankruptcy court.
10 The onset of …nancial distress is de…ned as the …rst time that a …rm defaults or violates
a covenant or avoids this by negotiating to restructure its debt with its creditors or …le for
Chapter 11.
32
the share that it receives of the …rm’s value in bankruptcy–the deviations from the
APR. Given that safe projects have higher downside returns, they generate more for
equity.
In a prior research, Chang (1992) developed a sequential bargaining model of
the Chapter 11 negotiation process and analyzed the e¤ects of the legal rules that
govern this process. The author shows that the outcome of the bargaining process
often diverges from the contractual rights of the classes. Speci…cally, Chapter 11 gives
equity holders the ability to obtain value even if the value of the …rm’s assets is less
than its debt. The amount that equity holders will receive tends to increase with: the
volatility of the value of the company’s assets, the extent to which reorganization
imposes “…nancial distress cost”, the length of the reorganization period, the length
of the period during which the equity holders have the exclusive right to make o¤ers,
the extent to which liquidation imposes a loss in value, and the extent to which the
value of the company’s covers the company’s debts.
Empirical studies of corporate reorganization show that there are deviations
from the absolute priority rule (APR). Particularly, Chapter 11 often enables equity
holders to obtain a share of the value of the reorganized company even when that
value is not su¢ cient to cover debtholders’claims [Franks and Torous (1989), Weiss
(1990), Baird et al. (2007)]. Compared to previous studies, Bris et al. (2006) found
fewer APR violations. Besides, Franks and Torous (1994) found that equity deviations from absolute priority are higher in distressed exchanges than in Chapter 11
reorganizations.
Many of the previous studies investigate the determinants of APR deviations.
Weiss (1990) and Franks and Torous (1994) …nd that deviations are positively related
to the size of the …rm whereas Baird et al. (2007) show that APR violations are more
likely in small cases. Bris et al. (2006) and Baird et al. (2007) …nd that APR tends
33
to be violated more often when there are fewer secured creditors and when there is
more secured debt relative to total debt.
e- Creditors’repayment
Franks and Torous (1994) set out for each class of creditor in both distressed
exchanges and Chapter 11 reorganizations the percentage of total payments received
in the form of particular security, property, or cash. Regardless of the reorganization
form, the majority of payments of senior debt are in the form of cash and new senior
debt, whereas the majority of payments to junior debt are in common stock. The
aggregate cash used in exchanges of securities is higher in Chapter 11 (29%) than in
distressed exchanges (13%). The authors also …nd that …rm recovery rates are significantly smaller in Chapter 11 reorganizations, a median of 50.9%, than in distressed
exchanges, with a median of 80.1%. The investigation of recovery rates determinants
shows that recovery rates are positively related to the general performance of the
economy, but negatively related to the size of assets sales.
Bris et al. (2006) …nd that creditors in Chapter 11 reorganizations fare signi…cantly better (mean 69%, median 79%) than creditors in Chapter 7 liquidations.11
The results also indicate that creditors in Chapter 11 and in …rms with relatively
more secured debt recover more, whereas creditors in …rms that are more underwater,
…rms that have fewer secured creditors, and …rms that are forced to bankruptcy by
creditors recover less.
Baird et al. (2007) conducted an empirical study on the dynamics of large and
small Chapter 11 cases using a sample of 139 Chapter 11 bankruptcies between 1995
and 2001. In small bankruptcy cases that make up the majority of the sample, there
is little to be distributed among non-priority unsecured creditors. The empirical
11 For
Chapter 7 liquidations, the mean is 27% and the median is 6% in the optimistic
scenario and this drops to 5.4% and 0%, respectively, in the pessimistic scenario.
34
evidence suggests that the protection of such small creditors may not be important,
at least not under existing Chapter 11. In counterpart, when the assets of the business
are greater than $5 million, unsecured creditors will collect on average (median) 60
cents on the dollar (67 cents on the dollar) despite the fact that the absolute priority
rule is respected and senior creditors are paid in full (as they are in about 80% of
the cases).
Davydenko and Franks (2008) compare bank recovery rates of bank credit in
the UK, France, and Germany. The authors …nd that median recovery rates are
lowest in France (56%) and highest in the U.K. (92%), with Germany in between
(67%). In addition, the study shows that recovery rates are lower for formal bankruptcies and for piecemeal liquidations, compared with workouts and going-concern
reorganizations.
2.2.4
The alternative mechanisms to bankruptcy law
A) Market-based approach
The structural problems of the prevailing bargaining-based approach have led to
much research work on alternative arrangements. One approach that has been natural for researchers to explore is to rely on the market to address the bankruptcy
problem. The …rst market-based approach was proposed by Roe (1983) who suggests
selling a sample of 10% of the company’s stock on the market from which …rm value
is extrapolated and then to distribute the remainder of the equity on the basis of
this estimate and according to the absolute priority rule. Roe (1983) suggests adding
the proposed method as one of the possible means of valuation and restructuring if
the bargain fails to produce a result after a speci…ed period of time. Baird (1986),
however, did not see a reason to stop at 10% rather than sell the full 100% of the
company’s stock and developed the auction approach.
35
a- Auction approach
The auction approach originated with Baird (1986). He argues that reorganization procedure should be abolished and replaced by a mandatory sale procedure
based on a competitive auction. The proceeds of the sale would be paid according
to the absolute priority rule. The new owners of the …rm would choose whether
to shut it down or continue its operations and would also decide whether to keep
the old managers on or replace them. White (1994) suggests that a way to reform
Chapter 11 without abolishing it would be to sell all …rms as going concerns if a
reorganization plan could not be adopted.
The argument for the auction approach is that there is no haggling among the
claimants about who should get what. The …rm is transformed into cash, which is
distributed according to absolute priority rule. This procedure has also the advantage
of being quicker and cheaper than bargaining based approach. Another advantage
advanced by Baird (1986) and Easterbrook (1990) is that a real sale (auction) would
provide more accurate valuation of the …rm than hypothetical prices (in Court).
Bidders risking their money have every reason to spend the optimal amount to
value the assets and make e¢ cient decisions concerning whether to save or liquidate
the …rm. In addition, Baird and Morrison (2001) show that a regime of mandatory
auctions is strongly information forcing. It gives managers an incentive to make
information available and veri…able to potential buyers to preserve the …rm as a
going concern.
Although the auction approach seems to be a good alternative to bargaining
approach, critics expressed doubts as to whether an auction will move assets to their
highest-value use and whether it will always work well. Shleifer and Vishny (1992)
investigate the …rst question. They argue that when …rms have trouble meeting debt
payments and sell assets, other …rms in the industry which are the highest valuation
36
potential buyers of these assets are likely to have liquidity problems as long as the
shock that causes the seller distress is industry or economic wide. This general equilibrium aspect of asset sales implies that auctions can have signi…cant costs to the
extent that the assets do not end up owned by the highest value user. Aghion et al.
(1992) investigate the second question and a¢ rm that auctions work well if raising
cash for bids is easy and there is plenty of competition among several well-informed
bidders. However, in most economies, these conditions will often not be met. First,
it may be very di¢ cult, risky and costly for a bidder to raise funds in a short time.
Second, the cost of preparing a bid is considerable, particularly if the incumbent
management is reluctant to provide information about the …rm’s operations. Thus,
only one bidder will recoup its bidding costs and the rest will make losses. This
fact limits the number of bidders and accentuates the competition problem of auctions. Finally, it is important to stress that another potentially important barrier to
auctions is regulation. For example, antitrust regulation is an important factor that
often prevents industry buyers from buying industry assets (Shleifer and Vishny,
1992).
b- Options approach
Another alternative to the existing bargaining process is the options approach.
This approach was put forward by Bebchuk (1988, 1998) as the basis for reform
of reorganization law and is also advocated by Aghion et al. (1992). Like the auction approach, the options approach seeks to eliminate the costs and deviation from
priority rule that accompany bargaining process. Indeed, Bebchuk (1988, 2000) proposes an ingenious scheme based on options to divide the value of the reorganized
…rm among the participants in corporate reorganization. Under this method, the
participants are grouped into di¤erent classes according to the relative priority of
their claims. Then, instead of receiving equity interests in the reorganizing …rm, the
37
participants of each class receive option rights according to the absolute priority
rule. The options would be designed so that, whatever the reorganization value, no
participants would ever be able to complain that they would end up with less than
the value to which they are entitled. Finally, the …rm uses the receipts from the
options exercised to make redemptions starting with the most senior claimants and
to determine how the units of the reorganized company will be distributed among the
holders of rights. Thus, unlike the auctions method, the e¤ectiveness of the options
method does not depend on whether outside buyers acting in the market will value
correctly the …rm. Another advantage of the options procedure is that it improves
both ex-post and ex-ante e¢ ciency. In fact, Bebchuk (1988) argues that the options
procedure would improve ex-post e¢ ciency by eliminating costly and lengthy bargaining between various creditor group and the large legal fees and by getting the
company into e¢ cient decision-making. This procedure would also improve ex-ante
e¢ ciency by implementing the contractually prescribed de…nition.
In a subsequent study, Aghion et al. (1992) propose a scheme similar to Bebchuk’s
with two main contributions. First, both cash and non-cash bids for the new allequity …rm are solicited in the …rst stage of the procedure and at the same time
rights to the shares are allocated in the new …rm. Second, once all the reorganized
company’s tickets are divided using the options scheme described by Bebchuk (1988),
the “new” shareholders vote on whether to select one of the cash bids or to maintain the company as a going concern.12 The main advantage of Aghion et al. (1992)
proposal is that, by permitting non-cash bids, it reduces the …nancing problem and
indirectly it increases the number of eventual bidders, and therefore the competitiveness of the auction and the value of the winning bid to claimants.
12 In
this stage Aghion et al. (1992) suggest hiring an agent like an investment bank to
value the various proposals because shareholders may have di¢ culty to vote for the best
o¤er.
38
B) Debt restructurings and private workouts
Another alternative to bankruptcy lies in out-of-court reorganization mechanisms. In
fact, many …rms …rst attempt to resolve …nancial di¢ culties via private restructurings because they are expected to involve lower transaction costs and less disruption
to the …rm’s operations than formal bankruptcy proceedings, so resources are saved.
Measuring the direct costs of out-of-court restructurings is di¢ cult because these
costs are not reported separately from other expenses of the distressed …rm. The costs
can be observed, however, for the restructuring of public debt via a formal exchange
o¤er (Hotchkiss et al., 2008). An early empirical work conducted by Gilson et al.
(1990) documents an average (median) cost for 18 exchange o¤ers of 0.6% (0.32%)
of the book value of assets. The study also shows that stock returns are signi…cantly
higher when debt is restructured privately, suggesting that the costs are lower for
workouts.13 In addition, many studies report that out-of-court restructurings take
signi…cantly less time than formal proceedings, suggesting that various indirect costs
may be lower.14
A number of studies have documented the determinants of …rms’choice between
formal bankruptcy and out-of-court proceedings. Based on a sample of 169 exchangelisted companies that were in severe …nancial distress during 1978-1987, Gilson et al.
(1990) …nd that …rms having more intangible assets, a higher bank debt ratio and
fewer lenders are more likely to restructure their debt privately. The authors argue
that …rms with higher proportions of intangible assets choose informal workouts in
order to preserve assets value that might be lost if the …rm reorganize formally under
Chapter 11. Debt is more likely to be restructured outside Chapter 11 when relatively more of the debt is privately held by banks and insurance companies because
13 Stockholders
of …rms that successfully restructured realized average abnormal returns
of 41.4% over the restructuring interval, whereas stockholders of ultimately bankrupt …rms
realized abnormal returns of –39.1%.
14 See Section 2.1.3-c
39
bank debt reduces the amount of information asymmetry between stockholders and
creditors. Moreover, fewer claimants facilitate informal restructurings by reducing
the potential problems created by asymmetric information and con‡icts of interest.
Franks and Torous (1994) investigate the characteristics of the …nancial recontracting for …rms completing public debt exchange o¤ers and …rms entering Chapter
11. The comparison between the two samples indicates that …rms that successfully
complete exchange o¤ers are signi…cantly more solvent and more liquid than …rms
entering Chapter 11.15 Unlike Gilson et al. (1990), …rms that successfully complete
exchange o¤ers do not owe more of their long-term debt to banks. According to
Franks and Torous (1994), this could be explained by the sampling procedure which
excludes …rms without publicly traded debt and therefore the sample …rms may rely
less heavily on bank debt.
Chatterjee et al. (1996) examine a sample comprised of 70 Chapter 11 …lings, 21
prepackaged bankruptcies, 65 private workouts, and 45 public workouts including
publicly traded …rms during the period 1989-1992.16 The authors provide evidence
that the restructuring decision depends on the degree of the …rm’s leverage, the
severity of its liquidity crisis, the extent of the creditor’s coordination problem,
and the magnitude of the …rm’s economic distress. Particularly, …rms that choose
prepackaged bankruptcies or workouts have greater bank debt and trade credit and
they are economically more distressed than Chapter 11.
Khal (2001) examines a sample of 95 …rms that entered …nancial distress between
1979 and 1983 including …rms that never enter Chapter 11 as well as …rms that enter
Chapter 11 at some point during the process. Consistent with Gilson et al. (1990),
15 Firm’s
solvency is measured by the market leverage ratio (book value of debt divided
by the sum of the book value of debt plus the market value of equity). Firm’s liquidity is
measured by the current ratio (current assets divided by current liabilities).
16 A prepackaged bankruptcy is a reorganization of …rm’s debt contracts that has been
negotiated or accepted by creditors prior to the beginning of a bankruptcy proceeding.
40
the results show that …rms with a higher proportion of private debt are less likely
to …le for Chapter 11. Moreover, a …rm is less likely to …le for Chapter 11 if the
stock returns in the two years before the onset of …nancial distress are higher. This
is consistent with the …ndings in Franks and Torous (1994).
2.2.5
Empirical evidence in the French context
In what follows an overview of some studies conducted on bankruptcy in France.
The studies are arranged in the chronological order of their publication.
Kaiser (1996) investigates European bankruptcy laws including French law. The
study reports that the reorganization procedure results in liquidation in over 94%
of cases on average in France over the period 1987-1993. The author argues that
the French law, by trying too hard to maintain …rms as going concern in order to
preserve employment, is failing to achieve any of its objectives of continuation of the
…rm or preservation of the employment.
Blazy and Combier (1997) provide the …rst detailed empirical analysis on bankruptcy in France based on a sample composed of 245 reorganization cases and 517
liquidation cases …led in the commercial Court of Paris in 1991. The authors investigate the causes for …ling and use Dice’s index to classify the most similar causes
into groups according to the procedure’s outcome. They acknowledge that …nancial
di¢ culties are not su¢ cient to comprehend the mechanisms leading to bankruptcy.
Blazy and Combier (1997) also study the characteristics of the …rms at the opening
of the bankruptcy proceedings and the measures undertaken by the Court during the
observation period. Moreover, the study shows that continuation cases have higher
recovery rates than liquidations or sales.
Davydenko and Franks (2008) investigate whether di¤erences in creditor’s rights
across countries (France, Germany, and the U.K.) lead banks to adjust their lending
41
and reorganization practices to mitigate the expected creditor-unfriendly aspects of
the bankruptcy law. Particularly, the authors …nd that, in response to the French
bankruptcy code which limits creditors rights, banks in France require more collateral
and rely on account receivable and personal guarantees that avoid the dilution of
claims. Despite these endogenous adjustments to the bankruptcy law, Davydenko
and Franks (2008) show that recovery rates for banks in France remain signi…cantly
below those in the U.K. and in Germany.
In a recent study, Blazy and Chopard (2010) use a database of 273 French corporate bankruptcy …lings on the period 1995-2005 to study the relationship between
the …rm’s capital structure and the likelihood of reorganization in a court-supervised
reorganization process. The results show that the measure of how well-secured creditors are and the fraction of secured debt are not signi…cant determinants of the
Court’s choice between reorganization and liquidation whereas the number of secured
claimants and the fraction of claims with a “super-privilege” signi…cantly decrease
the likelihood of reorganization.17 Blazy and Chopard (2010) also …nd that the probability of reorganization depends mainly on i) the amounts of various assets, ii) the
age, and iii) the causes of default.
In another recent study, Blazy et al. (2011) use a sample of 942 French corporate
bankruptcy …lings over the period 1989-2005 to address the dilemma associated
with the social and …nancial objectives of the French bankruptcy law. The authors
investigate the determinants of the probability of reorganization as the same entity
and of sale, relative to the probability of liquidation. They …nd that commercial
Courts actively work to facilitate reorganization against liquidation. Blazy et al.
(2011) also modeled the determinants of the global recovery rate for each outcome.
17 Blazy
and Chopard (2010) consider that secured creditors have strong incentives to
liquidation if the expected liquidation value of assets minus the super-privileged claims is
higher than the secured claims.
42
The results show that creditors’repayment mainly depends on the situation of the
debtor at triggering, while the way the procedure is managed by the Court has little
impact. In the …nal part of their analysis, the authors compare rival o¤ers in case of
sales as a going concern to investigate whether the Court favours social over …nancial
e¢ ciency. The choice between rival o¤ers con…rms that social considerations prevail
in the arbitration.
2.3
2.3.1
Overview of the French bankruptcy law
The historical evolution of the French bankruptcy law
French bankruptcy law can be traced back to the creation of the French Republic at
the end of the 18th century and the emergence of the modern French legal systems.
Its evolution is characterized by a progressive loss of its adversarial character and
an increasing importance to economic scope. It can be divided into four periods:
1st period:
The Commercial Code of 1807 contained the …rst codi…cation of legal provisions
regarding merchants who were not capable of paying their debt. The focus of these
provisions was clearly the repayment of the creditors and the punishment of bankrupt
debtors including the sealing and con…scation of the debtor’s assets, incarceration in
some cases, and other civil and professional sanctions. In practice, this system was
rarely applied given its extreme severity and the problems of default were resolved
out of the court via a friendly liquidation when it is feasible. Then, the Bankruptcy
Act of May 28, 1838 marked slight softening of the bankruptcy provisions. In fact,
this Act reduced the sanctions incurred by the debtor and accelerated the procedure by authorizing the closing of a case for insu¢ ciency of assets. However, this
43
reform still expresses the traditional bankruptcy view which punishes the debtor by
declaring it bankrupt and by selling its goods. The distinction between dishonest
merchants and those who take wrong decisions, but in good faith and the taking of
economic situation into consideration became imperative. Thus, the Law of Mars 4,
1889 introduced a new procedure that is not repressive and that is intended to merchants in good faith: liquidation procedure (liquidation judiciaire). This procedure
aimed to conclude an agreement (concordat) between the debtor and its creditors;
otherwise, traditional bankruptcy is applied.
2nd period:
A major shift in philosophy was introduced with the law of July 13, 1967 which
sought to separate the …rm from its managers. In fact, only debtors who were guilty
of negligent conduct were subject to civil and/or criminal sanctions. Another innovation of the reform of 1967 is the introduction of a temporary stay on the creditors’
proceedings to facilitate the reorganization of the company. This procedure, by its
preventive character, gave birth to a new concept in the French bankruptcy law: business in di¢ culty (entreprise en di¢ cultés). However, it is a special procedure that
could be applied only if three conditions are simultaneously met: the company must,
…rst of all, experience …nancial di¢ culties, but that are not irremediably compromising. Second, it is necessary that it has fast and good prospects for reorganization.
Third, this procedure is applicable only to companies whose liquidation would be
likely to cause a serious trouble to the national or regional economy. In addition to
this procedure, the reform of 1967 instituted two bankruptcy proceedings (procédures collectives) available to any …rm that is in default of payment (cessation de
paiement): judicial settlement (règlement judiciaire) and liquidation of goods (liquidation des biens). The opening of a procedure depends on the Court’s appreciation
of the reorganization’s potential of the …rm. If the …rm is viable, the Court would
44
order the judicial settlement, the debtor works out a payment proposal that is subject to creditor’s vote and then to the Court’s approval. Thus, the creditor’s played
an important role in this procedure. If the …rm is not viable, the Court would order
the liquidation of goods, the debtor loses the control of the …rm, and a trustee is
appointed to carry out the liquidation operations.
3rd period:
Although the law of 1967 has marked the emergence of the concept “business in
di¢ culty”, it was subject to many criticisms and French Bankruptcy Law underwent
a dramatic overhaul reforms in the mid 1980s. Particularly, the prior adversarial
character of the law was removed and replaced by an economic rather than legal
paradigm. The tendency has been reversed and the bankruptcy procedures have
been designed so as to protect debtors from their creditors. The purpose of the
legislation is to facilitate and to encourage e¤ective reorganization of …nancially
distressed businesses. The reform was based on two aspects: the prevention from
business failures through the law of March 1, 1984 and the treatment of …rms’
di¢ culties through the law of January 25, 1985.
On the one hand, the law of 1984 was designed to prevent business failure and
therefore avoid bankruptcy procedure and had two primary objectives. First, it
sought to detect early warning signs of problems through the use of information
and alert procedures. Second, it sought to facilitate the contacts between the debtor
and its creditors through "legal workout" (règlement amiable). On the other hand,
the law of 1985 designed a single uni…ed bankruptcy procedure: reorganization proceedings (redressement judiciaire). The primary objective of this procedure is to save
the company, followed by job protection and the reimbursement of the company’s
debts.
45
In practice, the law of 1984 regarding the prevention was ine¤ective for two
reasons. First, only large companies were concerned by the law, small and medium
companies were left out of the procedure. Second, the prevention intervened too late.
To remedy this problem, the government enacted the law of June 10, 1994 regarding
the prevention and the treatment of company di¢ culties. The main objectives of this
law were the reinforcement of the proceedings designed to prevent business failure
and the simpli…cation and the acceleration of bankruptcy proceedings.
4th period:
The French bankruptcy system was substantially reformed by the law of July 26, 2005
regarding the …rms’ safeguard. Most of the new reform provisions came into force
on January 1st , 2006. The reform of bankruptcy system had been under discussion
for several years prior to its promulgation. The goal of the new bankruptcy law is to
improve the procedures to prevent companies’default at an early stage and avoid
that their …nancial di¢ culties lead to bankruptcy proceedings.
2.3.2
French bankruptcy system prior to the reform of 2005
This section provides a detailed description of the functioning of the French bankruptcy system for the period covered by the study; that is 1995-2004. Over this
period, the French Bankruptcy system was governed by the bankruptcy law reforms
of March 1, 1984, January 25, 1985, and June 10, 1994. The bankruptcy system is
characterized by three main phases: prevention, non-judicial measures, and collective
bankruptcy proceedings.
46
A) Prevention of businesses’di¢ culties
The goal of this phase is to detect any problems within the company as soon as possible in order to adopt measures to improve the situation of the company. Prevention
can be achieved through the use of information and alert procedures.
a- Prevention through the use of information
First, all persons and legal entities quali…ed as merchants have an obligation to
maintain regular accounts and, at the end of the …nancial year, establish annual
accounts. Second, limited companies, limited liabilities companies and partnerships
must …le annual accounts and an annual report with the clerk of the commercial
Court and are subject to criminal penalties in case of violation. Third, the law of
1984 forces companies having at least 300 employees or annual revenues of at least
18.3 million euros to draw up four forward looking management reports: (i) a statement of the quick assets, excluding inventories, and a statement of current liabilities
(situation de l’actif réalisable et disponible et du passif exigible), (ii) a …nancial breakdown (tableau de …nancement), (iii) a provisional pro…t and loss statement (compte
de résultat prévisionnel), and (iv) a …nancial plan (plan de …nancement).
b- Prevention through the use of alert procedures
Alert procedures were introduced by the law of 1984. These procedures can be
mandatory or optional depending on the situation of the debtor and can be initiated
by the statutory auditors (commissaires aux comptes), the company’s work council
(comité d’entreprise), the commercial Court or the prevention group.
The law of 1984 gives a detailed description of the alert procedure when it is
initiated by the statutory auditor. This latter must inform managers in case of
knowledge of any fact which could compromise the ongoing status of the company.
In the absence of a response within 15 days of the request, or if the response does
47
not guarantee the continuation of the activity, the statutory auditor will direct the
managers to request the collegiate board to deliberate upon these facts. If these
provisions are not complied with or if the statutory auditor considers that the continuity of the business is still in danger, he is required to draft a special report to be
presented to the work council and to a member’s general meeting. If, at the end of
this meeting, the statutory auditor is still not satis…ed with the decisions, he noti…es
the commercial Court.
B) Extra-judicial reorganization measures
These measures are contractual as well as judicial in nature because their goal is to
establish an arrangement under the auspices of a conciliator and under the authority
of the Court. It allows companies that are in di¢ culty but not yet in default to …nd
an agreement with their creditors and avoid the opening of a bankruptcy proceeding.
There are two extra-judicial reorganization measures provided by the law of 1984: the
special commission (mandat ad hoc) and the "legal workout" (règlement amiable).
a- The special commission (mandat ad hoc)
This procedure has its origin in the law of 1984 and involves the appointment of
a special commissioner to deal with the di¢ culties that the company is facing. The
special commissioner may not participate in the management of the company; his
role is limited to assist the interested parties in reaching a common agreement. The
main advantage of the special commission is its ‡exibility with regard to procedure
and duration. There is no limit provided for the time period for the procedure and
the scope of the mission is freely set by the commercial Court based on the parties’request. Another advantage of this procedure is its con…dentiality because only
creditors who agree to participate in the proceedings are kept informed. However,
48
an eventual agreement does not provide any particular legal protection to any of the
parties involved which can lead to its failure.
b- The "legal workout" (règlement amiable)
This procedure has also its origin in the law of 1984, but it has more legal
description than the special commission. The "legal workout" is open to all companies which, without being in default of payment are experiencing legal, economic
or …nancial di¢ culties or have needs which cannot be met by a …nancing scheme
adapted to the enterprise’s possibilities. The debtor should …le a request stating its
economic, employment and …nancial situation, …nancing needs and, if necessary, the
means to tackle them. Once the procedure is opened, the Court appoints a conciliator
without a¤ecting the management’s powers and sets his exact mission based on the
request made by the parties. The conciliator duty is to emphasize the restructuring
of the company through the agreement with the principal creditors which is intended
to put an end to the business’di¢ culties. Its mission lasts three months and could
be extended one month following the conciliator’s request. The Court may suspend
for the duration of the procedure any creditors’proceedings seeking the payment of
their debts if the conciliator considers that this measure will facilitate the conclusion
of an agreement. The Court should also approve an agreement that is reached with
all creditors. If some creditors do not take part in the agreement, the Court has
the option of approving it and can grant additional time for the payment of debts
owed to creditors who did not participate in the proceedings. Besides, the agreement suspends for the duration of its implementation the proceedings of creditors
who took part in the agreement. These measures emphasize the judicial nature of
the procedure.
In general, because of the relatively short period allowed for the conciliator’s
mission, debtors prefer …rst …ling for a special commission in order to have time
49
to reach an agreement. Then, the special commission will be replaced by the "legal
workout" so that the Court approves the agreement.
C) Collective bankruptcy proceedings
At the time of the study (1995-2004), there exist two bankruptcy proceedings: the
reorganization procedure (redressement judiciaire) and the liquidation procedure
(liquidation judiciaire).
Prior to the reform of 2005, the default of payment (cessation de paiements)
was a key criterion that triggers bankruptcy proceedings.18 Thus, the conditions for
the opening of bankruptcy proceedings state that the procedure is available to any
debtor who falls within the scope of the law and who is in default of payment.19 The
debtor must apply for the opening of a bankruptcy procedure within the 15 days
following the default of payment by submitting a declaration of default (déclaration de cessation de paiements) in the Court. The violation of this obligation could
expose the manager to civil penalties including the possibility of personal bankruptcy proceedings and management prohibition. The bankruptcy procedure can
also be initiated by any creditor. In general, such requests originate with banks and
social security authorities. The Court has also the possibility to initiate the bankruptcy procedure; this possibility is designed to avoid the continuation of a business
in default when the debtor and the creditors omit to initiate the procedure. Finally,
the public prosecutor can initiate the procedure. Though this is possible, it rarely
occurs in practice. In the light of the elements regarding the situation of the debtor,
18 Article
3 of the law of 1985 states that there exists a default of payment when the
debtor can no longer meet its due liabilities with its available assets.
19 The Commercial Code states cases other than the default of payment for the opening
of the bankruptcy procedure. First, the Court may commence bankruptcy proceedings in
case of breach of a …nancial obligation under the composition procedure. Second, in the
case of breach of the terms of the continuation plan, the Court orders the cancellation of
the plan and the commencement of a liquidation procedure against the debtor.
50
the Court will order either the reorganization procedure which allows the company
to continue its activities or the liquidation procedure if the debtor has ceased all
activity or when the restructuring is clearly impossible.20
The opening of proceedings shall automatically prohibit payment of claims arising
prior to the bankruptcy proceedings and stay interests on prior debts (L621.24 and
L621.48). In addition, it suspends legal actions of creditors seeking either an order
against the debtor for the payment of any debt or the resolution of a contract for
default of payment. It shall stay or prohibit all proceedings for enforcement …led by
the creditors in respect of movable and immovable proprieties (L621.40). However,
goods held by the debtor on consignment or for sale on behalf of the owner as well
as assets sold with retention clause may be claimed if they still exist in kind at the
time of the issuance of the opening order (L621.122). Any pending proceeding shall
be suspended until the creditor who initiated it has …led its submission of claim
(L621.41). The next section provides a description of the reorganization and the
liquidation proceedings.
a- Reorganization procedure
The objectives of the reorganization procedure are in order: 1) saving the company, followed by 2) protecting jobs, and …nally, 3) reimbursing the …rm’s debts
(L620.1).
The law of 1985 introduced a simpli…ed reorganization procedure (régime simpli…é) available to debtors employing less than 50 persons or having an annual
turnover below 3,100,000 euros. The di¤erence between the general and the simpli…ed
procedure relates essentially to the duration of the observation period and the administrator’s appointment which is mandatory in the general procedure. The opening
20 Prior
to the law of 1994, the Court had not the possibility to order immediately
the opening of a liquidation procedure. It had to order the opening of a reorganization
procedure and it is only at the end of the observation period that it can decide to liquidate
the company.
51
order sets the date for the default of payment, the scheme applied, the duration of
the observation period, and appoints the supervisory judge (juge-commissaire) and
the creditor’s representative. In some cases, the Court appoints an administrator and
de…nes his mission, which may be to (i) supervise the debtor, (ii) assist the debtor,
or (iii) manage the company alone.
The observation period
The commencement of a reorganization procedure triggers an observation period
at the end of which the Court decides on the fate of the debtor: either the reorganization or the liquidation of the company. Its duration depends on the scheme
applied and can vary from 4 to 20 months.21 During this period, the administrator,
in cooperation with the debtor and possibly assisted by experts is required to draw
up a report on the business’s economic and employment situation (bilan économique
et social). This report should state the origin, the extent, and the nature of the
business’s di¢ culties. The report must also contain the administrator’s analysis of
whether rehabilitation is possible. If so, the administrator’s report will include a
reorganization draft plan. The draft plan can take the form of a continuation plan
or/and a sales plan. It de…nes the terms and conditions for creditors’repayment and
explains the level and the prospects for employment.
At the end of the observation period and based on the administrator’s report, the
Court decides on the fate of the debtor. If rehabilitation is possible, the Court orders
the reorganization of the …rm and therefore con…rms a reorganization plan. If the
Court and the administrator determine that rehabilitation is impossible, then the
Court orders the commencement of a liquidation procedure. An important feature
of the French bankruptcy law is that creditors are not actively associated to the
21 In
the general procedure, the observation period lasts six months and can be extended,
a …rst time, for the same period and, a second time, for eight months, whereas, it lasts
four months and it can be extended for the same period in the simpli…ed procedure.
52
reorganization process; they do not vote on the reorganization plan and cannot veto
it. They have only a consultative role.
The reorganization plan
The order con…rming the plan should state the persons bound to implement the
plan and the requirements related to the future of the business’s activity, the terms
and conditions for maintaining and …nancing the business, the settlement of liabilities
as well as any guarantees given to ensure the implementation of the plan. The plan
should also state and explain the level and prospects for employment (L621.63). The
duration of the plan is …xed by the Court. It may not exceed ten years and if the
debtor is a farmer, this period may not exceed …fteen years (L621.66).
The restructuring of the company may take the form of continuation as the same
entity or sale to another entity (See Figure 2.1).22
Continuation
The judge opts for a continuation only if he assesses that the …rm can keep
operating and the claims can be reimbursed (L621.70). In this case, the …rm is kept
as a legal entity, and a plan of debt repayment based on a reasonable …nancial
forecast should be proposed. Creditors can agree to write down a fraction of their
loan or receive a fraction of the equity of the …rm, in exchange for these writeo¤s. They can also agree to reschedule their payments.23 The Court cannot force
the creditors to write down their claims but it can rede…ne the terms of the debt
22 In
Blazy et al. (2011) paper and in Figure 2.1, the term “continuation” designates
the restructuring of the …rm as the same entity or the sale of the …rm as a going-concern
which corresponds to the term “reorganization”in our study and the term “reorganization”
designates the restructuring of the bankrupt …rm by keeping operations in the same entity
which corresponds to the term “continuation” in our study.
23 Debt cancellations and moratoriums shall not apply to some claims mentioned in the
labour Code. In addition, within a limit of 5% of the estimated liabilities, claims that do
not exceed 152e, should be reimbursed without any cancellation or moratorium (L621.78).
53
contract, including the maturity. In practice, creditors may either accept write-downs
with a quick repayment, or opt for a long-delayed repayment in full. If the debtor
fails to implement the plan within the period …xed by the Court, the latter may
order the cancellation of the plan and the commencement of a liquidation procedure
(L621.80).
Sale
The judge opts for the sale of the …rm if he believes that the capacity of the …rm
to serve any signi…cant debt in the future is very limited. In this case, the …rm as such
disappears and it is taken over by a new entity. If there are many o¤ers, the Court
must select the o¤er that ensures the best prospects for preserving employment and
reimbursing debts (L621.87). All the assets of the …rm are transferred to the new
owner (le repreneur) and creditors are reimbursed from the proceeds of the sale
according to their rank and priority.
b- Liquidation procedure
The order commencing or pronouncing the liquidation proceedings triggers the
acceleration of the repayment of all outstanding debts (L622.22). The Court should
nominate a supervisory judge and a liquidator (liquidateur) whose mission is to carry
out the liquidation of the …rm and the veri…cation of the claims.24 The manager is
removed and all rights and actions over the estate are exercised by the liquidator.
The liquidator determines the priority order of the creditors and distributes the
proceeds of the sale among them.
24 The
veri…cation of unsecured claims need not be made if it appears that the proceeds
of the assets sales will be totally absorbed by legal fees and secured claims.
54
Figure 2.1: The French bankruptcy code before 2005 reform (Blazy et al., 2011)
55
2.3.3
The main features of the law of July 26, 2005
A) The institution of a new procedure: the safeguard procedure
The safeguard procedure (procédure de sauvegarde) represents the most signi…cant
innovation of the law of July 26, 2005. The purpose of this new procedure is to
facilitate the reorganization of the business in order to allow the continuation of
the economic activity, the preservation of the employment and the settlement of the
liabilities (Art. 12).
The safeguard procedure shows some similarities with American bankruptcy code
provisions. Particularly, three characteristics of the new bankruptcy law are directly
inspired by the American law.
i) A voluntary and preventive bankruptcy proceeding
Similarly to Chapter 11, the safeguard procedure allows a debtor to initiate a
reorganization procedure prior to the default of payment which was not possible
in previous French bankruptcy proceedings. Precisely, the commencement of a safeguard procedure is available to any debtor showing di¢ culties that it is unable to
overcome on its own and that would lead to a default of payment (Art. 12). This
condition is similar to the one in the American Chapter 11 which requires “severe
…nancial di¢ culties” to initiate bankruptcy. However, contrary to Chapter 11, the
safeguard procedure is triggered only at the debtor own initiative and it cannot be
initiated if the debtor had already ceased its payments upon the commencement of
the procedure.
ii) A procedure more favourable to debtors
Like American debtors, French debtors could seek the protection of the law upon
the identi…cation of the …rst di¢ culties. Typically, the commencement of a safeguard
56
procedure prevents debtors from paying claims arising prior to the opening of the
safeguard procedure and it entails a stay on the creditors’action against the debtor
(Art. 25).
Another measure inspired by Chapter 11 is the concept of "debtor in possession". The new procedure encourages debtors to request the opening of a safeguard
procedure at an early stage by putting them in the core of the procedure. Thus, the
management of the business shall be carried out by its manager during the safeguard procedure. The administrator may only supervise the debtor’s management
operations or assist the debtor in all or some of the management, but not represent
it (Art. 23).
iii) The creditors’committees
As in Chapter 11, the new safeguard procedure provides for the creation of two
creditors’committees allowing a more contractual method, but only for large debtors
(Art. 83).25 Unlike Chapter 11 where committees are created according to the claims’
nature, secured or unsecured, the committees are created according to the creditor’s
nature. In sum, two committees are established. The …rst committee consists of the
credit institutions and the second consist of the main suppliers of goods and services
(Art. 83).26 Another di¤erence with the Chapter 11 is the setting of time limits to
avoid the slowness of a strongly contractual procedure. Indeed, the two creditors’
committees shall be created by the administrator within thirty days from the opening
of the safeguard procedure. Then, the debtor shall present its proposals for the
drawing-up of the plan within two months from the date on which the committees
25 The
creation of creditor’s committees is mandatory only for debtors whose accounts
are certi…ed by a statutory auditor or prepared by a public accountant and whose number
of employees is at least 150 or sales turnover is over 20 million euros.
26 Each supplier of goods or services shall be a member of the committee of the main
suppliers when its claims account for more than 5% of the total claims of suppliers. The
other suppliers may be members of this committee on invitation by the administrator.
57
were set, which may be extended once for two more months. The committees must
announce whether they have decided to approve the draft plan within thirty days
after the proposals have been sent by the debtor. Similar to Chapter 11, the decision
shall be made by a majority vote of each committee’s members, representing at least
two-thirds of the total amount of claims in the committee (Art. 83).
The safeguard procedure is also widely inspired by the reorganization procedure
with regards to the entities involved in the procedure and its di¤erent stages. Each
of the two procedures starts with an observation period during which the payment of
the claims prior to the commencement order is prohibited and the creditor’s actions
against the debtor are stayed. During the observation period, the administrator in
cooperation with the debtor should draw up a report on the business’s economic and
employment situation and eventually a draft plan to be con…rmed by the Court.
However, contrary to the reorganization procedure, only the debtor can initiate
a safeguard procedure and he must not be in a situation of default of payments. In
addition, the safeguard plan cannot order the sale or the liquidation of the business
which is possible in the case of a reorganization procedure.
B) The substitution of the "legal workout" by the composition procedure
The composition procedure (procédure de conciliation) replaces the "legal workout".
It is instituted for debtors who encounter a real or a foreseeable legal, economic or
…nancial di¢ culty, and who have not ceased their payments for more than forty-…ve
days (Art. 5). This represents a signi…cant innovation of the law of July 26, 2005 in
the sense that the former "legal workout" was not designed for debtors who have
already ceased their payments. The goal of this new de…nition is to avoid the automatic interruption of the proceedings and the opening of a bankruptcy procedure
upon noticing the default of payments, which would improve the e¢ ciency of the
58
"legal workout". The composition procedure is a four-month voluntary procedure
renewable for one month and has the same objective as the former "legal workout".
It includes the appointment of a conciliator whose mission is to promote the conclusion of an agreement between the debtor and its main creditors to resolve the
debtor’s …nancial di¢ culties (Art. 6). If an agreement is reached, the Court may
either record it or, at the debtor’s request and under some conditions, homologate
it. In this case, the approval decision is subject to publication formalities (Art. 7).27
The approval of an agreement has two main advantages. First, with regard to the
debtor, the approved agreement stays, during its period, all creditors’actions against
the debtor and suspends the time limits within which creditors covered by to the
agreement can enforce their claims (Art. 7). Second, with regards to creditors, the
persons who, under the approved agreement, have made a contribution of new funds
or have supplied new assets or services in order to ensure the continuation of the
business’s activity are privileged. Their new claims will be paid before all other
claims prior to the commencement of a composition procedure if this latter fails and
safeguard, reorganization or liquidation proceedings are subsequently triggered (Art.
8). However, from the point of view of some debtors, the publication of the approval
can alter their relations with suppliers, clients, and competitors since it reveals the
encountered di¢ culties. Therefore, these debtors may prefer to have the agreement
only acknowledged in order to maintain con…dentiality.
27 The
Court shall approve the agreement obtained if the following conditions are met:
(i) the debtor is not in default of payments or the agreement puts an end to it; (ii) the
terms of the agreement should ensure the continuity of the business’s activity; (iii) the
agreement does not hurt the interests of non-signatory creditors.
59
C) The renovation of the reorganization procedure
The new bankruptcy law has maintained the reorganization procedure and is strongly
inspired by the former provisions as to the commencement of an observation period
in order to assess the economic and employment situation and to draw-up reorganization proposals. In addition, the main speci…city of the former bankruptcy proceedings
is maintained i.e. this procedure is available only to debtors who have ceased their
payments. However, in comparison with the former provisions, the new bankruptcy
law gives the debtors more time to …le for the bankruptcy procedure. Clearly, the
debtor must request the commencement of the bankruptcy proceedings within the
forty-…ve days following the default of payments if it has not, within this time limit,
requested the commencement of a composition procedure (Art. 89).28 In addition,
the new bankruptcy law renovates the reorganization procedure by removing the
original distinction between general and simpli…ed reorganization procedures and by
referring to some provisions applicable under the new safeguard procedure. Particularly, provisions as to the creation of creditor’s committees and the vote process
discussed in the safeguard procedure are also applicable under the reorganization
procedure.
D) The simpli…cation of the liquidation procedure
The liquidation procedure has been also maintained and it is initiated when the
debtor has ceased its payments and the rescue of its business is manifestly impossible. Similar to the reorganization procedure, a debtor must …le for liquidation
within forty-…ve days from its default of payments if it has not begun a composition
procedure (Art. 97). The main innovation of the new bankruptcy law regarding the
liquidation procedure is the creation of a simpli…ed procedure intended to accelerate
28 The
former bankruptcy provisions required that the debtor …les for the bankruptcy
proceedings within …fteen days following its default of payments.
60
the liquidation of small companies.29 In this case, it is the liquidator who should
determine, within three months following the commencement of the liquidation procedure, the assets of the debtor that may be sold in a private sale and at the end
of this period, the remaining assets should be sold at public auction. In addition,
the veri…cation of claims should be limited to those that ranking could enable payment and to claims resulting from employment contract. Finally, the Court should
pronounce the closing of the liquidation proceedings one year at the latest after
the commencement of the procedure and in some special cases, this period can be
extended for three additional months (Art. 125). Another measure intended to accelerate the liquidation procedure consists in determining a time limit at the end of
which the closing of the case will be examined. At the expiry of a two-year period
and if the procedure has not yet been closed, the debtor, the Public prosecutor or
any creditor can seek the Court to close the liquidation procedure. Another innovation of the law is that the liquidation procedure may lead to the sale of the debtor’s
business which was not allowed under the old bankruptcy law. The liquidator or the
administrator shall manage the business, prepare the sales plan and carry out the
acts necessary to implement the plan (Art. 105).
E) Alleviation of certain sanctions
The new provisions alleviate some sanctions applicable to managers. The goal is to
induce managers to seek preventive and safeguarding measures at an earlier stage.
For example, under the new law, the manager may not be sued for his defective
management if the safeguard or the reorganization plans succeed. The goal of this
provision is to encourage the manager to contribute to the success of the plan. In
addition, the new bankruptcy law replaces the former sanction which permitted the
29 The
provisions of the simpli…ed liquidation procedure are applicable to companies that
do not own real estate property, whose number of employees does not exceed 5, and whose
annual turnover is lower than 750,000 e.
61
Court to extend the ongoing bankruptcy procedures to the managers. The Court may
now order managers to pay debtors’debts only in case of liquidation and when they
contributed to the default of payments. There is another alleviation that concerns
the personal bankruptcy sanction (faillite personnelle).30 Previously, this sanction
was not subject to any statute of limitation. It may now be initiated only within
three years from the date of the bankruptcy judgment and the Court must specify
the maximum period during which the sanction applies and this period may not
exceed 15 years.
One should note that the safeguard procedure was not as successful as had been
hoped. In 2007, safeguard proceedings have represented just 1% of the 50,000 insolvency proceedings, which is deemed insu¢ cient. We should note that legal systems
are not the only responsible for the low level of safeguard procedures. The main
reason for this lack of success is the debtor’s stigma attached to insolvency proceedings in France, especially among family-owned …rms. Although the safeguard
procedure aims at anticipating the …rm’s di¢ culties at an early stage, debtor’s management still delays …ling a petition for the commencement of safeguard proceedings
for so long that it reaches a point at which the company is already insolvent and it
becomes too late to enter into the safeguard procedure. Moreover, the law revealed
problems which were partially addressed by the Courts (especially in the Eurotunnel
safeguard). For instance, it was unclear whether investment funds had to sit on the
“credit institution” committee. The law also did not set out rules regulating the
voting of bondholders whose bond issue was not governed by the French law.
30 This
sanction may be imposed upon a manager who has committed serious wrongdoings. It prohibits the concerned manager from managing directly or indirectly a commercial
enterprise or an enterprise of the private sector.
62
For these reasons, French insolvency law has been amended by the ordinance of
December 18, 2008 only three years after its adoption. This reform comes into force
on 15 February 2009. The Ordinance is aimed at improving, more particularly, the
e¢ ciency of the safeguard procedure.
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68
[45] Tucker and Moore (1999), “Reorganization Versus Liquidation Decision for
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Chapter 3
Reorganization of Bankrupt Firms in France
Descriptive Statistics
3.1
Introduction
This chapter o¤ers a …rst look at …nancial reorganization in France. It examines a
micro dataset of 500 …rms in reorganization that …led for bankruptcy in the commercial Court of Paris during the 1995-2004 period and that had led to the con…rmation
of a reorganization plan within the framework of a continuation or a sale.1 Descriptive
statistics from the data are used to provide demographic and …nancial characteristics
of reorganized …rms and to characterize the main features of the bankruptcy process
in France.
Our primary purpose is to provide an outline of fundamental facts about business reorganizations under the French bankruptcy Code. The data reported in this
chapter include size, solvency, corporate or individual debtor type, type of businesses, claims’ variables, data speci…c to each form of reorganization, reasons for
…ling, and time spent in reorganization.
1 See
Section 2.3 for an overview of the French bankruptcy law.
69
70
The chapter is organized as follows. Section 3.2 describes the sample and how
the data were collected. Section 3.3 examines the status of the studied cases. In
section 3.4, we present a detailed description of the …rms’characteristics including
age, legal entity, size, business’s type, and solvency. Section 3.5 focuses on claims’
variables according to their ranking and to creditors’ nature. Section 3.6 and 3.7
describe some data speci…c to continuations and sales, respectively. In section 3.8,
we report the reasons for …ling bankruptcy. Section 3.9 focuses on the time spent in
reorganization. In the …nal section, we conclude by a discussion of our …ndings.
3.2
Data and Sample
In France, every bankruptcy case is …led with one of the 190 commercial Courts. To
provide descriptive statistics on reorganized …rms and on the reorganization process
in France, we used a large database constructed from a speci…c commercial Court in
France. A complete national sample was far beyond the available resources. Specifically, we selected the sample cases from the commercial Court of Paris (Tribunal
de Commerce de Paris) for the 1995-2004 period. We chose the district of Paris
because it has the highest proportion of bankruptcy …lings on the national level. In
fact, about 11% of the French bankrupt …rms had …led in the commercial Court of
Paris during the study period.2 The district of Paris was also selected for ease of
access to the data. The choice of the 1995-2004 period was based mainly on reforms
timing to avoid the impact of a given reform on the reorganization process. Precisely,
the study period follows the reform of 1994 and precedes the reform of 2005.
Our sampling framework was designed to ensure a representative sample and
to have a su¢ cient number of cases in order to conduct analysis. The sample is
composed of two random sub-samples that re‡ect the proportion of continuation
2 Source:
www.insee.fr
71
and sale cases. A …rst sample of 350 cases is selected among the 1,718 cases that had
led to the continuation of the bankrupt …rm as the same entity. A second sample of
150 cases is selected among the 829 cases that had led to the sale of the bankrupt
…rm. Altogether, the initial sample is composed of 500 cases. The selection of these
cases was facilitated by access to the list of commercial reorganizations in Paris by
outcome during the 1995-2004 period.
We collected data about the individual and …nancial characteristics of the bankrupt …rms, the reorganization plans’characteristics, and the reorganization proceedings. In the absence of an electronic version of the …les, data were gathered manually
from several documents available in the …rms’individual …les: the bankruptcy declaration, Court’s decisions during the reorganization process, the list of claims, the
report on the business’s economic and employment situation, and the …nancial statements of the …rm at the time of bankruptcy.3 For each …ling, …nancial variables and
claims variables were measured at the year preceding the year in which the Court
ordered the opening of the reorganization procedure.
One should note that the study period includes the transition to the Euro; …les
were reported in French Franc, Euro, or both currencies. Therefore, we converted
data from Franc to Euro.4 In addition, given that the study covers a ten-year period,
all Euro values are expressed in December 2004 Euro on the basis of a consumer
price index. The reference base period is December 2004 and the current period
corresponds to the opening of the reorganization proceedings.
3 The
French names of these documents are respectively: “déclaration de cessation des
paiements, jugements du tribunal de commerce, état des créances, bilan économique et
social, états …nanciers”.
4 We used the following rate to convert data from Franc to Euro: 1 euro = 6.55956 FF.
72
3.3
Status of Cases
The status of the 500 sample cases was determined either directly based on Court
judgment or indirectly from other sources.5 It was easier to determine the status
of sales cases because all provisions and all payments to creditors were generally
completed within the year following the sale decision. Then, the judge should assert
the success of the sales plan and order the closing of the case. In reality, we noticed
that in many cases, the plan was completed, but the e¤ective “closing” of the case
might last many years. Thus, we assumed that a sale is “completed” if two years
had elapsed since the con…rmation of the sales plan. This condition was met in 150
cases which provided for a sales plan.
The situation is more complicated when the Court orders the continuation of
the case. In fact, payments to creditors may take many years and in some cases
the reorganized …rm cannot meet the provisions of the plan and consequently the
Court may order the cancellation of the plan and the liquidation of the …rm. The
350 cases including a continuation plan can be placed in one of the following four
status categories:
-
de…nitely completed
-
probably completed
-
in progress
-
converted into liquidation
A continuation is characterized as “de…nitely completed” if there is a judgment
asserting the success of the continuation plan and ordering the closing of the case:
e.g. all provisions and payments to creditors promised in the plan were completed.
Cases in the “probably completed” category are still not closed, but for which the
information documenting full compliance was obtained through other sources than
5 The
date on which the companies’status was last observed is 1st July 2010.
73
the judgment or for which the consummation of the plan has been assumed.6 A
case is classi…ed as “converted into liquidation”if there is a judgment asserting the
cancellation of the continuation plan and ordering the liquidation of the debtor.
Finally, cases classi…ed as “in progress” include cases that are still in progress and
for which the outcome of the reorganization plan (success or failure) is not known
at the time of the study. Applying this classi…cation, we …nd that out of the 350
cases in the sample, 120 cases are “de…nitely completed”, 14 cases are “probably
completed”, 45 continuations are still “in progress”, and 171 plans are de…nitely
“converted into liquidation”. According to these …gures, the proportion of completed
plans would vary between 38.29% and 51.14% while the proportion of plans converted
into liquidation would vary between 48.86% and 61.71% depending on the outcome
of cases “in progress”.7 Thus, it seems that the French system is not very successful
in achieving its …rst objective which consists in maintaining the …rm’s activity.
In Table 1, we sorted continuation cases by the status and the …ling year to provide a better picture of the progression of cases over time. The category “completed”
regroups together cases that are “de…nitely completed”and cases that are “probably
completed”. Not surprisingly, the older the reorganization case is, the less likely it
is still “in progress”. The table also con…rms that the proportion of cases ending
up into liquidation is very high; it varies between 33.33% and 62.5%. These …gures
may be even worse than reported if some cases “in progress” would be de…nitely
converted into liquidation.
6 The
consummation of the plan was assumed if more than one year had elapsed since
the last payment date …xed in the plan and the case was still not closed.
7 The total number of consummated plans would be bounded by 134 if all plans classi…ed
as “in progress” would fail and by 179 if all plans would succeed.
74
3.4
3.4.1
Firm characteristics variables
Legal structure
There are two main categories of legal structure available to businesses in France:
unincorporated businesses (natural-persons quali…ed as merchants or artisans) versus
incorporated businesses (public company "SA", company limited by shares "SAS",
limited liability company "SARL", private limited company under sole ownership
"EURL", partnership "SNC", limited partnership "SCS", and partnership limited
by shares "SCA").8
Table 2 displays the distribution of the reorganized …rms according to the legal
structure and the form of restructuring. It shows that around 58% of the …rms are
limited liability companies (SARL). This can be explained by the fact that this legal
entity is the most widely used in France. In fact, it has many advantages for small
companies, such as low stated capital requirements and simple rules and regulations.
We can also note that about 14% of the reorganized cases are …led by unincorporated
businesses. However, this feature varies according to the form of the restructuring. It
reaches more than 16% for cases that continue in the same entity, whereas it is only
about 9% for …rms that were sold. In addition, Table 2 shows that public companies
(SA) represent more than 38% of sold companies and only about 16% of …rms that
reorganize through continuation. It seems that it is easier to …nd a purchaser when
the …rm is an incorporated company. This may also suggest that buyers are more
interested in the size of the bankrupt …rm than in its legal structure because larger
…rms often operate in incorporated structure.
8 The
French names of these corporations are ‘Société anonyme’ (SA), ‘Société par
actions simpli…ées’ (SAS), ‘Société à responsabilité limitée’ (SARL), ‘Entreprise unipersonnelle à responsabilité limitée’ (EURL), ‘Société en nom collectif’ (SNC), ‘Société en
commandite simple’(SCS), and ‘Société en commandite par actions’(SCA).
75
3.4.2
Business type
We took a preliminary look at business type, beginning with the classi…cation of
businesses into three main sectors reported in Table 3: manufacturing, trade, and
services. Data show that the majority of the …rms in the sample perform in the “services”sector (60%) while 19% are in the “manufacturing”sector and the remaining
21% of the cases are in the “trade”sector. This …nding is not surprising and re‡ects
the industrial base in Paris. Then, businesses are classi…ed among 16 categories
de…ned by the NES classi…cation.9 Precisely, we converted the NAF codes contained
in reorganization …les to NES codes.10 The relative proportions of various types of
businesses in the sample are presented in Table 4. The most common type of bankrupt business is “personal service activities” at 30% of the speci…ed types of businesses. Because of the importance of this activity, we developed in Table 4 another
level which includes three activities. It appears that “hotels and restaurants”are the
most a¤ected by bankruptcy.
In addition, an important number of reorganized …rms perform in “trade activities” (20%), “business service activities” (16%), and “manufacture of consumer
goods” (13%). The remaining types of businesses had lower proportion of cases;
“construction”is represented in almost 5% of the cases and the other types are rare
or not represented at all.
Table 4 reports also the relative proportions of various types of businesses by
reorganization form. The most notable di¤erence is that almost 21% of the …rms that
are ultimately sold performed in “business service activities” while the proportion
of continuation cases operating in this type of business is around 15%. Potential
9 The
NES (Nomenclature Economique de Synthèse) classi…cation is the French aggregated economic classi…cation and it is comparable to the SIC (Standard Industry Classi…cation) in the U.S.
10 The NAF (Nomenclature des Activités Française) code re‡ects INSEES’classi…cation
of an enterprise according to its economic activity.
76
buyers may be interested in these activities because they do not use speci…c assets
which provide them more ‡exibility. “Trade” and “manufacture of food products,
beverage and tobacco”are more represented in continuations than in sales. For the
other types of businesses, the di¤erence among continuations and sales is very small.
3.4.3
Age
Table 5 indicates that the average (median) age of a bankrupt debtor is around 14.25
(10) years. The comparison of …rm age between the two forms of reorganization is
shown in Table 6. It shows that the average (median) age for the …rms that are
ultimately sold is equal to 16.39 (10.5) years whereas the average (median) age for
those that continue their operations in the same entity is equal to 13.33 (9) years.
Based on mean comparison test, …rms that are sold are older than the …rms that
reorganize in the same entity.11
3.4.4
Size
There are di¤erent measures of a company’s size, such as: assets, debts, turnover, and
number of employees. In this section, we will …rst examine each criterion separately.
Then, we will use the de…nition adopted by the European Commission on the 6th May
2003 to classify the …rms. Finally, we will compare the size of …rms by reorganization
form.
Table 7 sets for the overall distribution of reorganized …rms by assets and debts.
Overall, about 60% of the reorganized …rms have less than e500,000 in assets at the
time of …ling and only about 3% have more than e5 million. Table 7 indicates that
11 Before
performing the "di¤erence in means", the observations were truncated at the
and 99th percentile because of extreme values among the observations which might
a¤ect the statistical results. The test is de…ned as follows: t = r VXarCont: XVSale
ar
1st
Cont: +
Sale
NCont:
NSale
77
the average value of assets is e1,364,900 for the full sample. However, that number is
in‡ated by the few cases with very large assets. The largest …rm had a value of assets
greater than e90 million and the second largest …rm had more than e66 million in
assets. The median value of assets is a more modest at e385,500.
We use the same thresholds to classify the …rms by debts. The data show that
almost three-quarters of the …rms have a value of debts less than e1 million. Once
again, in‡uenced by the cases with the largest debts, the mean debt is e1,409,010
while the median debt is a much more modest e487,610. The overall distribution of
reorganized …rms by turnover in Table 8 shows the same picture. More than 84% of
the …rms have less than e2 million in turnover, whereas less than 1% of the …rms
have more than e50 million.
Another measure of size is the number of employees. Employment is not constant
over time, especially before and after a bankruptcy …ling. Nonetheless, the employee
data provide a glimpse into the social repercussions of bankruptcy. Table 9 shows
that the mean number of employees is around 16 while the median number is equal
to 5. The di¤erence between the mean and the median can be explained by the large
number of …rms having a very few number of employees. Table 9 reports that more
than the three-quarters of the …rms employ less than 10 persons and less than 1% of
the sample consist of …rms having more than 250 employees, as indicated in Table
9.
Based on the SME de…nition adopted by the European Commission on the 6th
May 2003, we can classify the reorganized …rms in four categories: micro, small,
medium and large enterprises.12 The de…nition introduces thresholds for three criteria to determine …rm’s category: employees, annual turnover and annual balance
sheet. Typically, micro enterprises should employ fewer than 10 persons and their
12 The
information is available in the website of the European Commission:
www.ec.europa.eu/index_en.htm
78
annual turnover or annual balance sheet total should not exceed e2 million. Small
enterprises are de…ned as enterprises which employ fewer than 50 persons and whose
annual turnover or annual balance sheet total does not exceed e10 million. Mediumsized enterprises are de…ned as enterprises employing fewer than 250 persons and
which have either an annual turnover not exceeding e50 million, or an annual balance sheet total not exceeding e43 million. Large enterprises should employ more
than 250 persons or should have an annual turnover exceeding e50 million and an
annual balance sheet total exceeding e43 million.13 Table 10 shows that around 68%
of the sample consists of micro enterprises and only 1% of the sample consists of
large enterprises.
The di¤erent measures of a company’s size show that the sample includes a large
number of small businesses and a very small number of large businesses. This …nding
is consistent with the distribution of …rms in France. Just as the great majority of
businesses in France are small businesses, so are the great majority of businesses in
bankruptcy.
Having looked at the whole sample, it is useful to compare the size of …rms by the
reorganization form. Table 6 indicates that acquired …rms, on average, have almost
two times more employees, assets and debts than …rms reorganized via continuation.
For example, the former have a mean value of assets of e2,159,180 compared to
e1,063,880 for the latter. Moreover, …rms that were sold employed, on average, 24
employees compared to 12 for continuations. As one would expect, the comparison
of employees, assets and debts means between the two forms of reorganization shows
a signi…cant di¤erence (at a 5% level).
13 It
is necessary to note that while it is compulsory to respect the sta¤ headcount
thresholds, an SME may choose to meet either the turnover or balance sheet ceiling. It
does not need to satisfy both and may exceed one of them without losing its status.
79
Table 7 indicates similar results. About 4% of the acquired …rms had a value of
assets less than e100,000 whereas this …gure is around 20% for continuations. In
addition, around 32% percent of …rms that are sold had more than e1 million in
assets, while this …gure is about 12% for …rms that continue their operations as the
same entity.
Based on the SME de…nition adopted by the European Commission, data in
Table 10 show that around 11% of the acquired …rms in the sample are medium or
large enterprises. This …gure is around 4% for …rms that remain in the same entity.
Overall, the data suggest that …rms which are ultimately sold are larger than
…rms that continue in the same entity.
3.4.5
Solvency
To explore the relative solvency (or insolvency) of the debtors, we used the debtsto-assets ratio. Typically, a lower ratio indicates a better …nancial health. Table 11
indicates a mean (median) solvency ratio of 1.65 (1.29) for the full sample. Moreover,
in nearly three-quarters (73.5%) of the cases, the debtors’balance sheet listed total
debts which exceed total assets and in nearly one quarter of the cases (23.5%) debtors
have twice more debts than assets. Table 11 also shows the di¤erence in debts-toassets ratio between the two forms of reorganization. Sales with a mean (median)
value of 1.52 (1.26) seem in better …nancial conditions than continuations which have
a mean (median) ratio of 1.70 (1.31). However, the t-test shows that the di¤erence
between the two groups is not statistically signi…cant. Overall, these data document
the fact that French …rms entering into bankruptcy process are often highly levered.
This can be explained by the fact that it is di¢ cult for managers to admit the defeat
and to declare bankruptcy. Instead, they avoid the bankruptcy process as long as
possible which may increase the debts and worsen the …nancial health of the …rm.
80
Another way to interpret the solvency data is to analyze them as a function of
size (measured by assets). Table 11 illustrates the mean and median value of debtsto-assets ratio across a range of asset classes for the full sample and for the two forms
of reorganization. There appears to be a negative correlation between size and the
debts-to-assets ratio. Typically, larger entities seem to be more solvent than smaller
ones. For example, the mean (median) value of debts-to-assets ratio is equal to 3.08
(2.34) for cases with less than e100,000 in assets. This ratio decreases to 1.27 (1.20),
respectively, for cases that have more than e500,000 and less than e1,000,000 in
assets. For cases with more than e5,000,000 in assets, the mean (median) solvency
ratio is equal to 0.75 (0.67). We found the same tendency in both forms of reorganization: debtors with more assets are more likely to be solvent. There are a number of
possible explanations for this relationship. First, larger entities are usually subject
to higher …nancial scrutiny than smaller businesses. Second, larger businesses may
have recourse to …nancial consultants who make them aware of bankruptcy long
before they collapse. Third, creditors holding large claims would not allow a large
company to get too insolvent before initiating the bankruptcy process.
3.5
Claims variables
We used the list of claims, when available in …les, to collect claims variables.14
Particularly, for each case, we have computed the amount of claims and the number
of creditors. Then, claims were sorted out according to their ranking and to the
nature of creditors.
14 We
should distinguish between debts and claims. Debts variable is obtained from the
…rm’s …nancial statements whereas claims’variables are obtained from the list of claims.
In fact, creditors are required to submit their claims to the Court nominee within two
months from the publication of the opening judgment; otherwise, their claims would not
be reimbursed. Thus, the total amount of claims may di¤er from the amount of debts.
81
As indicated in Table 12, a reorganized …rm involves on average 37 creditors;
this number being signi…cantly higher for sales (49) than for continuations (32). The
table also shows that the mean (median) value of total claims is equal to e1,081,380
(e446,120). The variance indicates how the mean is distorted by very few cases
with a large amount of claims (the standard deviation is equal to e3,905,470). In
e¤ect, if we eliminate 5% of the …rms having the biggest amount of claims (22
…rms), the mean value of total claims in the new sample would decrease substantially
(e610,990). Table 13 illustrates claims variables by reorganization form. We notice a
signi…cant di¤erence between continuations and sales. Precisely, acquired …rms have
larger claims than continuations.
Moreover, data provide information on the three largest claims. On average, the
largest claim represents 40% of the total claims and the three largest claims represent
more than 67% of the total claims.
3.5.1
Claims by ranking
As Table 12 indicates, almost every …ling involves some privileged and ordinary
claims at the time of bankruptcy. For the full sample, privileged claims represent
about 57% of the total amount and they involve only a low proportion of superpreferential claims (7%). Moreover, the average (median) value of privileged claims
is equal to e459,800 (e210,040) while these …gures are equal to e607,370 (e136,150)
for ordinary claims.
Table 13 shows the same proportion of privileged and ordinary claims for both
forms of reorganization (respectively 57% and 43%). Moreover, the claims by ranking
are signi…cantly higher for acquired …rms. Precisely, acquired …rms have almost twice
as much privileged claims as continuations (e764,620 for the former compared to
e353,690 for the latter). The di¤erence is also signi…cant when comparing ordinary
82
claims; the mean value of ordinary claims is equal to e588,800 for continuations and
e660,730 for sales.
3.5.2
Claims by creditors’nature
About 63% of the full sample have positive wage claims.15 For these cases, the average
value is e79,516. In addition, wage claims are signi…cantly higher for incorporated
than for unincorporated …rms, with an average value of e87,237 compared to e10,933
for the latter. This …nding is not surprising since incorporated …rms have more
employees than unincorporated ones. On an individual basis, the average (median)
wage claim per worker is equal to e3,121 (e1,301) for the …rms having at least one
worker. The wage claim per worker exceeds the value e1,000 in 56% of the cases
and the value of e3,000 in 31% of the cases.
As expected, Table 12 indicates that banking claims represent an important
component (22% of total claims). Moreover, about 77% of the sample …rms involve
some banking claims and in 25% of the cases, they represent more than 35% of the
total claims. The average (median) value of banking claims is equal to e293,430
(e42,380) and the largest banking claim reaches e31,341,390. Statistics also show
that the number of banks among the creditors exceeds one in 40% of the cases and
three in 18% of the cases re‡ecting the fact that multiple banks lending to a …rm is
frequent.
Another interesting feature lies in the importance of government and social claims
in France. In fact, each of them represents, on average, 20% of total claims at the
time of bankruptcy. For the full sample, Table 12 reports a mean (median) value of
e135,720 (e44,870) for governmental claims and a mean (median) value of e118,170
(e62,150) for social claims.
15 There
are 267 cases of 426 that have positive wage claims.
83
In Table 13, there is a comparison between sales and continuations regarding the
proportion and the amount of claims by creditor’s nature. There is not a signi…cant
di¤erence between the claims’distribution for both forms of reorganization except
wage claims proportion which is signi…cantly higher for acquired …rms. The data
also show that claims’ amounts by creditor’s nature are larger for sales than for
continuations. This …nding is not surprising since acquired …rms have more claims
than continuations and the distribution is similar.
3.6
Continuations
The judge opts for a continuation only if he assesses that the …rm can keep operating
and the claims can be reimbursed.16 The duration of the plan is …xed by the Court,
it should not exceed ten years and the repayments should be based on reasonable
…nancial forecasts. Creditors can agree to write down a fraction of their loan or
receive a fraction of the …rm’s equity, in exchange for these write-o¤s.
In practice, the Court often o¤ers a quick repayment with write-downs or a
long-delayed repayment in full. In our sample composed of 350 continuation cases,
the Court proposed a single repayment for 259 cases (74%), two alternatives of
repayment for 69 cases (19.7%), and three alternatives for 8 cases (2.3%). For the
remaining cases, the judgment containing the continuation decision and information
about the plan was not available.
More details about continuation plans are presented in Table 14. We should notice
that the statistics reported in this table correspond to expected values because they
are derived from the judgment …xing the modalities of continuation plans and not
from the follow-up of the plans’implementation.17 The plan duration in this study is
16 See
L621.70 under the old commercial Code (2005).
Court may order some modi…cations in the modalities during the implementation
of the plan. For example, the duration of the plan may be extended or shortened.
17 The
84
de…ned as the time spent between the continuation judgment and the last payment
date …xed by the Court. Table 14 suggests that continuation plans may last many
years. On average, the duration …xed by the Court is about 8 years and in 50% of
the cases the duration exceeds 9 years.
Table 14 also shows that the expected time to the …rst payment to creditors is
less than one month in 50% of the cases. However, the expected amount of the …rst
payment represents less than 4% of total claims in 50% of the cases. One possible
explanation for this quick but low repayment is that the French bankruptcy Code
states that, on the one hand, some claims should be reimbursed without moratorium
and, on the other hand, these are small claims.18
Moreover, Table 14 illustrates the expected percentage of repayments within different periods. We notice that the repayments to creditors are still low even nine
months after the continuation decision. On average, expected payments should represent about 10% of total claims within nine months. The percentage of accomplished
payments should reach more than 17% of total claims, on average, within one year.
This important increase of the expected percentage of payments can be explained by
the fact that in many cases, the Court decides that the …rst payments to creditors
should begin one year after the continuation judgment. We also note that four years
after the continuation judgment, the average of payments to creditors is expected to
be less than 50% of total claims.
Another interesting feature in our study lies in the payo¤ rate to creditors when
the …rm is reorganized within the framework of a continuation. Because this information was not directly available, we made an approximation based on the case status,
on debt write-o¤s, and on the expected payments …xed in the continuation plan.
These rates do not take into account any modi…cations occurring during the plan’s
18 Debt
moratoriums shall not apply to claims which do not exceed e152 (within a limit
of 5% of the estimated liabilities) as well as to some claims mentioned in the labour Code.
85
implementation. In addition, payo¤ rates were not calculated for cases “in progress”
since real rates may increase considerably especially if the higher payments will take
place at the end of the plan. Table 15 shows payo¤ rates for completed and cancelled
plans. As indicated in the table, the mean payo¤ rate for completed cases is equal
to 90%.19 This value is less than 100% because some creditors may accept write-o¤s
either voluntarily or in exchange for early reimbursement. In about 64% of completed
cases, creditors received a 100% payo¤ rate which is relatively high.20
The picture changes dramatically for cancelled plans. As shown in Table 15, the
average (median) payo¤ rate is equal to 33% (23%). Moreover, creditors receive a
payo¤ rate of less than 12% in one quarter of the cases and less than 50% in about
three-quarters of the cases. One should notice that the e¤ective payo¤ rates may
be worse than reported in the table since some time may elapse between the last
e¤ective payment and the judgment ordering the cancelling of the plan. Payments
expected to be paid during that period of time were not excluded and led to an
overestimation of the payo¤ rates.
3.7
Sales
The judge opts for the sale of the …rm if he believes that the …rm cannot continue
its operations and reimburse its creditors in the future. Table 16 presents some
statistics on the sales price, purchase o¤ers, and employees. The sale price varies
from e7,500 to e1,981,840 and the average (median) value is equal to e149,146
(e70,000). Moreover, the comparison of the sale price with the total amount of
claims shows that in about half of the cases, the sale price covers less than 11%
of the claims’ amount. There were only two sales in which the price exceeds the
19 Completed
cases include cases that are “de…nitely completed” and cases that are
“probably completed” as de…ned in Section 3.3 of the present chapter.
20 There are 85 cases of 133 that received 100% payo¤ rate.
86
amount of claims, for the other cases the price represents less than 65% of the
claims. The payo¤ rate of sales seems to be low. There are two possible explanations
to this …nding. First, the sales prices are very low because potential buyers would
systematically underestimate the price of a bankrupt …rm to re‡ect related risks.
Second, the judge generally chooses to sell the …rm because it has many debts and
cannot repay them within the framework of a continuation.
Table 16 also shows that the average (median) number of dismissed employees
is about 6 (1). The di¤erence between the mean and the median can be explained
by the fact that a small number of sales had engendered the dismissal of a large
number of employees. On the other hand, the proportion of dismissed employees is
about 17% in half the cases.
From the opening date of the reorganization proceedings, all persons except directors of the company or relatives of a director may submit a purchase o¤er. According
to Table 16, the average number of proposals is around two and it varies from 1 to
11 o¤ers. However, many potential buyers dropped out at last minute. As a result,
their proposal is no longer taken into consideration. Thus, by “e¤ective” proposals
we mean proposals emanating from present buyers or those represented the day when
the judge decides on the …rm’s outcome. The average number of e¤ective proposals
is around one.
If there are many o¤ers, the Court must select the o¤er that ensures the best
prospects for employment and repayment of debts.21 This chronological order suggests that priority should be given to social rather than …nancial consideration. To
consider this e¤ect, we examined the sales involving two or more e¤ective proposals
as well as the judgment containing the Court’s decision. There are 18 cases that
meet these criteria.
21 See
L621.87 under the old commercial Code (2005).
87
The examination of these cases shows that the judge selected the proposal with
the best price in more than 75% of the cases and he selected the proposal with
fewer dismissals in more than 80% of cases. It seems that the judge combines both
social and …nancial e¢ ciency. However, it would be interesting to conduct econometric analysis to investigate the determinants that a¤ect the choice between rival
o¤ers. Unfortunately, this kind of analysis was not undertaken in this study since
the number of observations is too small (18 observations).
3.8
Reasons for …ling for reorganization
When debtors …le for reorganization, they should report in the bankruptcy declaration the causes they think to be the origin of default. We recognize that debtors might
not give an objectively correct answer of what was actually wrong either deliberately
or not. For example, the debtor may say that business conditions in the industry
were very bad while a business analyst might say the manager was incompetent. In
addition, some debtors may give many causes which may prevent us from identifying
the main cause of default. We collected the causes from the …les and we developed
a code sheet of 98 reasons for …ling bankruptcy. With more than 90 categories of
responses, we had plenty of information, but not an overall picture. Consequently, we
decided to regroup the answers, collecting them into related reasons. We developed
seven groups:
- External business environment
- Strategy
- Management / Business operations
- Financing
- Outlets
- Accidental causes
88
- Personal causes
Details explaining which reasons were grouped into which categories are reported
in Appendix I. The grouping is not perfect. Some of the debtors’ responses are
ambiguous, and some could overlap one or more categories.
The 461 debtors that reported the explanations for the reason their businesses
went into bankruptcy gave more than 1,000 responses.22 About 73% of the debtors
that gave explanations identi…ed at least two reasons, about 35% gave at least three
reasons, and less than 9% gave four reasons or more. Table 17 illustrates the …ve
main reasons reported by the debtors when …ling for reorganization. The most frequently listed reasons are: “bad economy” (21.9% of the cases), “declining sales”
(13.23%), “competition”(12.58%), “high loans and debt service”(11.5%), and “loss
of important clients”(8.46%).
We should note, however, that the frequency of these reasons decreases if we
restrict the sample to the debtors that identi…ed a single reason. In this case, only
8.87% of the debtors identi…ed “bad economy” as the cause of the encountered
di¢ culties. This …nding demonstrates that even if the reasons illustrated in Table
17 are not the main causes of default, they are identi…ed by many debtors as factors
that contributed to bankruptcy …ling.
Table 17 reports the …ve main reasons for …ling for bankruptcy according to the
form of the reorganization (continuation or sale). We …nd again “bad economy”,
“declining sales”, and “competition” among the …ve main reasons. However, an
interesting feature in the table is that the cause “Medical problems/death of the
manager”appears in 9.5% of the cases leading to sale and it appears only in 4% of
the cases leading to continuation suggesting that …rms whose managers su¤er from
22 We
have collected only the four …rst reasons reported by the debtors. There are few
debtors that gave more than four reasons.
89
personal problems would …nd more di¢ culties to continue the operations of the …rm
within the framework of a continuation.
The debtors’responses by groups are illustrated in Figure 1. Because of the multiple responses, the percentages of all categories add to more than 100%. The most
obvious point of this graph is that a collection of reasons dominate the reorganization …lings. Precisely, the three most frequently listed reasons are those having to do
with the “external business environment” (61.17%), those related to the “internal
operations of the business”(44.25%), and those related to “…nancing”(42.95%).
Once we have presented the overview of the reasons that businesses end up in
reorganization, we take a look at whether the split in the business sample among
individuals and corporations would show some disparities. Overall, Figure 2 shows
that the most frequently listed reasons are the same for incorporated and unincorporated …rms. As expected, debtors of unincorporated …rms listed more reasons related
to “personal problems” since the …nancial health of the …rm may depend strongly
on the owner. In fact, family problems, death, or personal bankruptcy of the owner
a¤ect generally the …nancial survival of the business.
Finally, we explored whether the aggregated data hide critical di¤erences among
debtors according to the reorganization form (continuation or sale). Figure 1 illustrates the frequency of listed categories by reorganization form. Overall, “external
business environment”, “business operations”, and “…nancing” are still dominating
reasons for …ling. Figure 1 also reveals that there are some di¤erences in the explanations the debtors give according the reorganization form.
First, debtors that ultimately continue their operations mentioned “…nancing
problems”and “accidental causes”more frequently than acquired …rms (respectively
48% versus 31% and 34% versus 19%). It is reasonable to expect that businesses
encountering …nancial problems will reorganize as the same entity since the continuation plan would generally extend the maturity of the debt contract and, therefore,
90
would resolve the …nancing problems of the …rm. As for accidental causes, if the
Court observes that the damage caused by the accident may be repaired within a
short period, it may order the continuation of the …rm especially if the business has
been prosperous before the accident.
Second, “personal problems”and “strategy”are listed much more often for …rms
reorganizing via sale than those reorganizing via continuation (respectively 12%
versus 6% and 18% versus 9%). Not surprisingly, most …rms whose managers evoked
personal problems end up in sale. In fact, many companies, especially unincorporated
ones remain dependent on their owners. When this latter can no longer run the
business the Court may have no option but to order the sale of the business. If we
turn to problems related to strategy, the di¤erence in the frequency among the two
forms is less obvious. One can suppose that strategy problems are sometimes so
severe that a simple extension of debt maturity would not resolve the main problem
and the Court may prefer ordering the sale of the business.
Third, “business operations and management” are evoked in 45% of cases that
end up in continuation while these problems are listed in 42% of cases that end up
in sale. In one sense, it is reasonable that …rms encountering business problems …le
for bankruptcy. This demonstrates that the bankruptcy system works the way that
it should. Firms …le for bankruptcy to resolve business problems.
3.9
Time in reorganization
Based on the French Bankruptcy Code, the time spent in reorganization is the time
between the judgment ordering the opening of the reorganization procedure and the
judgment ordering its closure. There are two main phases in reorganization:
91
Phase 1: Opening to con…rmation
This phase can be divided into two sub-periods: the …rst one is under the control
of an administrator and lasts from the opening of the reorganization proceedings to
plan submission. The second one is under the control of the Court and lasts from
the plan submission to con…rmation. In practice, the decision of the Court depends
on the administrator’s opinion upon the …rm’s survival prospects. Thus, in 92.4% of
the sample cases (462 of 500 cases) the judge followed the suggestion of the administrator and con…rmed the draft plan. There is only one case where the administrator
suggested the liquidation of the …rm while the judge ordered its reorganization via
continuation. For the remaining 37 cases, the administrator presented two alternative
plans and the judge con…rmed one of them.
Phase 2: Con…rmation to closure
This phase is dedicated to the implementation of the plan and has two possible
outcomes: the …rst outcome is the success of the reorganization plan; in this case
the closure coincides with the judgment asserting the success of the reorganization
plan and ordering the closing of the case. The second outcome is the failure of
the reorganization and its conversion into a liquidation procedure; in this case, the
closure coincides with the judgment ordering the liquidation of the case.
Table 18 presents some descriptive statistics on the time spent in the di¤erent
phases of the reorganization process by reorganization form (continuation/sale). The
table shows that “opening to closure” and “con…rmation to closure” variables are
based only on 353 of 500 observations because the remaining cases were still pending.
There is a proportion of pending cases that have their continuation plans in progress
especially the most recent ones, but there is also a substantial number of pending
cases that have their reorganization plans already …nished and they are still pending
because the judge did not order the closing of the case, yet. We noticed that the
second problem concerns mainly sale cases.
92
The average (median) time between the opening and the closure of a continuation
case is equal to 71.41 (59.83) months while these …gures are equal to 61.28 (52.64)
months for a sale case. It is di¢ cult to interpret and compare these …gures because
there are at least two biasing factors. First, the closing of the case by the Court may
occur many months after the e¤ective date asserting the success of the plan. Thus,
the time between the opening and the closure given in Table 18 exceeds the time
e¤ectively spent in reorganization. Second, one should notice that the table gives
aggregate data for continuation plans that succeed and those that fail. In Table 19,
we compute time variables separately for successful and failing continuation cases
to avoid the second biasing factor. As expected, successful cases took much more
time than failing ones. Precisely, the average (median) time between the opening
and the closure of a continuation case that ultimately succeeds is equal to 103.42
(109.31) months while it is equal to 52.12 (42.11) months for a continuation case
that ends up in liquidation. Table 19 also shows that successful cases spent most
of the reorganization time in the con…rmation to closure phase. Thus, the opening
to con…rmation phase takes on average 1.37 year while the implementation of the
continuation plan needs on average 7.2 years.
Another variable of interest is time from opening to con…rmation. Table 18 shows
that it takes longer time to con…rm a continuation plan than a sale plan. The average
(median) time spent by …rms from opening to con…rmation is 16.96 (17.26) months
for continuations and only 9.2 (8.2) months for sales. One possible explanation is that
the administrator search promptly for potential buyers when the …rm have serious
problems and cannot keep operating to avoid more deterioration in …rm assets.
Another explanation lies simply in the fact that the drafting of a continuation plan
may take more time than a sales plan.
Table 19 also indicates that the time spent from opening to con…rmation is similar
for successful and failing continuation cases. The mean (median) time from opening
93
to con…rmation is equal to 16.43 (16.04) months for successful cases and 16.9 (17.62)
months for failing cases.
As mentioned previously, the “observation” period is dominated by the administrator who draws up the reorganization plan and guides the judge in the …nal
decision. In fact, Table 18 shows that opening to plan submission phase, which is
under the administrator control, lasts on average 14.58 (7.84) months for a continuation (sale), whereas plan submission to con…rmation phase, which is under the
judge’s control, lasts on average 2.37 (1.39) months.
In table 20, we compare the opening to con…rmation times by …rms’legal structure (incorporated versus unincorporated). Figures show that it takes slightly longer
to con…rm unincorporated cases than incorporated ones. For the full sample, the
average time to con…rmation is 16.56 months for unincorporated businesses and 14.34
months for incorporated businesses. This result is even more pronounced when the
con…rmation leads to the sale of the …rm. In this case, the average time to con…rmation is 11.57 months for unincorporated …rms and 8.97 months for incorporated
…rms. This observation suggests that it is more di¢ cult to …nd a purchaser when
the …rm is unincorporated.
Finally, a comparison was made of the average and median times from opening
to con…rmation, sorted by the level of claims on one hand (Table 21) and by assets
amounts on the other hand (Table 22). One would expect that the largest the case
is, the longest it takes to be con…rmed. Contrary to expectations, it does not appear
to be a strong correlation between the length of time from opening to con…rmation
and the size of the …rm. However, when …gures are sorted by reorganization form,
it appears to be a slight positive correlation between the size and the time to con…rmation. Nevertheless, we should note that the very largest cases appear to take
less time to be con…rmed regardless of the reorganization’s outcome. The statistics
94
regarding the largest cases should be viewed with caution because the number of
very large cases in the study was quite small, only 9 cases.
3.10
Conclusion
This chapter has provided a description of a micro data set of 500 …rms which …led
for reorganization under the French bankruptcy Code during the 1995-2004 period
and which had led to the con…rmation of a reorganization plan. Speci…cally, we have
laid out a basic demographic and …nancial description of reorganized …rms and we
have described the main features of the bankruptcy process in France.
We now have substantial data about the …nancial characteristics of reorganized
businesses, including age, size, legal structure, type of business, and solvency as well
as data speci…c to each form of reorganization. We also have an idea about claims’
variables and time spent in reorganization. Moreover, we have an overview of the
reasons, from the debtors’perspectives, that business bankruptcies are …led and thus
of the problems that they are meant to address.
We have analyzed most of these aspects of business bankruptcy in terms of each
of the two forms of reorganization available to bankrupt …rms (continuation/sale).
Some of the themes that seem to us to have emerged from this …rst look at the data
are:
The sample is marked by its diversity; it includes a large number of small businesses and a small number of large businesses. The study also shows that …rms which
reorganize via sale are signi…cantly larger than …rms that continue as the same entity.
The study reveals that bankrupt …rms are highly levered when they enter the
bankruptcy process which suggests that …rms …le too late for bankruptcy. This observation is somewhat surprising for two main reasons. First, the French bankruptcy
law encourages alert procedures and provides extra-judicial reorganization measures
95
to detect any problems within the company as soon as possible in order to adopt
measures to improve the situation of the company. Second, the French bankruptcy
law is one of the most debtor-oriented laws around the world which should increase
the incentives of the debtor to …le early.
The data speci…c to continuations con…rm that the bankruptcy system in France
is favorable to debtors. In fact, …gures show that the Court con…rms continuation
plans that last many years and whose …rst repayments to creditors are very low. This
suggests that the …rst priority of judges is to maintain the …rm in activity at the
expense of creditors. The study also indicates that around half of the continuation
cases ended up as a failure and were liquidated. This …nding reveals an anomaly
in the system since the …rst objective of the reorganization procedure consists in
maintaining the …rm’s activity. Moreover, the payo¤ rate to creditors was very low
for failing cases and, hence, creditors …nd themselves in disadvantageous situation
one more time. The data speci…c to sales report low sale prices and low payo¤ rate
to creditors.
The most frequently listed reasons for bankruptcy are those having to do with
the “external business environment”, the “internal operations of the business”, and
those related to “…nancing”. Data show some di¤erences among the two forms of
reorganization. Overall, “…nancing problems”and “business operations and management”are mentioned more often in continuation cases whereas “personal problems”
and “strategy” are listed much more often in cases reorganizing via sale. “Business
operations and management”raise an interesting question about the e¢ ciency of the
bankruptcy system. In e¤ect, the French bankruptcy Code leaves the debtors with
signi…cant operational control in continuations. Therefore, it is reasonable to have
doubts about the ability of managers to reorganize e¢ ciently if they are describing
business and management problems they have been unable to solve.
96
Finally, the study shows that the French bankruptcy system provides a rapid
solution to bankrupt …rms. However, the implementation of this solution takes much
more time especially for continuations.
97
Table 1 : Distribution of Continuation Cases by Year and Status (%)*
Filing Year
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Completed
In progress
Converted into liquidation
48.94
45.76
52.63
51.28
25.00
30.43
22.22
42.86
4.17
16.67
0
0
0
5.13
12.50
26.09
22.22
9.52
50.00
50.00
51.06
54.24
47.37
43.59
62.50
43.48
55.56
47.62
45.83
33.33
* Based on a sample of 350 continuation cases.
Status as of July 1, 2010.
Table 2 : Distribution of Reorganized Firms by Legal Structure (%)*
Variables
Reorganization
Continuation
Sale
Incorporated
- SARL
- SA
- Others
85.92
57.75
22.94
5.25
83.62
62.36
16.38
4.89
91.28
46.98
38.26
6.04
Unincorporated
- Merchants
- Craftsmen
14.08
12.07
2.01
16.38
13.79
2.59
8.72
8.05
0.67
* Based on 498 reorganization cases (349 continuations and 149 sales) where the information
is available.
98
Table 3 : Distribution of Reorganized Firms by Industry (%)*
Variables
Manufacturing
Trade
Services
Reorganization
Continuation
Sale
19.23
20.30
60.47
19.75
21.24
59.01
17.83
17.83
64.34
* Based on 468 reorganization cases (339 continuations and 129 sales) where the information
is available.
Table 4 : Distribution of Reorganized Firms by Business Type (%)*
Variables
Agriculture, forestry and fishing
Manufacture of food products, beverage and tobacco
Manufacture of consumer goods
Manufacture of motor vehicles
Manufacture of capital goods
Manufactutre of intermediate goods
Energy
Construction
Trade
Tranportation
Financial activities
Real estate activities
Business service activities
Personal service activities
- Hotels and restaurants
- Recreation, sports and cultural activities
- Personal and households activities
Education, health, social work
Administration
Reorganization
Continuation
Sale
none
3.42
13.46
none
1.07
1.28
none
5.34
20.30
1.50
1.07
3.21
16.45
30.34
76.05
12.68
11.27
2.56
none
none
4.13
13.27
none
1.47
0.88
none
5.90
21.24
1.77
1.18
2.65
14.75
30.09
73.53
14.71
11.76
2.65
none
none
1.55
13.95
none
0
2.33
none
3.88
17.83
0.78
0.78
4.65
20.93
31.01
82.50
10.00
7.50
2.33
none
* Based on 468 reorganization cases (339 continuations and 129 sales) where the information is available.
99
Table 5 : Characteristics of Firms in Reorganization
Variables
N
Mean
Median Std. Dev.
Min
Max
Firm's age
472
14.25
10
14.06
0
83
Number of employees
478
15.54
5
51.97
0
831
Total assets (Thousands)
Total debts (Thousands)
302
302
1364.90
1409.01
385.50
487.61
6721.76
5750.84
2.57
9.71
92890.85
80600.51
Total debts / Total assets
302
1.65
1.29
1.30
0.21
13.36
Table 6 : Characteristics of Firms by Reorganization Form
Continuation
Variables
N
Mean
Firm's age
330
13.33
9
Number of employees
333
11.82
Total assets (Thousands)
Total debts (Thousands)
219
219
Total debts / Total assets
219
Sale
Median Std. Dev.
N
Mean
median
Std. Dev
t-test
12.92
142
16.39
10.5
16.25
0.045*
4
51.038
145
24.08
7
53.28
<0.001*
1063.88
1108.10
298.47
418.10
6362.00
5494.57
83
83
2159.18
2200.83
533.28
798.87
7574.00
6345.22
0.012*
0.001*
1.70
1.31
1.33
83
1.52
1.26
1.20
0.122
* Indicates a statistical difference between continuations and sales at the 5% level.
Table 7 : Distribution of Reorganized Firms by Assets and Debts (%)*
Assets
Variables
<=100,000
100,000< <=500,000
500,0000< <=1,000,000
1,000,0000< <=5,000,000
>5,000,000
Reorganization Continuation
15.64
44.30
22.15
14.98
2.93
20.18
44.39
22.87
10.76
1.79
Debts
Sale
Reorganization
Continuation
Sale
3.57
44.05
20.24
26.19
5.95
6.84
43.97
24.10
20.85
4.23
8.48
49.55
20.98
19.64
1.34
2.41
28.92
32.53
24.10
12.05
* Based on 302 reorganization cases (219 continuations and 83 sales) where the information is available.
100
Table 8 : Distribution of Reorganized Firms by Turnover (%)*
Variables
< 2,000,000
2,000,000 <= <10,000,000
10,000,000 <= < 50,000,000
> 50,000,000
Reorganization
Continuation
Sale
84.30
12.50
80.18
16.52
60.00
2.91
0.29
2.70
0.60
30.34
8.28
1.38
* Based on 345 reorganization cases (237 continuations and 108 sales) where the information is available.
Table 9 : Distribution of Reorganized Firms by Number of Employees (%)*
Number of employees
Reorganization
Continuation
Sale
Mean
Median
15.54
5
11.82
4
24.08
7
<=10
10<= <50
50<= <250
>=250
75.78
19.21
4.18
82.04
14.67
2.69
0.60
61.38
29.66
7.59
1.36
0.84
* Based on 479 reorganization cases (334 continuations and 145 sales) where the information
is available.
Table 10 : Distribution of Reorganized Firms based on SME Definition (%)*
Variables
Micro entreprise
Small entreprise
Medium entreprse
Large entreprise
Reorganization
Continuation
Sale
67.89
25.85
5.22
1.04
73.82
21.82
3.64
52.78
36.11
9.26
1.85
0.73
* Based on 383 reorganization cases (275 continuations and 108 sales) where the information
is available.
101
Table 11 : Debts-to-Assets Ratio by Assets' Amounts
Reorganization
Variables
N
Continuation
Mean Median
N
Sale
Mean Median
N
Mean Median
t-test
Debts-to-Assets ratio(a)
302
1.65
1.29
219
1.70
1.31
83
1.52
1.26
0.12
<=100,000
100,000< <=500,000
500,000< <=1,000,000
1,000,000< <=5,000,000
>5,000,000
47
133
68
45
9
3.08
1.54
1.27
1.24
0.75
2.34
1.33
1.20
1.03
0.67
44
96
51
24
4
2.98
1.53
1.24
1.18
0.79
2.35
1.31
1.15
1.03
0.77
3
37
17
21
5
4.48
1.59
1.35
1.32
0.73
2.31
1.62
1.25
1.15
0.65
0.84
0.72
0.50
0.37
0.72
(a)
Mean and Median values are computed for the full sample regardless of assets' amount.
Table 12 : Claims' Characteristics of Firms in Reorganization
Variables
N
Mean
Median Std. Dev.
Min
Max
Total claims (Thousands)
Total number of creditors
436
405
1081.38
36.62
446.12
24
3905.47
46.61
3.231
1
73605.66
617
Privileged claims (Thousands)
- Super-preferential claims (Thousands)
- Preferential claims (Thousands)
Ordinary claims (Thousands)
426
426
426
426
459.80
33.64
426.15
607.37
210.04
4.11
193.82
136.15
776.53
121.27
711.12
3523.52
0
0
0
0
6842.38
2022.51
6653.92
66968.05
Privileged claims / Total claims
Ordinary claims / Total claims
Super-pref. claims/ Privileged claims
Preferential claims / Privileged claims
426
426
425
425
0.57
0.43
0.07
0.93
0.59
0.41
0.02
0.98
0.26
0.25
0.10
0.10
0
0
0
0.28
1
1
0.72
1
Wage claims (Thousands)
Banking claims (Thousands)
Government claims (Thousands)
Social claims (Thousands)
Other claims (Thousands)
424
424
424
424
424
49.85
293.43
135.72
118.17
463.47
5.16
42.38
44.87
62.15
104.25
208.88
1588.67
317.03
206.31
2153.22
0
0
0
0
0
3789.25
31341.39
4641.97
1783.72
463.47
Salarial claims / Total claims
Banking claims / Total claims
Government claims / Total claims
Social claims / Total claims
Other claims / Total claims
424
424
424
424
424
0.05
0.22
0.20
0.20
0.34
0.01
0.10
0.12
0.15
0.28
0.08
0.26
0.19
0.18
0.26
0
0
0
0
0
0.68
0.99
0.99
0.99
1
316
316
316
316
316
316
315
315
317
317
317
317
317
317
317
317
317
317
Privileged claims (Thousands)
- Super-preferential claims (Thousands)
- Preferential claims (Thousands)
Ordinary claims (Thousands)
Privileged claims / Total claims
Ordinary claims / Total claims
Super-pref. claims/ Privileged claims
Preferential claims / Privileged claims
Wage claims (Thousands)
Banking claims (Thousands)
Government claims (Thousands)
Social claims (Thousands)
Other claims (Thousands)
Wage claims / Total claims
Banking claims / Total claims
Government claims / Total claims
Social claims / Total claims
Other claims / Total claims
0.04
0.22
0.19
0.20
0.35
36.49
289.43
96.46
86.65
463.44
0.57
0.43
0.06
0.94
353.69
24.01
329.59
588.80
968.11
32.23
Mean
Continuation
0.01
0.11
0.12
0.16
0.29
3.39
36.71
40.07
53.44
95.82
0.59
0.41
0.01
0.99
184.26
2.011
165.41
113.92
363.37
22
0.07
0.26
0.19
0.20
0.27
219.08
1804.71
190.98
135.59
2456.64
0.26
0.26
0.10
0.10
605.22
121.18
537.08
4040.39
4375.48
45.33
Median Std. Dev.
* Indicates a statistical difference between continuations and sales at the 5% level.
325
299
N
Total claims (Thousands)
Total number of creditors
Variables
0
0
0
0
0
0
0
0
0
0
0
0
0
0.28
0
0
0
0
3.23
1
Min
0.68
0.98
0.97
0.99
1
3789.25
31341.39
1660.75
1644.77
35169.50
1
1
0.72
1
6637.61
2022.51
4736.30
66968.05
73605.66
617
Max
107
107
107
107
107
107
107
107
107
107
110
110
110
110
110
110
110
110
111
106
N
0.06
0.20
0.21
0.18
0.35
89.65
305.26
252.04
211.53
463.56
0.57
0.43
0.09
0.91
764.62
61.07
703.54
660.73
1414.60
49.02
Mean
Table 13 : Characteristics of Firms by Reorganization Form
Sale
0.03
0.01
0.14
0.14
0.28
14.95
65.55
90.49
89.21
155.78
0.59
0.41
0
0.95
367
11.56
371.64
231.87
742.92
34
0.09
0.24
0.20
0.16
0.25
169.98
601.60
523.52
321.36
714.35
0.26
0.26
0.10
0.10
1079.9
117.83
1016.59
1107.64
1943.40
48.14
median Std. Dev.
0
0
0
0
0
0
0
0
0
0
0
0.02
0
0.54
0.26
0
0.26
0.35
28.28
4
Min
t-test
<0.001*
<0.001*
<0.001*
0.002*
0.990
0.990
0.024*
0.024*
<0.001*
0.090
<0.001*
<0.001*
0.020*
0.010*
0.600
0.390
0.260
0.850
6842.38
733.20
6653.92
7111.47
0.98
1
0.46
1
853.65
3732
4641.97
1783.72
3868.73
0.42
0.96
0.99
0.74
0.90
13125.21 <0.001*
304
0.002*
Max
103
Table 14 : Characteristics of Continuation Proposals
Variables
N
Mean
Median
Std. Dev.
Min
Max
Expected duration of the plan (months)
345
97.06
108.06
29.54
0
144
Expected time to the first payment (months)
Expected percentage of the first payment
345
332
3.50
9.12
0.98
3.97
4.79
17.40
0
0
13.34
100
Expected payments within 1 month (%)
Expected payments within 3 months (%)
Expected payments within 6 months (%)
Expected payments within 9 months (%)
Expected payments within 12 months (%)
Expected payments within 24 months (%)
Expected payments within 36 months (%)
Expected payments within 48 months (%)
Expected payments within 60 months (%)
Expected payments within 72 months (%)
332
332
332
332
332
332
332
332
332
332
4.95
6.76
8.78
9.81
17.66
28.35
38.84
49.40
59.80
69.60
0.36
1.34
2.70
4.11
12.16
22.55
33.65
44.54
55.50
66.74
14.38
16.68
18.89
19.12
19.60
19.20
18.73
18.24
17.72
16.59
0
0
0
0
0
5
13
17.88
18.50
18.50
100
100
100
100
100
100
100
100
100
100
Table 15 : Payments to Creditors by Continuation Cases' Status (%)
Variables
N
Mean Std. Dev.
Min
Max
25th%ile Median 75th%ile
Payments related to completed plans
133 89.88
19.39
10.12
100
87.31
100
100
Payments related to cancelled plans
161 32.67
27.31
0
100
11.86
23
49.44
Table 16 : Variables Specific to Sales
Variables
N
Mean
Median
Std. Dev.
Min
Max
Sale price (Thousands)
118
149146.40
70000
245600.5
7500
1981840
Sale price / total claims (%)
84
23.10
11.47
38.58
0.63
273
Number of dismissals
115
5.72
1
14.61
0
117
% of dismissed employees
108
22.53
17.48
24.02
0
100
Number of offers
81
2.14
2
1.73
1
11
Number of "effective" offers
55
1.56
1
1.01
1
7
104
Table 17 : The Five most Reported Reasons for Filing for Reorganization
Reorganization
Reason
Frequency
Percentage
101
61
58
53
39
21.91
13.23
12.58
11.50
8.46
Frenquency
Percentage
73
48
43
39
33
22.53
14.81
13.27
12.04
10.19
Frenquency
Percentage
28
19
13
13
10
20.44
13.87
9.49
9.49
7.30
Bad economy
Declining sales
Competition
High debt service
Loss of important clients
Continuation
Reason
Bad economy
Declining sales
High debt service
Competition
Delay in payment / nonpayment by clients
Sale
Reason
Bad economy
Competition
Medical problems / death of the manager
Declining sales
Loss of important clients
71.41
16.96
14.58
2.37
54.6
274
350
350
350
274
N
103
119
119
119
103
Time between opening and closure
Phase 1: Opening to confirmation
Opening to plan submission
Plan submission to confirmation
Phase 2: Confirmation to closure
Variables
Time between opening and closure
Phase 1: Opening to confirmation
Opening to plan submission
Plan submission to confirmation
Phase 2: Confirmation to closure
43.54
17.26
14.89
2.07
59.83
Median
39.6
4.52
4.55
1.45
39.77
Std. Dev.
Continuation
2.56
1.84
1.55
0.23
10.35
Min
160.4
32.22
30.51
13.61
182.43
Max
79
150
150
150
79
N
52.16
9.23
7.84
1.39
61.28
Mean
86.77
16.43
14.14
2.29
103.42
Mean
92.51
16.04
13.61
2.03
109.31
35.69
4.65
4.75
1.52
36
Median Std. Dev.
Success
6.67
6.18
3.64
0.23
19.8
Min
160.40
32.22
30.51
13.05
182.43
Max
171
171
171
171
171
N
35.22
16.9
14.5
2.4
52.12
Mean
Table 19 : Time in Continuations by Final Outcome (months)
Mean
N
Variables
Failure
28.96
5.69
5.47
1
29.07
Std. Dev.
Sale
27.38
17.62
15.19
2.07
42.11
27.37
4.6
4.48
1.32
27.7
Median Std. Dev.
45.86
8.20
6.99
1.13
52.64
Median
Table 18 : Time in the Reorganization Process by Reorganization Form (months)
2.56
1.84
1.54
0.23
10.35
Min
12.92
0.49
0.30
0.20
24.56
Min
128.84
30.83
26.73
12.3
147.78
Max
143.54
25.15
20.35
7.83
152.75
Max
106
Table 20 : Opening to Confirmation Interval by Legal form and Reorganization Form (months)
Continuation
Reorganization
Variables
Sale
N
Mean
Median
N
Mean
Median
N
Mean
Median
Incorporated
428
14.34
15.12
292
16.86
17.26
136
8.97
8.15
Unincorporated
70
16.56
17.03
57
17.7
17.72
13
11.57
11.64
Table 21 : Opening to Confirmation Interval by Claims Level and Reorganization Form (months)*
Reorganization
Continuation
Sale
Variables
Mean
Median
Mean
Median
Mean
Median
<=100,000
100,000< <=500,000
500,000< <=1,000,000
1,000,000 < <=5,000,000
>5,000,000
15.01
15.37
15.72
14.56
13.98
14.55
16.01
16.83
15.52
15.65
15.93
16.57
17.58
18.38
16.58
15.06
16.77
18.1
19.3
17.92
6.31
9.66
12.11
9.11
8.76
6.67
9.63
11.04
8.28
7.71
* Based on 436 reorganization cases (325 continuations and 111 sales) where the information is available.
Table 22 : Opening to Confirmation Interval by Assets Level and Reorganization Form (months)*
Reorganization
Continuation
Sale
Variables
Mean
Median
Mean
Median
Mean
Median
<=100,000
100,000< <=500,000
500,000< <=1,000,000
1,000,000 < <=5,000,000
>5,000,000
16.1
15.08
15.72
14.06
8.84
15.99
15.8
17.24
15.52
6.94
16.66
16.85
17.48
18.17
10.32
16.67
17.26
18.15
19.79
8.05
7.65
10.36
10.45
9.38
7.66
7.86
9.2
9.76
7.87
6.94
* Based on 302 reorganization cases (219 continuations and 83 sales) where the information is available.
107
Figure 1 : Listed Reasons for Filing Reorganization by Form and Grouping
70%
60%
50%
40%
30%
Reorganization
20%
Continuation
10%
Sale
0%
Figure 2 : Listed Reasons for Filing Reorganization by Legel Structure
70%
60%
50%
40%
30%
20%
Incorporated
10%
Unincorporated
0%
108
APPENDIX I: Stated Reasons for Filing : Groupings
External Business environment
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Bad economy
Competition
Decrease of prices
Increasing cost of doing business (raw materials, labor costs)
Increasing rent
Exchange rate
Technological revolution
Legislation (increase in VAT / new law / prefectorial authorization etc.
Problem related to the customer behavior
Bankruptcy of a subcontractor
Difficulties encountered by the subsidiary or the main branch are extended to the firm
Reputation needs costs and time
Inability to find skilled personnel / the firm is understaffed
Declining sales
Strategy
15
16
17
18
19
20
21
22
23
24
25
26
Takeover of a bad business
Failure of activity expansion
Failure of diversification
Expensive merger
The activity depends strongly on a specific sector or market
Overinvestment
Disinvestment from some projects
Continuation of an unprofitable business
Costly relocation
Location was bad
Large royalties
Problems related to lease-management
Management / Business operations
27
28
29
30
31
32
33
34
35
36
37
Bad management / inexperience
Problem related to management control
Time devoted to management is insufficient
Conflict between business partners concerning management
Excessive takings from receipts by management
Hard startup
Difficulties to realize a project / failure of an important project
Organizational problems
Slow implementation of new measures
Lack of dynamism and adaptation
Absence of an IT department
109
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Weak account reporting
The activity is not profitable
Operating loss
High costs compared to firm’s activity
Wage and social claims are too high compared to firm's activity
Problems related to bad predictions
Underestimation of the sector crisis
Bad evaluation of cost price
Bad evaluation of costs
Stock management
Over-sizing of production capacity
Problem with personnel
Unskilled personnel
Departure of critical personnel
Financing
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
High debt service
Banks refuse to support the firm
Bank overdraft is too high
Bank account is blocked due to bank restructuring
Excessive support of banks
Shorter delays on account receivable
Cash flow problem
Liquidity problems resulting from the dismissal of many workers
Absence of working capital
Increase in working capital requirement
Lack of equity
Problems related to the financing of restructuring measures
Financial structure
Bankruptcy of a shareholder
Old debts taken on at business purchase
Delay in payment / nonpayment by clients
Outlets
68
69
70
71
72
73
74
75
76
77
78
Bad quality of products
Obsolete products
Products lack diversity
Problems related to commercial strategy
Failure of a new commercial organisation
Difficulty to commercialize firms’ products
Marketing positioning
Concentration of retailing
Loss of important clients
Bankruptcy of important clients
Clients’ merger
110
Accidental Causes
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
War / attacks
Strikes
Weather related problems
Road work
Problems related to neighbours
Departure of many firms from the district
Robbery / fire / cow disease etc.
Defective installation
Temporary closing of the firm
Goods’ blocking through customs
Port’s closing
Conflict with a partner
Problems encountered with lessor
Important condemnation pronounced by the French industrial tribunal
Tax adjustment / Penalties due to delay in payment of tax and social claims
High compensation related to lease-purchase contract
The factor did not pay the firm
Personal problems
96
97
98
Medical problems / death of the manager
Family problems
Personal bankruptcy
Chapter 4
Reorganization of Bankrupt Firms in France
Continuation versus Sale
4.1
Introduction
For a long time, a liquidation/reorganization dichotomous view had dominated the
existing literature on bankruptcy. In the mid-1980, Baird (1986) proposed another
alternative for addressing bankruptcy which consists in selling the bankrupt company as a going-concern. Therefore, there are three possible outcomes for addressing
bankruptcy: the bankrupt …rm may reorganize as the same entity, sell the business
as a going-concern, or close the business and sell the assets piecemeal.
Most bankruptcy laws provide distressed debtors with two main bankruptcy procedures (liquidation and reorganization) that may involve some measures speci…c to
going-concern sales. For example, the bankruptcy code in the U.S. provides bankrupt
…rms with a section 363 sale.
Contrary to the most countries, the French bankruptcy law has the particularity
of o¤ering a speci…c procedure dedicated to sales as going-concern. Typically, during
the period covered by the study (1995-2004), the French bankruptcy law provides
111
112
distressed …rms with two forms of reorganization.1 The Court may order either the
continuation of the bankrupt …rm as the same entity or the sale of the bankrupt
…rm as a going-concern to another entity.
Very little empirical research has been conducted on the factors that in‡uence
whether the bankrupt …rm reorganizes as the same entity or is sold as a whole
especially in France. To our knowledge, the only study investigating determinants
that in‡uence the decisions of French commercial Courts about the outcome of
…nancial distress was conducted by Blazy et al. (2011). However, the authors compare
…rms that are reorganized (within the framework of a continuation or a sale) relative
to those that are liquidated and does not distinguish between …rms that reorganize
as the same entity and those that are acquired by another …rm.2
The object of this chapter is to address this lack of data and to provide new
evidence on the factors that would in‡uence the reorganization form in France (continuation as the same entity versus sale as a going-concern). We consider a unique
sample of 500 …rms that …led for reorganization between 1995 and 2004 in the Court
of Paris and that had their continuation or sale plan con…rmed. Then, we analyze
the e¤ect of several explanatory variables on the probability of keeping operations
in the same entity (continuation), over the probability of sale as a going-concern.
We use both standard logistic models which assume that the data are drawn from a
simple random sample and logistic models that take into account the sample design.
The remainder of the chapter is structured as follows: the next section focuses on
the sale versus reorganization debate and presents some empirical evidence. Section
1 The
French bankruptcy system was substantially reformed by the law of July 26,
2005. The sale of the bankrupt …rm as a going-concern is incorporated in the liquidation
procedure (Art. 97).
2 In Blazy et al. (2011) paper, the term “continuation” designates the restructuring of
the …rm as the same entity or the sale of the …rm as a going-concern which corresponds
to the term “reorganization” in our study and the term “reorganization” designates the
restructuring of the bankrupt …rm by keeping operations in the same entity which corresponds to the term “continuation” in our study.
113
4.3 discusses the potential determinants that may in‡uence the reorganization form
in France. Section 4.4 describes the data set and presents some descriptive statistics.
Section 4.5 presents logistic estimation for simple random samples and for complex
survey design. Section 4.6 discusses the results of the empirical analysis. The …nal
section of the chapter contains a summary and some concluding remarks.
4.2
The reorganization versus sale debate
In what follows, we present the logic and limits of both alternatives (reorganization/sale) and some empirical evidence on the comparison between them.3
4.2.1
Reorganization
The role of reorganization law is to provide a collective forum in which the different players try to solve the problems of excessive debt and illiquidity. In general,
reorganization addresses these problems by reducing the amount of debts and/or
by extending their maturity date. The ultimate objective of this procedure is to
maximize the value of the …rm by keeping operations in the same entity. Bankruptcy scholars advance many arguments to justify the necessity of a reorganization
procedure.
First, under non-bankruptcy law, each creditor has an incentive to be the …rst
to sue the debtor for payment if the …nancial situation becomes precarious. This
uncoordinated debt collection by the various creditors can be very costly. According
to Baird (1986), bankruptcy law prevents a costly and destructive race to the …rm’s
assets by o¤ering a collective procedure that freezes the rights of all investors in a
3 In
most papers, the term “reorganization” designates the restructuring of the bankrupt …rm in the same entity which corresponds to the term “continuation” in the French
bankruptcy system. Thus, the use of the term “reorganization” in this section implies
“continuation”.
114
…rm, values them, and then distributes these assets according to the priority scheme
that the parties agreed.
Second, Brown (1989) shows that con‡icting incentives of the claimholders classes
are likely to result in a continuous proposal process during which resources are
dissipated. The author demonstrates that the reorganization law, by providing rules
governing the negotiation process, yields a unique solution to the reorganization
process. Speci…cally, in the formal game, the impairment rule on voting, the agenda
rule, and the cram down rule are the key elements that determine the outcome of the
reorganization. Besides, con‡icts of interest can lead to the formation of coalitions
in order to extract concessions from other claimants. The role of bankruptcy law is
to minimize this problem.
Still, the reorganization law and particularly Chapter 11 are subject to many
attacks. First, reorganization law may favour the emergence of non viable …rms.
Kahl (2001) investigates the role played by Chapter 11 in the selection process. The
results suggest that …ling for Chapter 11 has a negative e¤ect on a …rm’s survival
chances; it leads to a longer process of …nancial distress and allows less viable …rms
to emerge from …nancial distress. Second, many empirical studies of corporate reorganization show that there are deviations from the absolute priority rule (APR).
Particularly, Chapter 11 often enables equity holders to obtain a share of the reorganized company’s value even when that value is not su¢ cient to cover debtholders’
claims [Franks and Torous (1989), Weiss (1990), Baird et al. (2007)].
4.2.2
Going-concern sale
The going-concern sale alternative relies on the market to address the problems of
excessive debt and illiquidity. The …rm is sold as a going-concern and transformed
into cash immediately available for the payment of debt according to the absolute
115
priority rule. Some scholars argue that this alternative is preferable because they
consider that a real sale would provide more accurate valuation of the …rm than
hypothetical prices …xed by the Court [Baird (1986), Easterbrook (1990)]. In addition, Baird and Morrison (2001) show that a regime of mandatory auctions is strongly
information forcing. It gives managers an incentive to make information available
and veri…able to potential buyers to preserve the …rm as a going-concern. Baird and
Rasmussen (2002; 2003) exhibit an overwhelming preference for sales over reorganization and go as far as to predict the disappearance of bankruptcy reorganization.
First, they argue that the majority of modern …rms have no going-concern value
due to the increasing standardization of assets and the increasingly service based
and information-based economy. Second, investors are now better able to anticipate
…nancial distress and elaborate accordingly more complex contracts that allocate
in advance control rights between the di¤erent players and eliminate the need for
reorganization. Third, the improvements in the market have made sales as a goingconcern increasingly possible.
Although the going-concern sales seem to be a good alternative to reorganization,
critics expressed doubts as to whether this alternative will move assets to their
highest-value use and whether it will always work well. On the one hand, Shleifer
and Vishny (1992) argue that auctions can have signi…cant costs to the extent that
the assets do not end up owned by the highest value user. Typically, if the shock that
causes the seller distress is industry or economic wide, other …rms in the industry
which would be the highest valuation potential buyers of these assets are likely to
have liquidity problems. On the other hand, Aghion et al. (1992) a¢ rm that auctions
work well if raising cash for bids is easy and there is plenty of competition among
several well-informed bidders. However, in most economies, these conditions may not
be met.
116
4.2.3
Empirical evidence
Little empirical research had been conducted either on the comparison between sales
and reorganizations to show the superiority of an alternative over the other or on the
determinants that in‡uence the choice between the two alternatives. Baird and Rasmussen (2003) compare cases that concluded in the 1980s with those that concluded
in 2002. The authors …nd that 88% of the large businesses entering Chapter 11 in
the 1980s emerge as operating companies whereas by 2002, the percentage had fallen
to 24%. Moreover, more than a third of these businesses (nine of twenty-three) were
prepackaged cases. LoPucki and Doherty (2007) test empirically Baird and Rasmussen’s assertion that reorganization is no longer a viable option by comparing
recoveries in bankruptcy sales of large public companies with the recoveries in the
bankruptcy reorganizations in the period 2000 through 2004. They found that the
choice between sale and reorganization has an impact on recoveries. Controlling for
the company’s earnings, the authors show that reorganized companies recover about
75% of their book value, compared to a 29% recovery ratio for acquired companies.
LoPucki and Doherty (2007) use these …ndings to prove the failure of going-concern
sales as an alternative to reorganization that remains essential for maximizing value.
In the French context, Blazy et al. (2011) compare recovery rates for each possible
outcome (liquidation, reorganization, and sale) for a large sample of French bankrupt …rms over the period 1995-2005.4 The results show that the average recovery
rate in reorganization cases is about 69% whereas this …gure in going-concern sales
is about 24%. These …ndings are close to LoPucki and Doherty (2007). In addition,
the authors …nd that recovery rates mainly depend on the situation of the …rm at
triggering.
4 See
supra note 2.
117
Another interesting study was conducted by Denis and Rodgers (2007). They
analyze the extent to which operation and …nancial characteristics are related to
the outcomes of Chapter 11 …lings. More precisely, they compare outcomes in pairs
across the three possible outcomes (reorganization, sale, liquidation). The regression
that compares the decision to reorganize to the decision to sell the assets as a whole
shows that …rms in more pro…table industries are more likely to emerge independent
than to be acquired. This result does not hold for weak …rms.5 Moreover, there is
some evidence that larger …rms and …rms that reduce their size are more likely to
emerge as independent …rms. The same study indicates that …nancial structure plays
an important role in the outcome of Chapter 11 …lings. Precisely, …rms that have
greater liabilities ratios prior to …ling Chapter 11 are more likely to reorganize than
to be acquired.6
4.3
Determinants of reorganization outcome
The choice of variables that would have an impact on the reorganization form in
France (continuation versus sale) is essentially based on prior research and on the
speci…cities of the French bankruptcy procedure. As mentioned previously, there
is little research conducted on the factors that would in‡uence the choice between
sale and continuation when reorganizing a bankrupt …rm. One possible explanation
lies in the design of the bankruptcy law around the world. In fact, contrary to the
French bankruptcy code that speci…es a procedure dedicated to going-concern sale,
the majority of the other bankruptcy laws provide bankrupt …rms with two main
procedures either reorganization as the same entity or liquidation.7
5 Firms
with negative operating margins in the lowest quartile of their industry are
classi…ed as weak …rms.
6 Liability ratio is measured as liabilities scaled by assets.
7 These procedures may involve some measures speci…c to going-concern sales.
118
To get around the lack of related research, we refer to some studies that investigate the factors a¤ecting sales outside bankruptcy. Indeed, we hypothesize that
the decision to acquire a bankrupt or a non-bankrupt …rm may be based on similar motivations. On the other hand, we refer to studies that focus on the choice
between reorganization and liquidation because some liquidation cases could involve
going-concern sales.
We examine in what follows the factors that may impact the reorganization form.
Some of these factors are not included in the empirical analysis due to data limitation. An overview of the variables’de…nitions and their expected signs is contained
in Table 1.
4.3.1
Factors included in the empirical analysis
Size
One can hypothesize that larger …rms are more likely to emerge as independent
entities because they are more likely to have su¢ cient resources to meet the …nancial
commitments of the continuation plan. Moreover, the incentive of banks to continue
to cooperate with a large …rm may be higher because larger companies are likely to
be clients with a better bank relationship (Rajan, 1992). The results of Denis and
Rodgers (2007) con…rm this hypothesis and show that larger …rms are more likely
to emerge as independent …rms. Finally, given that sales usually result in mass layo¤s, judges may be more inclined to order the continuation of cases involving many
employees to preserve employment. However, buyers may be interested in larger
…rms to grow quickly, to be more competitive, to get access to new markets and to
bene…t from the large clients portfolio of large …rms.
119
Consequently, one can expect a positive relationship between the number of
employees and the likelihood of con…rming a continuation plan whereas the relationship between the size (measured by total assets) and the reorganization outcome is
ambiguous.
Financial ratios
At …rst sight, it seems easier to …nd a buyer for …rms in better …nancial health.
Dewaelheyns and Van Hulle (2009) use the Altman Z”-score to measure the …nancial
distress.8 They …nd that companies with more severe …nancial di¢ culties are allowed
to stay in the procedure the longest. One explanation advanced by the authors is
that companies in better …nancial health should be easier to value and sell at an
acceptable price. A number of traditional …nancial ratios, such as pro…tability, liquidity and leverage can be used as proxies for the severity of the company’s …nancial
distress. Thus, if one predicts a positive relationship between going-concern sales
and the …nancial health of the bankrupt …rm, this would imply that the more profitable, the more solvent, and the less leveraged the bankrupt …rm is, the more likely
it will be acquired. However, the particularities of the French law and the fact that
the acquired …rm is a distressed one could o¤set the previous predictions. In fact,
the objectives of the reorganization procedure in France are …rst, saving the company, second, protecting jobs, and third, reimbursing the …rm’s debts. To the extent
that the …rm is enough pro…table to continue its operations, the judge may have a
preference for continuation over going-concern sale to preserve employment. Thus,
when the …rm is more pro…table, it has more chance to continue its operations as
the same entity. In addtion, when the …rm has severe liquidity problems, it would be
more di¢ cult to meet the …rst repayments …xed by the continuation plan especially
8 The
Z”-score weighs four …nancial ratios: (earnings before interest and taxes)/(total
assets), (book value of equity)/(total liabilities), (working capital)/(total assets), and
(retained earnings)/(total assets). Higher Z”-scores indicate stronger …nancial health.
120
when the …rm has an important amount of wage claims.9 Then, …ling companies
with higher liquidity ratio are more likely to continue their operations. Finally, …rms
that have a high level of leverage would have less free assets and therefore more
di¢ culties to convince creditors to …nance the operations of the …rm. Kruse (2002)
analyzes factors that are associated with higher incidences of asset sales by poorly
performing …rms. He …nds that …rms are more likely to sell assets if they are su¤ering
from low debt capacity. This view would predict that …ling companies with higher
leverage levels are more likely to be acquired.
Taking the speci…cities of bankruptcy and the French law into account, it could
be hypothesised that bankrupt companies with higher pro…tability, higher liquidity
ratio, and lower leverage ratio would be more likely to continue their operations as
the same entity.
Secured debt to assets ratio
The relation between how well-secured creditors are and their incentive to cooperate in a continuation or to push for a sale is complicated. Theory suggests that
secured creditors may have little incentive to cooperate even when total payments
to creditors would be higher in a continuation. If continuation occurs and the value
of the …rm increases, the secured creditors receive only part of the gains. But, if the
…rm’s value decreases, they will bear the future losses (Gilson and Stuart; 1995).
Moreover, well secured creditors are all the more incited to push for liquidation
because they are likely to be paid in full. Bergström et al. (2002) study the relation between the degree of creditor security and whether a reorganization plan is
con…rmed using a sample of 291 cases that …led under Finnish reorganization law.
The authors …nd a signi…cant relation between the likelihood of reorganization and
9 The
French law requires the repayment of some wage claims within 24 months after
the plan’s con…rmation.
121
a measure of creditors’security. Precisely, the more secured creditors are, the more
likely they oppose reorganization. Ayotte and Morrison (2009) analyze a sample of
large U.S. Chapter 11 cases. They …nd evidence of a secured creditor-driven …re sale
bias. Speci…cally, they report that cases are more likely to result in a sale when
secured creditors are oversecured than when the …rm has no secured debt or when
the creditors are undersecured.
Looking at the French bankruptcy law, creditors are not actively associated to
the reorganization process, whatever the nature of their claims. They don’t have the
right to participate in crafting the reorganization plan and do not vote on the plan.
Thus, the role played by the creditors in the bankruptcy process is ambiguous.
We calculate a secured debt to assets ratio. Secured creditors are better secured
when the ratio is lower, i.e., when the amount of assets is important relative to the
amount of secured debts.
Industry conditions
Schleifer and Vishny (1992) argue that the potential buyers of bankrupt …rms
are likely to be other …rms in the industry. Their model indicates that if the cause
of bankruptcy includes industry or economic conditions, the price of an asset in
liquidation might fall below value of best use because the potential industry buyers
have trouble to raise funds to buy the bankrupt …rm. Consistent with Schleifer
and Vishny (1992), Kruse (2002) …nds that …rms are more likely to sell assets if
their industry’s growth rate is higher. Thus, companies in stronger industries are
more likely to be sold than …rms with activities in struggling industries. Contrary
to the previous studies, Denis and Rodgers (2007) …nd that …rms in more pro…table
industries are more likely to emerge independent than to be acquired.
122
We include the average pro…tability of the bankrupt …rm’s industry as proxy for
the state of industry. Remaining industry e¤ects will be controlled for by industry
dummies.
Assets tangibility
Gilson et al. (1990) examine the determinants of …rms’ choice between formal
bankruptcy and out-of-court restructuring. They …nd that …rms with more intangible assets are more likely to complete a successful restructuring, arguing that the
higher bankruptcy costs associated with intangible assets provide better incentives
for creditors to renegotiate. Thorburn (2000) examines a sample of 263 small private
Swedish …rms …ling for bankruptcy between 1991 and 1998. The probability for a
going concern sale increases in the fraction of intangible assets because these assets
generate little value in a piecemeal liquidation. Anson (2007) describes intangible
assets as wasting assets particularly in liquidation scenario in bankruptcy. According
to the author, the valuation process of intangible assets in a bankruptcy context is
di¢ cult and complex. In the French context, the Court may have better incentives
to con…rm a continuation plan rather than a sale plan for …rms with more intangible
assets to preserve their value.
As a proxy for assets tangibility, we compute the average tangibility of the bankrupt …rm’s industry because the amount of tangible assets for the sample …rms was
not available.
Causes of default
In the French context, Blazy et al. (2011) introduced the causes of default among
the explanatory variables to determine the factors that a¤ect the probability of continuation and of sale, relative to the probability of liquidation.10 Although the causes
10 See
supra note 2.
123
of …nancial distress help little in explaining the Court’s decision, the study reveals
that measures undertaken by the Court may increase the probability of reorganization when they are connected to some particular causes. We believe that the causes
of default may also have an impact on the probability of continuation, relative to
the probability of sale in our study. For example, “…nancing”problems may increase
the probability of con…rming a continuation plan since this form of reorganization
results generally in debt rescheduling over many years. Moreover, descriptive statistics conducted in the previous Chapter suggest that there is a relationship between
the causes of default and the reorganization form.11
We collected the causes from the …les and we regrouped them into related reasons.
We developed seven groups:
- External business environment
- Strategy
- Management / Business operations
- Financing
- Outlets
- Accidental causes
- Personal causes
We associate each group of causes with a dummy variable which takes the value
1 if the debtor reported a reason among the group and the value 0 if not.12
4.3.2
Other factors not included in the empirical analysis
Given that the bankruptcy process in France is under the Court control, the reorganization form may di¤er according to the experience and/or the severity of the
11 See
Section 3.8 of Chapter 3 for a detailed description.
explaining which reasons were grouped into which categories are reported in
Appendix I.
12 Details
124
judge. Evans (2003) shows that judges’decisions regarding the exclusivity period are
correlated with the Chapter 11 outcome. In France, Blazy et al. (2011) …nd that the
proxy of the Court’s e¤orts to engage measures promoting reorganization has a large,
positive and statistically signi…cant e¤ect on the probability of reorganizing, over the
probability of liquidation.13 Similarly, the measures undertaken by the Court during
the observation period may in‡uence the form of the reorganization (continuation
or sale). It would also be interesting to include characteristics that are speci…c to
each alternative and to study the extent to which they in‡uence the form of reorganization such as the price o¤ered by potential buyers, the plan’s duration, and
the number of dismissals. Finally, specialized assets may increase the probability of
reorganization as the same entity, over the probability of sale (Baird and Morrison,
2005).
4.4
Data and sampling
4.4.1
Data sources and sampling procedure
The data in the present study are collected directly from documents …led in the
commercial Court of Paris (Tribunal de Commerce de Paris) during the 1995-2004
period. The district of Paris was selected since it has the highest business …lings
and for ease of access to the data.14 The choice of the 1995-2004 period was based
mainly on reforms timing to avoid the impact of a given reform on the reorganization
process.15
13 The
number of measures undertaken by the Court is a proxy for the restructuring
e¤orts of the Court.
14 About 11% of the French bankrupt …rms had …led in the commercial Court of Paris
during the study period.
15 The study period follows the reform of 1994 and precedes the reform of 2005.
125
The bankrupt …rms are selected based on a strati…ed random sampling design.
Precisely, the …rms are selected within two strata by simple random sampling. A …rst
sample of 350 cases is selected among the 1,718 cases that had led to the continuation
of the bankrupt …rm as the same entity. A second sample of 150 cases is selected
among the 829 cases that had led to the sale of the bankrupt …rm as a going-concern.
The number of …rms selected in each stratum was designed to re‡ect the proportion
of continuation and sale cases. However, missing data forced us to eliminate some
cases when performing regressions which results in unequal selection probabilities.
Thus, our sample design involves two features that may have potentially signi…cant
e¤ects on bias and variance: strati…cation and unequal weights. In the empirical
analysis, we used software procedures that take into account the survey sampling
design.
Some further remarks about data gathering should be made. First, data were
gathered manually from several documents: the bankruptcy declaration, the Court’s
decisions during the reorganization process, the list of claims, the report on the
business’s economic and employment situation, and the …nancial statements of the
…rm at the time of bankruptcy.16 Second, the study period includes the transition
to the Euro. Therefore, we converted data that were reported in Franc to Euro.17
Third, given that the study covers a ten-year period, all Euro values are expressed in
December 2004 Euro on the basis of a consumer price index. Finally, we used ALISSE
database to compute the average pro…tability of the bankrupt …rm’s industry.18 The
ALISSE database provides annual accounting data on an aggregated basis for each
economic activity sector. We classi…ed the sample cases among 114 categories de…ned
16 The
French names of these documents are: “déclaration de cessation des paiements,
jugement d’ouverture de la procédure de redressement judiciaire, jugement dé…nitif sur le
sort de l’entreprise, jugement de résolution du plan, état des créances, bilan économique
et social, bilan et état de résultat”.
17 We used the following rate to convert data from Franc to Euro: 1 euro = 6.55956 FF.
18 The access to ALISSE database is available at: www.alisse.insee.fr
126
by the NES classi…cation.19 Then, for each industry sector, we used the income
statement and the balance sheet data provided by ALISSE database to compute
annual industry pro…tability ratios.
4.4.2
Summary statistics
Table 2 presents summary statistics on the explanatory variables. Panel A reports
the sample’s industry composition. Data show that the majority of the …rms in the
sample perform in the “services”sector (60%) while 19% are in the “manufacturing”
sector and the remaining 21% of the cases are in the “trade” sector. This …nding
is not surprising and re‡ects the industrial base in Paris. Moreover, …rms in the
“manufacturing” and “trade” sectors are more likely to continue operations while
…rms in the “services” sector are more likely to be sold. Panel B displays the distribution of reorganized …rms by legal structure. It shows that most reorganized
…rms are incorporated businesses. In addition, about 16% of the cases that reorganize via continuation are …led by unincorporated structures while this …gure is only
about 9% for …rms that reorganize via sale. Panel C illustrates the causes of default
reported by the debtors by groups. There are three main related reasons for …ling
for bankruptcy, i) “external business environment”, ii) “internal operations of the
business”, and iii) “…nancing”. Finally, Panel D reports the mean and the median
of all continuous explanatory variables.20 Given that there is a number of extreme
values among the observations which may heavily in‡uence the statistical results,
the continuous variables were truncated at the 1st and the 99th percentile to reduce
the impact of outliers.
19 The
NES (Nomenclature Economique de Synthèse) classi…cation is the French Aggregated Economic Classi…cation and it is comparable to the SIC (Standard Industry Classi…cation) in the U.S.
20 See Chapter 3 for a detailed description of the sample …rms.
127
4.5
4.5.1
Empirical implementation
Logistic Regression Model
We use a logistic regression model to analyze the e¤ect of the explanatory variables on the type of reorganization procedure. The dependent variable in the logistic
regression model is Y, where Y=1 if the bankrupt …rm keeps operating as the same
entity (continuation) and where Y=0 if the bankrupt …rm is acquired by another
entity as a going-concern (sale). The logistic regression model uses a cumulative
standard normal distribution function to convert the values of explained variables
into probability values. The logistic probability function can be expressed as below:
0
pj = Pr(yj = 1jxj ) =
exj
(4.1)
0
1 + exj
where pj is the probability of reorganizing a bankrupt …rm j,(j = 1; : : : ; n),
through the framework of a continuation, xj is a vector of explanatory variables that
determine the reorganization form of the j th …rm and
is a vector of coe¢ cients to
be estimated.
Taking the product of the probabilities in equation (4.1) over all n …rms yields
the likelihood function:
L( ) =
n
Q
[Pr(yj = 1jxj )]yj [1
Pr(yj = 1jxj )]1
yj
(4.2)
j=1
Estimates of the parameter
may be obtained by maximising the logarithm of
the likelihood function:
ln L( ) =
P
j2S
ln F (xj ) +
P
j 2S
=
ln f1
F (xj )g
(4.3)
where S is the set of all observations such that yj 6= 0 and F (z) = ez =(1 + ez ):
128
Accounting for the sample design in the analysis:
Estimates obtained from the previous speci…cation ignore survey design features
and assume that the data are drawn from a simple random sample. Kreuter and
Valliant (2007) show that survey weights as well as information on strati…cation
and clustering should be taken into account. In fact, omitting them runs the risk
of biased point estimates and erroneous standard errors. These erroneous estimates
a¤ect the validity of resulting con…dence intervals or tests of statistical signi…cance.
If we take into account the sample design in the logistic model regression, estimates of the parameter
would be obtained by maximising the logarithm of the
following pseudo-likelihood function:
ln L( ) =
P
wj ln F (xj ) +
j2S
P
j 2S
=
wj ln f1
F (xj )g
(4.4)
where S is the set of all observations such that yj 6= 0, F (z) = ez =(1 + ez ), and
wj is a sampling weight.
4.5.2
Testing signi…cance of the coe¢ cients
We used two test statistics to check the signi…cance of the coe¢ cients depending on
the assumption made about the sample design.
Case 1: Logistic model under iid-based sampling
Under the null hypothesis H0 :
i
z^ i =
= 0, it can be shown that for i = 1; :::; k,
^i
SEi
N (0; 1)
(4.5)
where k is the number of regression parameters and SEi is the standard error
based on variance estimator given by the inverse of the negative Hessian (second
dervatives) matrix.
129
Case 2: Logistic model with complex survey data
Under the null hypothesis H0 :
= 0, it can be shown that if for i = 1; :::; k,
i
^
t^ i =
t(g
i
SEil
s)
where SEil is the standard error based on the linearized variance estimator given
by a …rst-order Taylor series linear approximation, g is the total number of sampled
clusters, and s is the number of strata.21
4.5.3
Testing joint signi…cance
There are two ways to test the joint null hypothesis H0 :
q
= 0; where q < k with q
the number of restrictions imposed under the null hypothesis. One way is to perform
a Wald test that depends only on the estimate of the covariance matrix. The Wald
test statistic is de…ned as follows:
W = (R
r)0 (RV R0 ) 1 (R
r)
(4.6)
If the model is estimated based on iid-sample assumption, a chi-squared distribution with q degrees of freedom, is used for computation of the signi…cance level of
the hypothesis test.
If the model takes into account the survey design, the following adjusted-F statistic is used:
Wc = (f
q + 1)W=(qf )
(4.7)
where W is the Wald test statistic, q is the dimension of the hypothesis test, and
f is the number of sampled clusters minus the number of strata. An F -distribution
21 In
the present study, g=n because there is no clusters in the sample design.
130
with q numerator degrees of freedom and (f
q + 1) denominator degrees of freedom
is used for computation of the signi…cance level of the hypothesis test.
An alternative test of the null hypothesis, when the data are collected from simple
random sample, is to perform a likelihood ratio test. Under the null hypothesis,
the following test statistic (LR) follows a chi-square distribution with q degrees of
freedom:
LR =
"
L( ^ M LE )reduced
2 ln
L( ^ M LE )f ull
#
(4.8)
where:
L( ^ M LE ) = the likelihood under the model evaluated at
the maximum likelihood estimates of :
The reduced model in this case is the model excluding the q regression parameters
to be tested, while the full model is the model including the q regression parameters.
In models with complex survey design, the “likelihood”which is used to compute
the point estimates does not re‡ect the distribution of the sample; that is why tests
based on the likelihood should not be used.
4.5.4
Goodness-of-…t of the model
After a logistic regression model has been …tted, the overall goodness-of-…t of the
model is tested. While various goodness-of-…t tests have been proposed and implemented under iid-based sampling, few tests have been developed and implemented
in available software when data are collected using complex sampling design. A commonly used test of goodness-of-…t for simple random samples of data is the Hosmer
and Lemeshow (2000) test. Later, this test has been extended to complex sample
survey design [Archer and Lemeshow (2006), Archer et al. (2007)].
131
The Hosmer and Lemeshow test
The idea behind this test is that under the null hypothesis, the observed frequencies are not signi…cantly di¤erent from those predicted by the model. When there
are continuous predictors in the model, a common practice is to sort observations
in increasing order of their expected probability. Then, the observations are divided
into “g”equal sized groups. The H-L goodness-of-…t statistic is calculated using the
observed and expected frequencies. It is de…ned as follows:
g (o
P
nk
k
C^HL =
k=1 nk k (1
2
k)
(4.9)
k)
where nk is the total number of observations in the k th group, ok is the number
of responses (yj = 1) among the covariate patterns in the k th group, and
k
is the
average estimated probability in the k th group.
The H-L statistic is then compared to a chi-square distribution with (g
2)
degrees of freedom. Large values of C^HL (and small p-values) indicate a lack of …t
of the model.
The Arsher and Lemeshow test
The A-L procedure is a modi…cation of the standard H-L test that takes the
sampling weights and the strati…cation and the clustering features of the sample
design into account when comparing the observed and expected frequencies. Observations are sorted into deciles based on their estimated probabilities, and each decile
of risk includes approximately equivalent total sampling weights. The A-L statistic
for testing the g categories is de…ned as follows:
^ AL = f
W
g + 2 ^ 0 n^ ^ 1 o ^
M V (M )g g M
fg
(4.10)
132
^ = (M
^ 1; M
^ 2 ; :::; M
^ 10 ) is the estimate of the mean residuals by decile of
where M
^ ) is the associated estimated variance-covariance matrix which is obtained
risk, V^ (M
using linearization.
The A-L statistic is approximately F -distributed with (g
of freedom and (f
1) numerator degrees
g + 2) denominator degrees of freedom, where f is the number
of sampled clusters minus the number of strata and g is the number of categories
included in the hypothesis test (here, g = 10 corresponding to deciles of risk). Large
^ AL (and small p-values) indicate a lack of …t of the model.
values of W
4.6
Empirical results
Table 3 displays the results estimated by logistic regression models. These models
describe the relationship between the explanatory variables and the probability
of reorganizing a bankrupt …rm via a continuation plan rather than a sales plan.
Precisely, a positive (negative) regression coe¢ cient means that an increase in the
explanatory variable increases (decreases) the probability of a continuation.
Overall, we examined eight speci…cations and estimated sixteen models. In fact,
we developed two models for each speci…cation: the …rst model assumes that individual observations are independent and identically distributed and the second model
takes into account the survey design.
Table 3 reports the estimated coe¢ cients, the standard errors and the statistical
signi…cance of each coe¢ cient, and the number of observations. One should note
that the standard errors and the statistics used to test the signi…cance of the coe¢ cients are computed di¤erently according to the hypothesis assumed on the sample
design. Moreover, log-likelihood chi-square statistic, Hosmer-Lemeshow goodness-of…t statistic, AIC and BIC criteria are shown for models based on iid-observations.
These tests should not be used for models with complex survey design because the
133
pseudo-likelihood does not re‡ect the distribution of the sample. Thus, we used the
F-statistic instead of likelihood ratio statistic. We also used the Archer-Lemeshow
test instead of the Hosmer-Lemeshow test. Contrary to the H-L test, the A-L test
show small p-values indicating a lack of …t for all models.22 We are doubtful of the
adequacy of this test to our sample design. In fact, Archer et al. (2007) recommend
the A-L test for testing goodness-of-…t for data collected using complex sampling
design, particularly when the number of sampled clusters is large. In our sample,
there is no cluster which may explain the obtained results.
Overall, the comparison between the two types of models shows small changes
both in the coe¢ cients and in the standard errors because of the sample design. In
what follows, we present a detailed description of the di¤erent models presented in
Table 3.
In the …rst speci…cation, we introduce only basic company-speci…c variables and
we investigate their impact on the reorganization form. We include the following
variables: total assets, employees, pro…tability ratio, liquidity ratio, leverage ratio,
and we control for the …rm’s type. The results in columns (1) and (1’) show that
the coe¢ cients on total assets and on pro…tability ratio have the predicted signs
and are statistically signi…cant. On the one hand, the larger the bankrupt …rm
is, the more likely it will be acquired by another …rm. This result suggests that
potential buyers are interested in large bankrupt …rms. In fact, the value of most
assets is usually underestimated in the bankruptcy context which makes them more
attractive for potential buyers. On the other hand, the more pro…table the business
is, the more likely a continuation plan will be con…rmed. This result is consistent
with the objectives of the bankruptcy law which encourages the reorganization of the
…rm via continuation if it can keep operating and the claims can be reimbursed.23
22 The
23 See
A-L goodness-of-…t statistic is not shown in Table 3.
L621.70 under the old commercial Code (2005).
134
Contrary to our predictions, the coe¢ cient on employee’s variable is signi…cantly
negative. Thus, when the number of employees increases, the bankrupt …rm has less
chance to continue its operations as an independent entity. One possible explanation
lies in the fact that the number of employees could be a proxy for the size of the
bankrupt …rm and therefore re‡ects its importance as a target for potential purchasers. The results also suggest that unincorporated …rms are more likely to be
acquired than incorporated ones. The coe¢ cient on liquidity ratio is signi…cant only
in (1’).
Contrary to Denis and Rodgers (2007), the leverage ratio does not have an impact
on the …nal outcome in both models (1) and (1’). Therefore, we dropped leverage
ratio variable in the second speci…cation and compare the models (1) and (2), on
one side, with models (1’) and (2’) on the other side. Based on the likelihood ratio
test, AIC, and BIC, it seems that model (2) is preferred to model (1). The results
also show that the coe¢ cient on liquidity ratio is no longer signi…cant in model (2’).
Thus, we dropped the liquidity ratio variables in the third speci…cation. The results
are reported in columns (3) and (3’). The coe¢ cients on all variables are signi…cant
and keep the same signs as in the previous speci…cations. The Hosmer-Lemeshow
test shows that the model (3) has a better …t than the previous models (1) and
(2). In addition, the removal of the liquidity ratio variable leads to the increase of
the number of observations from 186 to 280 observations. Consequently, the third
speci…cation is the one to merit further consideration.
In the next speci…cation, we add secured debt to assets ratio to investigate the
relation between how well-secured creditors are and the reorganization form. Speci…cally, the higher the value of the secured debt to assets ratio is, the less secured creditors are. The estimation results of the fourth speci…cation are reported in columns
(4) and (4’). They show a negative and signi…cant relationship between the secured
debt to assets ratio and the likelihood of con…rming a continuation plan. In other
135
words, the less secured the creditors, the less likely the bankrupt …rm will continue
its operations as the same entity. This result is not consistent with theory and previous empirical studies. For example, Bergström et al. (2002) …nd that the more
secured creditors, the less likely they would encourage reorganization in the Finnish
case. Ayotte and Morrison (2009) …nd that Chapter 11 cases are more likely to result
in a sale when secured creditors are oversecured than when the …rm has no secured
debt or when the creditors are undersecured. In the French context, it seems that
secured debt can present an obstacle to the con…rmation of a continuation plan when
its amount becomes important relative to the assets of the bankrupt …rm because
creditors are no longer motivated to …nance the operations of the …rm.
We turn now to study the impact of industry outlook on reorganization outcome.
We add industry pro…tability ratio measured at the year during which the plan
was con…rmed as well as industry dummy variables for manufacturing, trade, and
services. The coe¢ cients on dummy variables are not signi…cant and are not reported
in columns (5) and (5’). The coe¢ cient on the industry pro…tability ratio is not
signi…cant either ignoring or including the sample design. This result is not consistent
with previous studies [Schleifer and Vishny (1992), Kruse (2002), Denis and Rodgers
(2007)] and may suggest that industry conditions do not in‡uence reorganization
form in France. It may also indicate that the proxy used for industry conditions
is not relevant. The comparison of the full models (5) and (5’) with the reduced
models (4) and (4’), respectively, shows that we can remove industry pro…tability
ratio and industry dummy variables because their introduction does not result in a
statistically signi…cant improvement in models …t.24
In the sixth speci…cation, we take a closer look at the impact of industry tangibility on the reorganization form. This latter is obtained by adding industry tan24 We
used likelihood-ratio test to compare the models (5) and (4) and Wald test to
compare the models (5’) and (4’).
136
gibility ratio to the fourth speci…cation. As expected, columns (6) and (6’) report
a negative and signi…cant relationship between the tangibility ratio and the probability of con…rming a continuation plan. The …rm is more likely to be sold if the
…rm is active in an industry with more tangible assets.
The next models reported in columns (7) and (7’) build on the previous speci…cation but introduce the reasons for …ling for bankruptcy. Each group of similar causes
of default is represented by a dummy variable. The results show that some causes
of default may have a signi…cant e¤ect on the reorganization form. Precisely, …rms
su¤ering from “personal problems” are more likely to be sold whereas …rms having
“…nancing”and/or “business operations and management”problems are more likely
to continue their activity in the same entity. Not surprisingly, many companies
remain dependent on their owners. When this latter can no longer run the business,
the Court may have no option but to order the sale of the …rm. It is also reasonable
to expect that businesses encountering “…nancing” problems will reorganize in the
same entity since the continuation plan would generally extend the maturity of the
debt contract and/or reduce its amount and, therefore, would resolve the …nancing
problems of the …rm. Finally, the fact that “business operations and management”
problems increase the probability of con…rming a continuation plan raises an interesting question. Is it reasonable to expect that …rms whose managers encounter
business and management problems will continue their operations e¢ ciently with
these same managers? In fact, the French system leaves the manager with signi…cant control during the bankruptcy proceedings. Thus, for debtors employing less
than 50 persons or having an annual turnover below e3,100,000, which is the case of
most …rms in bankruptcy, the appointment of a supervisor is not mandatory during
the observation period, and even in cases where the Court appoints a supervisor,
the mission of this latter is usually limited to the supervision or the assistance of
the debtor and rarely, it recommends the substitution to the manager. In addition,
137
when a continuation plan is con…rmed, the old manager is generally not replaced
and he continues to manage the …rm during the implementation of the plan.
In the …nal speci…cation, we control for year e¤ects. The coe¢ cients on years’
dummy variables are not signi…cant except for 2004 and are not reported in columns
(8) and (8’).
4.7
Conclusion
This chapter complements a growing literature on the reorganization of bankrupt
…rms. The study contributes to a better understanding of the factors that a¤ect
the reorganization form in the French context (continuation versus sale as a goingconcern). The empirical analysis shows the importance of several factors.
First, the results indicate that larger …rms are more likely to be acquired. Buyers
may be interested in larger …rms to grow quickly, to be more competitive, to get
access to new markets, and to bene…t from the large clients portfolio of large …rms.
They may o¤er an interesting price that makes a sale more attractive than a continuation. Moreover, the Court may face a real dilemma when a large …rm cannot
continue its operations and includes many employees. In such conditions, it may
prefer ordering the sale of the bankrupt …rm instead of liquidating it to avoid job
losses.
Second, the study reveals that …rms that are more pro…table are more likely to
emerge as independent entities. Thus, sale alternative is chosen in the less favorable
cases, i.e. when the …rm is unable to generate su¢ cient cash ‡ow to reimburse its
creditors which is consistent with the objectives of the French bankruptcy law.
Third, we …nd that the less secured the creditors, the less likely the bankrupt
…rm will continue its operations as the same entity. This is the opposite of what one
may …nd if creditors were actively associated to reorganization process.
138
Fourth, the study shows that the probability for a reorganization in the same
entity increases in the fraction of intangible assets in the …rm’s industry because the
value of these assets may be dissipated in sales.
Finally, the results provide strong support for the importance of the causes of
default in determining the reorganization form. Particularly, …rms su¤ering from
“personal problems” are more likely to be sold whereas …rms having “…nancing”
and/or “business operations and management”problems are more likely to continue
their activity in the same entity.
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Natural logarithm of the number of employees measured at the year F-1
(Earnings before interest and taxes)/(total assets) measured at the year F-1
(Current assets)/(current liabilities) measured at the year F-1
(Total liabilities)/(total assets) measured at year F-1
(Secured claims)/(total assets) measured at the year F-1
Industry average of the return on assets measured at the year in which the reorganization plan was confirmed
(based on the NES 114 level)(a)
Industry average of the tangibility ratio measured at the year in which the reorganization plan was confirmed
(based on the NES 114 level)(b)
Dummy variable, equal to 1 if the firm is an unincorporated company
Dummy variables for "manufacturing", "trade", and "services"
Dummy variables for "external business environment", "strategy", "management/business operations"
"financing", "outlets", "accidental causes", and "personal causes"
Employees
Profitability Ratio
Liquidity Ratio
Leverage Ratio
Secured debt /assets
Industry Profitability
Industry Tangibility
Firm's Type
Industry dummies
Causes of default dummies
(CD)
(b)
(a)
Dummy variables for the year in which the reorganization plan was confirmed
Tangibility ratio is measured as tangible assets scaled by the total amount of assets.
Return on assets is defined as the operating income before depreciation and amortization over total assets.
Year dummies
Natural logarithm of total assets measured at the year prior to filing (year F-1)
Total Assets
Dummy variable, equal to 1 if the cause of default reported by the debtor is among the group
Definition
Variables
Table 1 : Definition of the Explanatory Variables and Expected Signs
-
+/-
+/-
-
+
+
+
+/-
Exp. Sign
144
Table 2 : Summary Statistics
Panel A : Distribution of Reorganized Firms by Industry
Variables
Reorganization
Continuation
Sale
19.23%
20.30%
60.47%
19.75%
21.24%
59.01%
17.83%
17.83%
64.34%
Manufacturing
Trade
Services
Panel B : Distribution of Reorganized Firms by Legal Structure
Variables
Reorganization
Continuation
Sale
Incorporated
85.92%
83.62%
91.28%
Unincorporated
14.08%
16.38%
8.72%
Panel C : Listed Causes of Default by Reorganization Form and Grouping
Variables
External Business Environment
Strategy
Management
Financing
Outlets
Accidental Causes
Personal Problems
Reorganization
Continuation
Sale
61.17%
11.28%
44.25%
42.95%
19.52%
29.28%
8.24%
62.65%
8.64%
45.06%
47.83%
18.51%
33.64%
6.48%
57.66%
17.51%
42.33%
31.38%
21.89%
18.97%
12.40%
Panel D : Explanatory variables by Reorganization Form
Variables
N
Mean
Continuation
Median
Sale Continuation
Sale
Number of employees
478
11.82
24.08
4
7
Total assets (K€)
302
1048.00
2163.35
298.471
547.26
Total debts (K€)
302
1096.58
2200.82
421.94
798.86
Profitability ratio
293
-0.14
-0.30
-0.06
-0.26
Liquidity ratio
329
-0.33
0.28
0.16
0.13
Total debts / Total assets
302
1.70
1.52
1.31
1.26
Secured debt / Total assets
268
0.96
0.96
0.70
0.75
Industry profitability
420
0.09
0.09
0.10
0.10
145
Table 3 : Determinants of the Form of Reorganization (Continuation vs Sale as going-concern)
Variables
(1)
(1')
(2)
(2')
(3)
(3')
Total assets
-0.5872***
(0.2079)
-0.5872***
(0.1973)
-0.6849***
(0.1955)
-0.6861***
(0.1800)
-0.3755**
(1.473)
-0.3825***
(0.1364)
Employees
-0.5029***
(0.1845)
-0.5036***
(0.1891)
-0.4724***
(0.1808)
-0.4712***
(0.1811)
-0.3431**
(0.1463)
-0.3468**
(0.1419)
Profitability Ratio
1.4315***
(0.5268)
1.4358**
(0.6964)
1.0771***
(0.4098)
1.0749**
(0.4653)
0.8682***
(0.3137)
0.8636***
(0.3156)
Liquidity Ratio
0.6180
(0.4697)
0.6369*
(0.3455)
0.4780
(0.4631)
0.4923
(0.3313)
Leverage Ratio
0.4868
(0.3684)
0.4994
(0.3671)
Firms' type
-2.1140***
(0.7025)
-2.1131***
(0.7161)
-2.0673***
(0.6946)
-2.0617***
(0.6775)
-0.9437*
(0.4987)
-0.9485**
(0.4779)
Intercept
1.1335
(0.6077)
1.0241
(0.5454)
1.6527
(0.4770)
1.5553
(0.4191)
1.5690
(0.3837)
1.3640
(0.3340)
N
Chi-square-statistic
F-statistic
AIC
BIC
HL
186
49.23***
186
186
47.65***
186
280
280
Secured debt / Assets
Industry Profitability
Industry Dummies
Industry Tangibility
CD1: External environment
CD2: Strategy
CD3: Management/Business
CD4: Financing
CD5: Outlets
CD6: Accidental causes
CD7: Personal causes
Year dummies
6.46***
1.043
-755.405
0.1999
8.39***
1.039
-764.513
0.1727
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
Standard errors in parentheses
1.087
-1255.286
0.4994
146
Table 3 : Determinants of the Form of Reorganization (Continuation vs Sale as going-concern) - continued
Variables
(4)
(4')
(5)
(5')
(6)
(6')
Total assets
-0.5835***
(0.1757)
-0.6157***
(0.1622)
-0.6518***
(0.2098)
-0.6729***
(0.1961)
-0.6145***
(0.2109)
-0.6231***
(0.1967)
Employees
-0.3295**
(0.1634)
-0.3291**
(0.1636)
-0.3022
(0.1851)
-0.3069
(0.1917)
-0.3159
(0.1906)
-0.3318
(0.2091)
Profitability Ratio
0.6615*
(0.3483)
0.6632*
(0.1811)
0.7295*
(0.3823)
0.7045*
(0.3991)
0.7702**
(0.3920)
0.7308*
(0.4338)
Firms' type
-0.8991
(0.5660)
-0.9038
(0.5749)
-0.1989
(0.7536)
-0.2758
(0.8374)
-0.1561
(0.7384)
-0.1910
(0.7801)
Secured debt / Assets
-0.3194*
(0.1642)
-0.3360*
(0.1811)
-0.5022**
(0.2204)
-0.4832**
(0.2046)
-0.4508**
(0.2295)
-0.4273**
(0.2053)
Industry Profitability
-3.6758
(4.6046)
-3.8077
(4.0421)
Industry Dummies
YES
YES
-3.0520**
(1.5055)
-2.9380**
(1.3735)
Liquidity Ratio
Leverage Ratio
Industry Tangibility
CD1: External environment
CD2: Strategy
CD3: Management/Business
CD4: Financing
CD5: Outlets
CD6: Accidental causes
CD7: Personal causes
Year dummies
Intercept
1.7999
(0.4294)
1.3810
(0.3815)
2.7669
(0.7585)
1.6992
(0.6831)
2.4806
(0.5689)
1.9442
(0.5663)
N
Chi-square-statistic
F-statistic
AIC
BIC
HL
243
35.89***
243
210
33.69***
210
210
35.68***
210
7.11***
1.010
-1068.36
0.0794
3.52***
0.991
-879.352
0.8236
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
Standard errors in parentheses
5.03***
0.960
-897.830
0.3877
147
Table 3 : Determinants of the Form of Reorganization (Continuation vs Sale as going-concern) - continued
Variables
(7)
(7')
(8)
(8')
Total assets
-0.7242***
(0.2317)
-0.7237***
(0.2022)
-0.7572***
(0.2471)
-0.7632***
(0.2122)
Employees
-0.2670
(0.2057)
-0.3017
(0.2194)
-0.2289
(0.2177)
-0.2568
(0.2228)
Profitability Ratio
0.8299**
(0.3925)
0.8314**
(0.3577)
0.8502**
(0.4162)
0.8181**
(0.3554)
Firms' type
0.0430
(0.7803)
-0.0795
(0.9159)
0.1683
(0.8008)
0.0529
(0.9462)
Secured debt / Assets
-0.5979***
(0.2364)
-0.5697***
(0.2112)
-0.6304**
(0.2545)
-0.5952***
(0.2318)
Industry Tangibility
-2.5393
(1.7118)
-2.6565*
(1.4796)
-2.7343
(1.8595)
-2.8042*
(1.6506)
CD1: External environment
-0.0448
(0.4047)
-0.0698
(0.3961)
-0.1931
(0.4426)
-0.1937
(0.4148)
CD2: Strategy
-0.7824
(0.6243)
-0.7873
(0.5745)
-0.7861
(0.6632)
-0.7484
(0.5913)
CD3: Management/Business
0.9603**
(0.4728)
0.8785*
(0.4846)
1.1771**
(0.5138)
1.0296*
(0.5346)
CD4: Financing
0.7647*
(0.4772)
0.7423*
(0.4091)
0.9477**
(0.4691)
0.9337
(0.4237)
CD5: Outlets
-0.3597
(0.5158)
-0.3561
(0.4874)
-0.2853
(0.5725)
-0.3835
(0.5392)
CD6: Accidental causes
0.0674
(0.4998)
-0.0457
(0.5268)
0.2805
(0.5430)
0.1704
(0.5350)
CD7: Personal causes
-1.3134*
(0.7095)
-1.3376*
(0.7124)
-1.2097*
(0.7362)
-1.2501*
(0.7189)
yes
yes
Liquidity Ratio
Leverage Ratio
Industry Profitability
Industry Dummies
Year dummies
Intercept
2.0463
(0.7269)
1.6680
(0.7172)
2.6062
(1.2366)
2.3580
(0.9201)
N
Chi-square-statistic
F-statistic
AIC
BIC
HL
210
50.71***
210
210
58.31***
210
3.01***
0.955
-875.435
0.8256
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
Standard errors in parentheses
1.93***
1.014
-829.563
0.9735
148
APPENDIX I: Stated Reasons for Filing : Groupings
External Business environment
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Bad economy
Competition
Decrease of prices
Increasing cost of doing business (raw materials, labor costs)
Increasing rent
Exchange rate
Technological revolution
Legislation (increase in VAT / new law / prefectorial authorization etc.
Problem related to the customer behavior
Bankruptcy of a subcontractor
Difficulties encountered by the subsidiary or the main branch are extended to the firm
Reputation needs costs and time
Inability to find skilled personnel / the firm is understaffed
Declining sales
Strategy
15
16
17
18
19
20
21
22
23
24
25
26
Takeover of a bad business
Failure of activity expansion
Failure of diversification
Expensive merger
The activity depends strongly on a specific sector or market
Overinvestment
Disinvestment from some projects
Continuation of an unprofitable business
Costly relocation
Location was bad
Large royalties
Problems related to lease-management
Management / Business operations
27
28
29
30
31
32
33
34
35
36
37
Bad management / inexperience
Problem related to management control
Time devoted to management is insufficient
Conflict between business partners concerning management
Excessive takings from receipts by management
Hard startup
Difficulties to realize a project / failure of an important project
Organizational problems
Slow implementation of new measures
Lack of dynamism and adaptation
Absence of an IT department
149
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Weak account reporting
The activity is not profitable
Operating loss
High costs compared to firm’s activity
Wage and social claims are too high compared to firm's activity
Problems related to bad predictions
Underestimation of the sector crisis
Bad evaluation of cost price
Bad evaluation of costs
Stock management
Over-sizing of production capacity
Problem with personnel
Unskilled personnel
Departure of critical personnel
Financing
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
High debt service
Banks refuse to support the firm
Bank overdraft is too high
Bank account is blocked due to bank restructuring
Excessive support of banks
Shorter delays on account receivable
Cash flow problem
Liquidity problems resulting from the dismissal of many workers
Absence of working capital
Increase in working capital requirement
Lack of equity
Problems related to the financing of restructuring measures
Financial structure
Bankruptcy of a shareholder
Old debts taken on at business purchase
Delay in payment / nonpayment by clients
Outlets
68
69
70
71
72
73
74
75
76
77
78
Bad quality of products
Obsolete products
Products lack diversity
Problems related to commercial strategy
Failure of a new commercial organisation
Difficulty to commercialize firms’ products
Marketing positioning
Concentration of retailing
Loss of important clients
Bankruptcy of important clients
Clients’ merger
150
Accidental Causes
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
War / attacks
Strikes
Weather related problems
Road work
Problems related to neighbours
Departure of many firms from the district
Robbery / fire / cow disease etc.
Defective installation
Temporary closing of the firm
Goods’ blocking through customs
Port’s closing
Conflict with a partner
Problems encountered with lessor
Important condemnation pronounced by the French industrial tribunal
Tax adjustment / Penalties due to delay in payment of tax and social claims
High compensation related to lease-purchase contract
The factor did not pay the firm
Personal problems
96
97
98
Medical problems / death of the manager
Family problems
Personal bankruptcy
Chapter 5
Do Continuation Plans Succeed in France?
5.1
Introduction
From the viewpoint of Courts or policymakers, two events must happen in sequence
for a …rm to emerge successfully from …nancial reorganization. First, the Court must
con…rm the plan. Second, the plan must be consummated, that is, all required distributions and provisions of the plan must be completed. It is obvious that the
consummation of the plan is most di¢ cult than its con…rmation because the plan
may promise creditors more than the debtor can repay after con…rmation. There
are at least two impediments to the plan’s consummation. First, there is an extensive literature indicating that the bankruptcy reorganization procedure allows some
ine¢ cient …rms to reorganize when they should have been liquidated [White (1994),
Mooradian (1994), Fisher and Martel (1995, 2004)]. Second, there is also uncertainty
associated with the plan’s implementation [Jensen-Conklin (1992), Baldiga (1996)].
In France, the objectives of the reorganization procedure are, in chronological
order, to maintain the …rm’s activity, to preserve employment, and last to reimburse debts. This order suggests that the priority is given to the continuation of
the …rm’s activity rather than the repayment of creditors. Another important fea-
151
152
ture of the French bankruptcy law is that creditors are not actively associated to
the reorganization process. First, they do not vote on the reorganization plan and
cannot veto it. Second, the Court may extend the maturity of the loans without
creditors’ approval. The French Code, with its explicit predisposition to allow the
reorganization of ine¢ cient …rms raises an important question about the feasibility
of the con…rmed plans.
Little research has been conducted on the consummation of reorganization plans,
particularly in the French context. To our knowledge, the only study reporting the
rate of success of the reorganization plans in France was conducted by Germain
and Frison-Roche (1993). However, this study did not attempt to build a statistical analysis, but rather simply examined relationships between the outcome of the
reorganization process and several individual variables.
The object of this chapter is to address this lack of data and to provide new
evidence on …rms in reorganization in France. Speci…cally, it reports on and analyzes
the results of a study conducted into the consummation of continuation plans at a
particular bankruptcy Court in France. The purpose of the study is twofold. First,
it determines the consummation rate of con…rmed plans. Second, the study provides
a statistical model that, on the one hand, identi…es factors indicative of successful
consummation and, on the other hand, predicts a plans’likelihood of success.
The remainder of the chapter is organized as follows: the next section presents a
review of previous research examining reorganization plans’consummation. Section
5.3 describes the data set and measures the consummation rate. It also presents some
descriptive statistics and compares characteristics of …rms that have their plans
consummated to those that fail. Section 5.4 discusses the potential determinants
that may in‡uence the probability of plans’consummation. Section 5.5 presents the
empirical analysis. We used the logistic estimation to assess the probability of success
of a continuation plan. Then, we used a holdout procedure to assess the predictive
153
accuracy of the obtained model. The …nal section of the chapter contains a summary
and some concluding remarks.
5.2
Plan’s consummation: prior research
Although information about plan’s consummation may be of interest to bankruptcy
practitioners and policymakers, little research has been conducted on consummation
rates and on the factors determining the success of a reorganization plan. According
to Baldiga (1996), this lack of research is due to the absence of a system to monitor
cases.
One of early studies of plan consummation was performed by Jensen-Conklin
(1992). This latter examined all Chapter 11 cases …led in the Southern District of
New York in Poughkeepsie during the 1980 to 1989 period. The author …nds that 58%
(26 plans) of the con…rmed plans (46 plans) are de…nitely or probably consummated
plans.1 Of these, approximately 38% included liquidating plans. The study reveals
that, in the …nal count, a Chapter 11 debtor has only 6.5% chance of con…rming and
consummating a plan as well as surviving as a rehabilitated entity post-con…rmation.
Moreover, Jensen-Conklin (1992) investigated the factors regarding the likelihood of
a plan’s consummation.2 For the author, factors associated with a plan that will likely
consummate include a liquidating plan, the presence of a creditors’committee in the
case, a plan payout of one year or less and the size of the case.3 Another study on
plan consummation in the U.S. was conducted by Baldiga (1996). More precisely, the
author focused on the consummation rate of 47 plans surviving an actual challenge
to feasibility during the Court con…rmation process and investigated whether these
1 Plans
comprising the “probably consummated”class were cases where the information
documenting full compliance was indirect or obtained through secondary sources.
2 Jensen-Conklin (1992) examined …rst order correlations and did not build a classi…cation model.
3 The larger debtors are more likely to consummate a plan.
154
plans are more likely to succeed. The data indicate that only 25.6% of the sample
represents con…rmed, non-liquidating plans which were fully consummated.4 The
author concluded that the additional scrutiny of the feasibility challenge did not
result in an improved consummation rate.
Canadian data provide a di¤erent picture. Fisher and Martel (1995, 1999, 2011)
estimated the consummation rate of con…rmed reorganization plans in Canada. Their
…rst study shows that 81% of the proposals con…rmed by the Court are consummated. The consummation rate is around 72% in the following studies. In addition,
a debtor …ling for reorganization in Canada has 59.13% chance of con…rming and
consummating a plan in the …rst study. This rate is equal to 50.4% in the second
study and 57.84% in the third study. These rates are roughly eight times higher than
cases in Chapter 11.
More recent studies on plan consummation were conducted in Finland. Laitinen
(2007) developed logistic model to predict success of 89 reorganization plans con…rmed through legal proceedings in Finland. The essential result is that non-…nancial
variables decisively improve predicting ability of the regression model such as the
form of the …rm (limited or no limited company), the fact that a woman is the
entrepreneur and the number of part-time employees. Laakso (2007) conducted a
comparable study on 85 reorganization plans con…rmed in Finland in the year 2000.
The essential contribution of this study is the introduction in the model developed
by Laitinen (2007) of a dummy variable to indicate the normal progression in the
process to create and con…rm a reorganization plan. Laakso denoted that the progression is “normal” when it is not “exceptionally rapid or slow”. The results show
that the normality-indicator is a very powerful tool in explaining failure of the plan.
4 The
addition of the ongoing plans with a possible chance of full consummation
increases the maximum plan success rate to 44.2%.
155
In France, Germain and Frison-Roche (1993) analyzed continuations in the commercial Court of Paris between 1986 and 1991. They …nd that 50% of the reorganization attempt up as a failure. The authors analyzed 193 of cases of such failures.
The study reveals that the administrator reported problems to the Court in more
than two-third of cases.
5.3
5.3.1
Sample and consummation rate
Sample …rms
The data in the present study are collected directly from documents …led in the
commercial Court of Paris (Tribunal de Commerce de Paris) during the 1995-2004
period. The district of Paris was selected since it has the highest business …lings
and for ease of access to the data.5 The choice of the 1995-2004 period was based
mainly on reforms timing to avoid the impact of a given reform on the reorganization
process.6 We selected a random sample of 350 cases among the 1,718 cases that …led
for reorganization between 1995 and 2004 and that had their continuation plan
con…rmed. Although the French bankruptcy Code provides bankrupt …rms with two
forms of reorganization (continuation or sale), we focus exclusively on continuations
because sales plans were generally consummated within the year following the sale
decision.
Some further remarks about data gathering should be made. First, data were
gathered manually from several documents: the bankruptcy declaration, the Court’s
decisions during the reorganization process, the list of claims, the report on the
business’s economic and employment situation, and the …nancial statements of the
5 About
11% of the French bankrupt …rms had …led in the commercial Court of Paris
during the study period.
6 The study period follows the reform of 1994 and precedes the reform of 2005.
156
…rm at the time of bankruptcy.7 Second, the study period includes the transition
to the Euro. Therefore, we converted data that were reported in Franc to Euro.8
Third, given that the study covers a ten-year period, all Euro values are expressed in
December 2004 Euro on the basis of a consumer price index. Finally, we used ALISSE
database to compute the average pro…tability of the bankrupt …rm’s industry.9 The
ALISSE database provides annual accounting data on an aggregated basis for each
economic activity sector. We classi…ed the sample cases among 114 categories de…ned
by the NES classi…cation.10 Then, for each industry sector, we used the income
statement and the balance sheet data provided by ALISSE database to compute
annual industry pro…tability ratios.
5.3.2
Consummation rate
In the present study, the de…nition of a successful reorganization is based on the
bankruptcy Code. A plan is “successful” if it is both con…rmed and consummated.
Given that a continuation plan can last several years and the study is over the 19952004 period, there are some …les that are still “in progress” on the survey date.11
In addition, in some cases the reorganized …rm cannot meet the provisions of the
plan and consequently the Court may order the cancellation of the plan and the
7 The
French names of these documents are: "déclaration de cessation des paiements,
jugement d’ouverture de la procédure de redressement judiciaire, jugement dé…nitif sur le
sort de l’entreprise, jugement de résolution du plan, état des créances, bilan économique
et social, bilan et état de résultat".
8 We used the following rate to convert data from Franc to Euro: 1 euro = 6.55956 FF.
9 The access to ALISSE database is available at: www.alisse.insee.fr
10 The NES (Nomenclature Economique de Synthèse) classi…cation is the French Aggregated Economic Classi…cation and it is comparable to the SIC (Standard Industry Classi…cation) in the U.S.
11 The date on which the companies’status was last observed is 1st July 2010.
157
liquidation of the …rm. The 350 continuation plans can be classi…ed into one of the
following four categories:12
- de…nitely completed
- probably completed
- in progress
- converted into liquidation
It appears that out of the 350 cases in the sample, 120 cases (34.3%) are “de…nitely completed”, 14 cases (4%) are “probably completed”, 45 continuations (12.9%)
are still “in progress”, and 171 plans (48.8%) are de…nitely “converted into liquidation”.
In the present study, a continuation plan is characterized as “consummated” if
it is classi…ed into one of these two categories: “de…nitely completed” or “probably
completed”. Thus, there are 134 “consummated” plans (38.3%) in the sample. If
we exclude the cases which are still “in progress”, the consummation rate would be
around 44%. This rate is slightly higher than the 35% rate found by Jensen-Conklin
(1992), but it is clearly lower than the rates reported by Fisher and Martel (1995,
1999, 2011).
By multiplying the 25% con…rmation rate in the commercial Court of Paris by
the 44% consummation rate, we conclude that a debtor …ling for reorganization has
an 11% chance of con…rming and consummating a plan as well as emerging from
reorganization as the same entity.13 This rate is higher than the 6.5% rate found by
12 See
Section 3.3 of Chapter 3 for the de…nitions used to include a plan into one of the
four following categories: “de…nitely completed”, “probably completed”, “in progress”, and
“converted into liquidation”.
13 During the period 1995-2004, we count for 6,860 commercial reorganizations among
which 1,718 cases had led to the con…rmation of a continuation plan. Thus, the percentage
of reorganization cases that resulted in the con…rmation of a continuation plan is about
25%.
158
Jensen-Conkiln (1992), but it is clearly lower than the rates found by Fisher and
Martel (1995, 1999, 2011).
If we take into account the cases “in progress”, the consummation rate in the
full sample (350 plans) would vary between 38.29% and 51.14% depending on the
outcome of cases “in progress” and the success rate would vary between 9.6% and
12.8%.14
On the other hand, the study of time to failure shows that 50% of the cases
that failed to consummate had their plans cancelled 2.12 years after the judgment
pronouncing the plan and in more than 75% of the cases, the failure took place less
than 3.5 years after plan’s con…rmation. The failure of the case is pronounced, on
the average, 2.68 years after plan’s con…rmation. Germain and Frison-Roche (1993)
found more pessimistic results: in more than 80% of the cases, the failure took place
less than 3 years after con…rmation.
Clearly, the …rst two objectives of the reorganization procedure in France which
advocate safeguard of the …rm and employment preservation do not seem to be
achieved because many bankrupt …rms fail in reorganization and are liquidated. This
…nding is not surprising since the French bankruptcy law by providing opportunities for reorganizing a distressed …rm is considered among the most debtor-oriented
systems in the world (La Porta et al., 1998). As a result, the French law creates an
important bias towards continuation of unpro…table …rms since a law that favours
the reorganization of viable …rms is also likely to save non-viable …rms as pointed by
White (1989, 1994) and Mooradian (1994). Blazy et al. (2011) show that the French
Courts work actively for preserving employment, by facilitating continuation against
liquidation. By trying too hard to preserve employment, the French law may fail to
14 The
total number of consummated plans would be bounded by 134 if all plans classi…ed
in the category “in progress”would fail and by 179 if all plans in the category “in progress”
would be consummated.
159
reorganize properly the distressed …rm which ends in liquidation (Kaiser, 1996). In
addition, by maintaining the original management in the …rm in most cases, the
bankruptcy law allows managers to make ine¢ cient decisions (Hotchkiss, 1995).
5.3.3
Summary statistics
In the remainder of the chapter, a continuation plan is considered “successful” if
it is both con…rmed and de…nitely or probably consummated. A continuation plan
is considered “failing” if it is con…rmed but that de…nitely did not consummate.
Applying this de…nition, it appears that 134 cases (38.3%) resulted in a successful
reorganization and 171 cases (48.86%) resulted in a failure. The 45 cases that are
still “in progress”are not taken into account.
Table 1 displays the characteristics of …rms that succeed in reorganization versus
those that ultimately failed. It also reports t-tests and Wilcoxon-tests between successful and failing …rms. As might be expected, …nancial variables are highly skewed:
e.g., while the mean asset value for successful reorganizations is e1.864 million, more
than 50% of the …rms have less than e296,000 in assets. Firms that failed in reorganization have average assets of e653,000 and more than 50% of the …rms have
less e314,000 in assets. Overall, the sample is marked by a large number of small
businesses and a small number of large businesses. In terms of total debt, the mean is
about e1.8 million and the median is around e432,000 for successful …rms and these
…gures are respectively about e760,000 and e422,000 for failing …rms. Secured debt
represents about 61% of total claims for …rms that succeed in reorganization whereas
it represents only 53% for …rms that fail. The median values are respectively 69%
and 56%. On average, banking claims represent 28% of total claims for successful
…rms and 17% for failing …rms. The median values are respectively 17% and 8%
160
for successful and failing …rms. The results from running t-tests and Wilcoxon tests
show that the di¤erence between the two groups is statistically signi…cant.
Then, we investigate the relationship between some variables and the success
rate to have a …rst outline on factors associated with plan’s success. As shown in
Table 2, the relative size of the case based on the amount of assets appears to have
little correlation to the consummation rate. This is consistent with Jensen-Conklin
(1992) and Fisher and Martel (1999) data.
This analysis also includes the examination of variables speci…c to the continuation plan such as plan’s expected duration and expected payouts. As Table 3 shows,
a plan with a shorter duration appears to have more chance to be consummated than
one of longer duration. More precisely, a plan with duration of one year or less has
81.82% of chance to be consummated, whereas a plan with duration that exceeds 10
years has only 30.61% of chance to be consummated. Moreover, the average duration of a plan that consummates is about 7.27 years, whereas this …gure is about
8.22 years for plans that fail. Table 4 displays the expected payout averages within
0, 1,. . . 36 months by reorganization outcome. Data show that the front-payments
promised in the plan are, on the average, higher for the …rms that ultimately succeed
in the reorganization than for failing …rms. This result suggests that viable …rms can
promise a high payout in the …rst installments of the plan which is consistent with
Martel (2003).
We also examine expected …rst payout promised in the continuation plan. It
appears that, on average, the …rst payment provided by the plan is about 15% for
plans that ultimately consummate and about 6% for failing plans.15
15 These
…gures are not reported in the tables.
161
5.4
Determinants of plan’s consummation
As previously mentioned, there is only a limited amount of research investigating
the factors that would determine the consummation of continuation plans. To get
around the lack of related research, we refer to some studies that investigate the
factors having an e¤ect on the post-bankruptcy performance or on the success of
reorganized …rms. In fact, it is reasonable to believe that …rms with high postbankruptcy performance or …rms that succeed in reorganization are more likely to
consummate the continuation plan. Consequently, the factors indicative of a high
post-bankruptcy performance or a successful reorganization may be also indicative
of successful consummation of the reorganization plan. However, one should note
that there are as many de…nitions of a “successful” reorganization as the related
empirical studies. Thus, the e¤ect of these factors will also depend on the de…nition
used to characterize a “success”. For example, pre-bankruptcy …nancial data would
have more impact if a “success” is de…ned as a reorganized …rm that continue to
operate for one year after con…rmation than a requirement of …ve-year survival period
after the con…rmation.
We examine in what follows the factors that may impact the consummation of a
continuation plan. An overview of the variables’de…nitions is contained in Table 5.
Firm characteristics variables
White (1981, 1984) demonstrates analytically that other things being equal, …rms
that successfully reorganize are larger because the size variable is likewise related
to borrowing capacity. Larger …rms are more likely to have raised capital in the
past by issuing long-term, unsecured bonds. The assets generated by such borrowing are available to serve as collateral for additional borrowing. Empirically,
Hotchkiss (1995) examines the performance of 197 public companies that emerged
162
from Chapter 11. The author …nds that the probability of reporting negative operating income in two of the …rst three years following bankruptcy and the probability
of restructuring within three years of the …rst bankruptcy decreases with the amount
of assets one year prior to …ling. Denis and Rodgers (2007) examine 141 …rms that
reorganized and emerged from Chapter 11 as independent publicly-traded …rms.
The results indicate that the likelihood of surviving as public …rm three years after
emerging from Chapter 11 and the likelihood of achieving positive operating margin
in at least two of the three years following emerging increase with the …rm size prior
to …ling for bankruptcy. Thus, our prediction is that larger …rms are more likely to
consummate the continuation plan. We measure …rm size by the natural logarithm
of total assets in the year prior to …ling for bankruptcy.
We also control for the …rm’s age and for …rm’s form by including a dummy
variable that distinguishes between incorporated and unincorporated …rms.
Banking claims
The study of Pond (1997) shows that the potential for rehabilitation of companies
going into administrative receivership seemed to have improved as a result of the
e¤orts and actions taken by the bank holding a ‡oating charge. Franken (2004)
argues that bank lenders would play the role of monitor of the small and mediumsized businesses with a concentrated debt structure once they are confronted with
a downturn of their fortune. In addition, the author argues that creditor-oriented
regime reinforces the monitoring and bonding functions of relational bank debt.
Even though the debtor-oriented bankruptcy law in French gives very limited
bargaining power to banks, we introduce the percentage of banking claims in the
model since the majority of the …rms in the studied sample are small businesses and,
therefore, may have a long-term lending relationship with one main bank lender. Our
163
prediction concerning this variable is that …rms with a higher percentage of banking
claims are more likely to complete the continuation plan.
Plan’s variables
It seems reasonable that some characteristics of the reorganization proposal may also
be expected to be related to the success of reorganization. Speci…cally, we include the
two following variables: the expected proportion of the …rst payout and the expected
duration of the continuation plan. The choice of the …rst variable is suggested by
Martel (2003) and Fisher and Martel (1995, 2011). They show that proposals with
front-loaded payments are more likely to succeed in reorganization. The interpretation of this result is that front-loaded payments are a signal of the …rm’s …nancial
viability. The second variable re‡ects uncertainty regarding the plan projections. In
fact, it is more likely to complete a plan that lasts few years than a plan that lasts
several years because the process of its implementation would involve less uncertainty that may a¤ect future performance and the consummation of the plan. The
duration of the plan also indicates the severity of the …nancial distress. A short plan
shows that the …rm does not have many debts or that it is capable of repaying them
within a short period. In both cases, it is a signal of the …rm’s viability.
Industry Conditions
We include the average pro…tability of the bankrupt …rm’s industry as proxy for
the state of industry. Remaining industry e¤ects will be controlled for by industry
dummies. We hypothesize that …rms in more pro…table industries are more likely to
consummate the continuation plan.
164
Causes of default
In the French context, Blazy et al. (2011) found that measures undertaken by the
Court may increase the probability of reorganization when they are connected to
some particular causes.16 Moreover, in the previous chapter, the empirical results
showed that some causes of default have a signi…cant e¤ect on the form of reorganization.17 Thus, it would be interesting to investigate whether the reported reasons
for …ling for bankruptcy have an e¤ect on the consummation of the continuation
plan. One may believe that some problems are easier to resolve than others. For
example, a …rm that encounters a temporary problem is more likely to complete the
plan than a …rm that su¤ers from serious strategy problems.
We collected the causes reported by the debtors in the bankruptcy declaration
and we regrouped them into related reasons. We developed seven groups:
- External business environment
- Strategy
- Management / Business operations
- Financing
- Outlets
- Accidental causes
- Personal causes
We associate each group of causes with a dummy variable that takes the value 1
if the debtor reported a reason among the group and the value 0 if not.18
16 In
Blazy et al. (2011) paper, the term “continuation” designates the restructuring of
the …rm as the same entity or the sale of the …rm as a going-concern which corresponds
to the term “reorganization” in our study and the term “reorganization” designates the
restructuring of the bankrupt …rm by keeping operations in the same entity which corresponds to the term “continuation” in our study.
17 See Chapter 4 for a detailed description of the study.
18 Details explaining which reasons were grouped into which categories are reported in
Appendix I.
165
Overall, the success-failure framework suggests that the following variables may
impact the bankruptcy decision: the size, the form, the age of the …rm, the percentage
of banking claims, the expected proportion of the plan’s …rst payout, the expected
duration of the plan, the pro…tability of the …rm’s industry, and the reasons behind
…ling for bankruptcy.
5.5
Empirical analysis
5.5.1
Logistic regression model
We use a logistic regression model to distinguish the …rms whose continuation plans
are consummated from the …rms whose continuation plans fail. The dependent variable in the logistic regression model is Y, where Y=1 if the continuation plan is
consummated and where Y=0 if the continuation plan fails. The logistic model uses
a cumulative standard normal distribution function to convert the values of explained
variables into probability values. The logistic probability function can be expressed
as below:
0
pj = Pr(yj = 1jxj ) =
exj
0
1 + exj
(5.1)
where pj is the probability that a …rm j; (j = 1; : : : ; n) has its continuation plan
consummated, xj is a vector of explanatory variables that determine the continuation
plan’s outcome of the j th …rm and
is a vector of coe¢ cients to be estimated.
An interesting transformation of pj is the logit transformation. This transformation is de…ned as:
g(pj ) = ln
pj
1
pj
= x0j
(5.2)
166
The importance of this transformation is that g(pj ) has many of the desirable
properties of a linear regression model.
Taking the product of the probabilities in equation 5.1 over all n …rms yields the
likelihood function:
L( ) =
n
Q
[Pr(yj = 1jxj )]yj [1
Pr(yj = 1jxj )]1
yj
(5.3)
j=1
Estimates of the parameter beta may be obtained by maximizing the logarithm
of the likelihood function:
ln L( ) =
P
ln F (xj ) +
j2S
P
j 2S
=
ln f1
F (xj )g
(5.4)
where S is the set of all observations such that yj 6= 0 and F (z) = ez =(1 + ez ):
A sample of 304 …rms composed of 134 reorganized …rms that have their continuation plan “de…nitely consummated” or “probably consummated” and of 171
reorganized …rms that have their plan converted into liquidation is used to estimate
the parameters of the model.
5.5.2
Estimation results
Table 6 displays the results estimated by logistic models for the full sample composed of 208 …rms.19 The dependent variable is a dummy variable that equals one
if the continuation plan is consummated, and it equals zero if the plan fails and the
reorganization is converted into liquidation. Table 6 also reports the estimated coef…cients, the standard errors, the statistical signi…cance of the coe¢ cients as well as
the log-likelihood chi square statistic, the pseudo-R2 , and information criteria (AIC
and BIC).
19 The
decrease in the number of observations from 304 to 208 is due to missing data.
167
We begin with a model that includes all the explanatory variables discussed in the
previous section (Section 5.4). The estimation results in column (1) show that there
are …ve variables that have statistically signi…cant impact on the consummation of a
continuation plan. More precisely, the coe¢ cients on “age”, “banking claims”, “…rst
payout to creditors”, “industry pro…tability”, and “accidental causes” are positive
and statistically signi…cant. The “expected plan’s duration” as well as the form
and the size of the …rm are not determinant variables in distinguishing …rms that
succeed from those that fail. The fact that the “expected duration”is not signi…cant
might be explained by the important correlation between this variable and the “…rst
payout to creditors” variable. Table 7 shows that the correlation between the two
variables is equal to -0.70. This …nding is not surprising since the shorter the plan’s
duration is, the higher the …rst payouts to creditors will be. Models (2) and (3) test
the original model with one variable at a time. We include “expected duration of the
plan” in Model (2) and “…rst payout to creditors” in Model (3). As expected, the
coe¢ cient on the “plan’s duration”variable becomes signi…cant and has a negative
e¤ect on plan’s consummation. In addition, the coe¢ cient on the “…rst payout to
creditors” variable is still signi…cantly positive. The comparison between the three
models based on AIC and BIC criteria suggests that Model (3) is preferred since its
shows smaller values of AIC and BIC. In what follows more attention will be paid
to Model (3).
Some remarks should be made on the e¤ect of the explanatory variables. First,
a high …rst payout is indicative of the company’s ability to generate consistently
positive cash ‡ow from operations and its rapidity in overcoming the encountered
problems. This …nding is consistent with Martel (2003). Second, although creditors
are not actively associated to the reorganization process in France, the study reveals
that the reorganized …rms may bene…t from a concentrated bank lender which is consistent with Franken (2004) and Fisher and Martel (1995, 2011). Speci…cally, bank
168
lenders may be inclined to play a monitoring role or to support …rms with concentrated debt structure to avoid the liquidation of the …rm and, therefore, ensure the
reimbursement of their claims. In fact, banks in France su¤er from low recovery rates
in liquidations because, on the one hand, their rights are diluted by preferential creditors and, on the other hand, the assets generate little value in a bankruptcy context.
Davydenko and Franks (2008) report that the median value of bank’s recovery rate is
equal to 31% for …rms that are liquidated. Furthermore, considering that relational
bank lending is an important source of funding for small and medium businesses,
reorganized …rms are forced to respect the installments of the plan. Third, it is
reasonable to believe that …rms operating in pro…table industries at the con…rmation year are more likely to have their continuation plan consummated because they
have favourable conditions to develop their activity and generate enough money to
meet the …nancial requirements of the plan. Fourth, it seems that …rms encountering
accidental problems are more likely to succeed in reorganization. In fact, sometimes
it happens that a highly pro…table business has to …le for bankruptcy because of
unexpected events such as gas explosion, dispute over a contract, robbery. . . Once
the …rm succeeds in restoring the situation, it may recover quickly and complete the
continuation plan. Finally, the positive impact of age suggests that older …rms may
be associated with more experience and, therefore, one may believe that they are
more likely to complete the continuation plan.
5.5.3
Odds ratios analysis
The coe¢ cients in the output of the logistic regression indicate the amount of change
expected in the log odds when there is a one unit change in the predictor variable
with all of the other variables in the model held constant. Because these coe¢ cients
are di¢ cult to interpret, we prefer to exponentiate them and interpret them as odds-
169
ratios. The odds of success is de…ned as the probability that a plan succeeds divided
by the probability that the plan fails.
The last column of Table 6 displays the odds ratios of the …ve variables found
to have signi…cant e¤ect on the probability of success in Model (3). The results
indicate that for one year increase in the age, the odds of a plan being consummated
(versus not being consummated) increases by a factor of 1.03. For 10% increase in the
expected …rst payment or in the proportion of banking claims, the odds of success
increases by a factor of 1.52 and 1.22, respectively.20 For 1% increase in industry’s
pro…tability, the odds of success increases by a factor of 1.11. Finally, the presence
of accidental problems increases the odds of success by a factor of 2.18.
5.5.4
Predictive power of the model
In this part of analysis, we focus on the predictive power of Model (3).
Predictive accuracy
Table 8 presents an analysis of the model’s ability to accurately classify the sample
…rms as either successes or failures based on a 0.5 cut-o¤ criterion. (Success is predicted if the model estimates a probability of a “successful” reorganization greater
than or equal to 50%; conversely, failure is predicted if the model estimates a probability of a “successful” reorganization less than 50%). The classi…cation analysis
indicates that the prediction model correctly classi…es around 71% of the sample
…rms.
The prediction accuracy achieved by the logistic model can be compared to that
of a naïve model which uses the actual proportions of successes and failures to
20 The
log odds ratio for a change of c units in the covariate xk is obtained from the logit
di¤erence g(xk +c) g(x) = c k and the associated odds ratio is obtained by exponentiating
this logit di¤erence = exp(c k ).
170
randomly classify the sample observations. The expected classi…cation accuracy rate
of a random naïve model is (q 2 +(1 q)2 ) where q represents the actual proportion of
the successful reorganizations in the sample. For the full sample of 97 successes and
111 failures, the random naive model would accurately classi…es 50.23% of the sample
observations, a level substantially below that achieved by the prediction model.
A more complete description of classi…cation accuracy can be given by the area
under the ROC (Receiver Operating Characteristics) curve. This curve plots the
probability of detecting true “success”(sensitivity) and the probability of detecting
false “failure”(1-speci…city) for an entire range of possible cut-o¤ points.21 The area
under the ROC curve in Figure 1 provides a measure of the model’s ability to discriminate between the …rms that have their continuation plans consummated versus
those that have their continuation plans failed. This area is equal to 0.75. According
to Hosmer and Lemeshow (2000), this is considered acceptable discrimination.22
Predictive validity
The purpose of this analysis is to assess the predictive accuracy of the model (3)
presented in Table 6 to a holdout sample of …rms …ling for bankruptcy later than
the …rms in the prediction sample. As a general rule a prediction model will …t the
sample from which it was drawn better than any other sample. Following Casey et
al. (1986) and Campbell (1996), we apply a holdout procedure to assess whether
over-…tting of the sample data is a problem in this study. The holdout procedure
splits the full sample into two groups: an estimation group and a holdout group.
The estimation sample data is used to construct a prediction model which is used
to classify the observations in the holdout sample. If over-…tting is a problem, the
21 Speci…city
is the probability of detecting true “failure”.
a general rule: if ROC = 0:5; this suggests no discrimination; if 0:7
ROC <
0:8, this is considered acceptable discrimination; if 0:8
ROC < 0:9, this is considered
excellent discrimination; if ROC 0:9, this is considered outstanding discrimination.
22 As
171
prediction model would achieve a substantially higher level of prediction accuracy
on the estimation sample than it does on the holdout sample. The observations
in the estimation sample are usually drawn from an earlier time period than the
observations in the holdout sample in order to assess whether relationships among
variables are stable over time. Thus, the sample …rms were ordered chronologically
according to the date on which they …led for bankruptcy. The estimation group is
composed of …rms that …led for bankruptcy between 1995 and 1998 and the holdout
group is composed of …rms that …led for bankruptcy between 1999 and 2004. Table
9 describes the samples used in the holdout procedure.
Table 10 presents the classi…cation analysis results for both the estimation and
the holdout samples. Using a 0.5 cut-o¤ criterion, the prediction model generated
from the estimation sample correctly classi…es about 66% of the …rms in the estimation sample and 62% of the …rms in the holdout sample. The decrease in classi…cation
accuracy is expected when using a holdout sample. These results suggest that the
relationships among variables are stable over time and that over-…tting is not a
problem in the sample data.
5.6
Conclusion
We address in this chapter the issue of plans’consummation at a particular bankruptcy Court in France. Several conclusions and observations can be drawn from
this study.
First, the con…rmation of a continuation plan does not imply its consummation.
We …nd that only 44% of con…rmed cases result in a consummated plan. Moreover, a
debtor …ling for reorganization has an 11% chance of con…rming and consummating
a plan as well as emerging from reorganization as the same entity. The poor consummation rate suggests that the French bankruptcy system is biased towards the
172
reorganization of unpro…table …rms. This can be explained by the lawmaker’s willingness to maintain the …rm and preserve employment by providing opportunities
for reorganizing. Thus, the Court maintains the original management in most cases
which may result in ine¢ cient decisions. In addition, the Court con…rms continuation plans that can last for many years. These plans may re‡ect, on the one hand,
the poor pro…tability of the …rms at the con…rmation date, and on the other hand,
they are subject to more uncertainty.
Second, the results of this study provide strong support for the importance of …ve
factors to distinguish bankrupt …rms that have their plans consummated from those
that fail. The study reveals that the probability of consummation increases with the
age of the …rm, the relative size of banking claims, the percentage of the plan’s …rst
payout, the …rms’industry pro…tability, and the presence of “accidental problems”.
The percentage of the …rst payout to creditors re‡ects the …rm’s ability to generate
cash ‡ow and its rapidity in resolving the …nancial crisis. Although creditors are
not actively associated to the reorganization process, the study suggests that the
reorganized …rms may bene…t from a concentrated bank lender. Our interpretation
of this result is that bank lenders may be inclined to play a monitoring role or to
support …rms with concentrated debt structure to avoid the liquidation of the …rm.
This latter is also forced to respect the installments since it relies on bank debt.
Third, the prediction model presented in this chapter correctly identi…es around
71% of the sample …rms as either successes or failures. This prediction model could
be useful when forming an opinion regarding the plan’s likelihood consummation.
We conclude with three remarks. First, this study focuses on the reorganization
aspect of bankruptcy procedure and represents a …rst step toward understanding
the ability of bankruptcy systems to …lter viable …rms from nonviable …rms. Second,
one can investigate the role played by the Court in the success or the failure of the
173
…rm’s rehabilitation. Finally, another extension of our work would be to consider the
performance of …rms after the con…rmation. A poor post-con…rmation performance
would con…rm economically important biases toward continuation of unpro…table
…rms. The examination of post-con…rmation performance is undertaken in the following chapter (Chapter 6).
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178
Table 1 : Characteristics of Firms by Plan's Outcome
Mean
Variables
Median
Success
Failure
t-test
Success Failure Wilcoxon-test
Firm's age (years)
16.01
11.32
2.836***
9
9
1.235
Number of employees
13.58
10.58
0.433
4
5
- 1.084
Total assets (K€)
Total debts (K€)
Total debts / Total assets
1,864
1,806
1.81
653
760
1.57
1.008
0.990
1.165
296
432
1.31
314
422
1.26
- 0.124
0.280
0.341
Total Claims (K€)
Total number of creditors
1,396
31.62
651
30.82
1.236
0.141
352
19
345
24
0.631
- 2.539**
Secured claims (K€)
Unsecured claims (K€)
470
939
283
341
2.269**
1.069
199
95
162
139
1.609
- 2.029**
Secured claims / Total claims
Unsecured claims / Total claims
0.61
0.39
0.53
0.47
2.685***
- 2.685***
0.69
0.31
0.56
0.44
2.938***
- 2.938***
Wage claims (K€)
Banking claims (K€)
Government claims (K€)
Social claims (K€)
Other claims (K€)
45
493
90
82
695
28
145
109
94
263
0.553
1.397
- 0.804
- 0.694
1.305
0
54
40
34
69
5
18
39
72
99
- 3.196***
2.196**
- 0.432
- 4.343***
- 0.875
Wage claims / Total claims
Banking claims / Total claims
Government claims / Total claims
Social claims / Total claims
Other claims/ Total claims
0.03
0.28
0.19
0.16
0.32
0.04
0.17
0.19
0.25
0.33
- 1.465
3.300***
0.020
- 3.715***
- 0.300
0
0.17
0.11
0.09
0.26
0.02
0.08
0.13
0.21
0.27
- 3.271***
2.673
- 0.555
- 4.202***
- 0762
*, **, *** denote mean (median) significantly different from zero based on t-test (Wilcoxon signed rank test) at 10%, 5%, and 1%
level, respectively.
Table 2 : Consummation Rate by Assets (%)
Assets
Less than € 100,000
€ 100,000 to € 500,000
€ 500,000 to € 1 million
More than € 1 million
Consummation Rate
42.42
39.29
39.02
40.00
P_0
5.79
1.91
P_ Month
Success (mean)
Failure (mean)
81.82
Consummation rate (%)
78.57
<=2
73.33
<=3
63.16
<=4
60
<=5
39.92
>6
39.45
>7
2.61
8.94
P_1
3.8
12
P_3
4.94
15.49
P_6
6.18
16.27
P_9
14.64
24.04
P_12
Table 4 : Expected Payout Average by Plan's Outcome (%)
<=1
Duration (years)
38.50
>8
Table 3 : Relation between the Consummation Rate and the Plan's Duration
26.11
33.85
P_24
35.66
>9
37.23
43.61
P_36
30.61
>10
Dummy variable, equal to 1 if the firm is an unincorporated company
Natural logarithm of total assets measured prior to filing
(Banking claims)/(Total claims) measured prior to filing
(Expected First payment)/(Expected total payments) in the continuation plan
Expected duration fixed in the continuation's plan
Industry average of the return on assets measured at the confirmation year (based on the NES 114 level)
Dummy variables for "manufacturing", "trade", and "services"
Dummy variables for "external business environment", "strategy", "management/business operations"
"financing", "outlets", "accidental causes", and "personal causes"
Dummy variable, equal to 1 if the cause of default reported by the debtor is among the group
Firm's type
Total assets
Banking claims/Total claims
Expected percentage of the first payout
Expected plan's duration
Industry profitability
Industry dummies
Causes of default dummies
(CD)
Return on assets is defined as the operating income before depreciation and amortization over total assets.
Age of the firm measured prior to filing (years)
Firm's age
(a)
Definition
Variables
Table 5 : Definition of Explanatory Variables
(a)
ROA_S
DUR
P_FP
P_BANK
ln_TA
AGE
Abbreviation
181
Table 6 : Summary of Logit Estimation Models
(1)
(2)
(3)
Explanatory variables
Coefficient
Coefficient
Coefficient
Odds-ratio
Firm's age
0.0302**
(0.0152)
0.0272**
(0.0132)
0.0295*
(0.0151)
1.0299
Firm's type
- 0.0223
(0.4564)
0.1723
(0.4402)
- 0.0108
(0.4545)
Total assets
- 0.0828
(0.1407)
- 0.0353
(0.1308)
- 0.0685
(0.1362)
Banking claims/Total claims
0.01976***
(0.0072)
0.0170***
(0.0064)
0.0200***
(0.0072)
1.0202
Expected plan's duration
0.0029
(0.0073)
- 0.0139**
(0.0054)
Expected percentage of the first payout
0.0452***
(0.0169)
0.0418***
(0.0147)
1.0427
Industry profitability
0.1028**
(0.0460)
0.0756*
(0.0422)
0.1021**
(0.0460)
1.1075
Industry: Trade
0.5215
(0.4542)
0.6276
(0.4320)
0.5205
(0.4543)
Industry: Services
- 0.0515
(0.4023)
- 0.0760
(0.3844)
- 0.0619
(0.4013)
CD1: External environment
- 0.2269
(0.3417)
- 0.1711
(0.3202)
- 0.2197
(0.3411)
CD2: Strategy
0.4492
(0.6355)
0.3235
(0.6059)
0.4539
(0.6355)
CD3: Management/Business
- 0.3215
(0.3619)
- 0.3058
(0.3390)
- 0.3139
(0.3613)
CD4: Financing
- 0.1670
(0.3373)
0.0104
(0.3213)
- 0.1543
(0.3359)
CD5: Outlets
0.0410
(0.5033)
0.3136
(0.4748)
0.0775
(0.4946)
CD6: Accidental causes
0.7725*
(0.3966)
0.7953**
(0.3761)
0.7818**
(0.3951)
CD7: Personal causes
- 0.4118
(0.7064)
- 0.5667
(0.6408)
- 0.4172
(0.7042)
Intercept
- 2.7425
(1.0796)
- 0.5393
(0.8490)
- 2.4135***
(0.7050)
208
38.3***
0.1286
291.63
345.03
208
49.86***
0.1735
269.54
322.95
N
Chi-square-statistic
pseudo-R²
AIC
BIC
208
50.02***
0.174
271.38
328.12
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
Standard errors in parentheses
2.1854
182
Table 7 : Correlation Matrice
AGE
ln_TA
P_BANK
P_FP
DUR
ROA_S
AGE
ln_TA
1.0000
0.1967
- 0.0989
0.0491
- 0.0833
0.0085
1.0000
0.1670
- 0.1551
0.3217
- 0.1322
P_BANK
1.0000
0.0470
0.0999
0.0401
P_FP
1.0000
-0.7034
-0.0953
DUR
1.0000
0.0186
ROA_S
1.0000
Table 8 : Classification Analysis of the Full Sample
Success
Predicted
Failure
Total
Observed
Success
Failure
60
24
37
87
97
111
Total
84
124
208
Number of correct classifications = 147 (70.67%)
Table 9 : Subgroups used in the Holdout Procedure
Variables
Success
Failure
Total
Group 1: Estimation group (1995-1998)
74
63
137
Group 2: Holdout group (1999-2004)
23
48
71
Sample firms
97
111
208
183
Table 10 : Classification Analyses for Estimation and Holdout Samples
Panel A: Estimation Sample
Success
Predicted
Failure
Total
Observed
Success
Failure
53
26
21
37
74
63
Total
79
58
137
Number of correct classifications = 90 (65.69%)
Panel B: Holdout Sample
Success
Predicted
Failure
Total
Observed
Success
Failure
16
20
7
28
23
48
Number of correct classifications = 44 (61.97%)
Total
36
35
71
184
0.00
0.25
Sensitivity
0.50
0.75
1.00
Figure 1 : ROC Curve
0.00
0.25
Area under ROC curve = 0.7542
0.50
1 - Specificity
0.75
1.00
185
APPENDIX I: Stated Reasons for Filing : Groupings
External Business environment
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Bad economy
Competition
Decrease of prices
Increasing cost of doing business (raw materials, labor costs)
Increasing rent
Exchange rate
Technological revolution
Legislation (increase in VAT / new law / prefectorial authorization etc.
Problem related to the customer behavior
Bankruptcy of a subcontractor
Difficulties encountered by the subsidiary or the main branch are extended to the firm
Reputation needs costs and time
Inability to find skilled personnel / the firm is understaffed
Declining sales
Strategy
15
16
17
18
19
20
21
22
23
24
25
26
Takeover of a bad business
Failure of activity expansion
Failure of diversification
Expensive merger
The activity depends strongly on a specific sector or market
Overinvestment
Disinvestment from some projects
Continuation of an unprofitable business
Costly relocation
Location was bad
Large royalties
Problems related to lease-management
Management / Business operations
27
28
29
30
31
32
33
34
35
36
37
Bad management / inexperience
Problem related to management control
Time devoted to management is insufficient
Conflict between business partners concerning management
Excessive takings from receipts by management
Hard startup
Difficulties to realize a project / failure of an important project
Organizational problems
Slow implementation of new measures
Lack of dynamism and adaptation
Absence of an IT department
186
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Weak account reporting
The activity is not profitable
Operating loss
High costs compared to firm’s activity
Wage and social claims are too high compared to firm's activity
Problems related to bad predictions
Underestimation of the sector crisis
Bad evaluation of cost price
Bad evaluation of costs
Stock management
Over-sizing of production capacity
Problem with personnel
Unskilled personnel
Departure of critical personnel
Financing
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
High debt service
Banks refuse to support the firm
Bank overdraft is too high
Bank account is blocked due to bank restructuring
Excessive support of banks
Shorter delays on account receivable
Cash flow problem
Liquidity problems resulting from the dismissal of many workers
Absence of working capital
Increase in working capital requirement
Lack of equity
Problems related to the financing of restructuring measures
Financial structure
Bankruptcy of a shareholder
Old debts taken on at business purchase
Delay in payment / nonpayment by clients
Outlets
68
69
70
71
72
73
74
75
76
77
78
Bad quality of products
Obsolete products
Products lack diversity
Problems related to commercial strategy
Failure of a new commercial organisation
Difficulty to commercialize firms’ products
Marketing positioning
Concentration of retailing
Loss of important clients
Bankruptcy of important clients
Clients’ merger
187
Accidental Causes
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
War / attacks
Strikes
Weather related problems
Road work
Problems related to neighbours
Departure of many firms from the district
Robbery / fire / cow disease etc.
Defective installation
Temporary closing of the firm
Goods’ blocking through customs
Port’s closing
Conflict with a partner
Problems encountered with lessor
Important condemnation pronounced by the French industrial tribunal
Tax adjustment / Penalties due to delay in payment of tax and social claims
High compensation related to lease-purchase contract
The factor did not pay the firm
Personal problems
96
97
98
Medical problems / death of the manager
Family problems
Personal bankruptcy
Chapter 6
Performance of Reorganized Firms in France
6.1
Introduction
One of the central questions debated about …nancial distress is the e¢ ciency of
bankruptcy systems. An e¢ cient bankruptcy law should, on the one hand, allow the
reorganization of viable …rms and, on the other hand, eliminate non-viable …rms.
However, as pointed by White (1989, 1994a, 1994b), it might be impossible to meet
simultaneously these objectives. A bankruptcy law which favours the reorganization
of viable …rms is also likely to save non-viable …rms. Conversely, a law which favours
the elimination of non-viable …rms is also likely to eliminate viable …rms. White
(1994a, 1994b) and Fisher and Martel (1995, 2004) de…ne two types of error that can
occur in bankruptcy procedures: Type I error occurs if ine¢ cient …rms are allowed to
continue operations and Type II error occurs if e¢ cient …rms are forced to liquidate.
The Type II error being di¢ cult to observe once a …rm has liquidated; the academic
research has focused on the Type I error. Speci…cally, prior research studied the
post-bankruptcy performance of reorganized …rms to examine the survival prospects
of those …rms and assess the e¢ ciency of bankruptcy system. Poor post-bankruptcy
performance would typically support the ine¢ ciency of the bankruptcy process.
188
189
Although there are numerous studies on post-bankruptcy performance of Chapter
11 in the U.S., very little research has been conducted on post-bankruptcy performance in France. Therefore, the object of this chapter is to address this lack of data
by giving the …rst detailed description and analysis of post-bankruptcy performance
of reorganized …rms at a particular bankruptcy Court in France.
In this chapter, our …rst question investigates whether the …rms that reorganize
in France are viable or whether the bankruptcy process allows …rms that are not
e¢ cient to reorganize and continue their operations. To answer to this question
we begin by examining the post-con…rmation outcome of 415 …rms that …led for
bankruptcy between 2001 and 2004. Then, we use 152 …rms from the previous sample
to examine a number of accounting measures of performance used in prior research.
Our second question concerns the determinants that a¤ect the post-con…rmation
outcome. Precisely, we compare characteristics of reorganized …rms that continue to
operate in the same entity to those that …le a second time. Then, we estimate logistic
regressions to determine the extent to which fundamental measures of operational
performance and …nancial structure are related to the post-con…rmation outcome in
France.
The remainder of the chapter is structured as follows: the next section presents a
review of previous research investigating post-bankruptcy performance. Section 6.3
describes the data set and the samples used in the study. In Section 6.4, we assess the
performance of the reorganized …rms by measuring the proportion of …rms that …le
for bankruptcy a second time and by examining accounting measures of performance.
Section 6.5 investigates the characteristics that distinguish …rms that successfully
reorganize from those that ultimately fail using the logistic estimation model. The
…nal section of the chapter contains a summary and some concluding remarks.
190
6.2
Review of prior research
One way to assess the success of a bankruptcy case is to measure the extent to which
the performance of the company improved. A review of the literature shows several
ways in which one might measure the post-bankruptcy performance.
Some studies examine the consummation of the reorganization plan to assess the
success of the reorganization. Jensen-Conklin (1992) reports that 35% of 46 con…rmed plans consummate and allow the …rm to continue as independent companies.
Baldiga (1996) …nds that only 25.6% of the 47 con…rmed, non-liquidating plans were
fully consummated. Fisher and Martel (1995, 1999, 2011) report that over 72% of the
proposals accepted by unsecured creditors and con…rmed by the Canadian Court are
consummated. In the French context, the study conducted in the previous chapter
shows that 43% of con…rmed continuation plans are consummated.1
Other studies argue that this de…nition is rather restrictive. First, the success
or the failure may be a¤ected by post-con…rmation events especially when the plan
lasts for many years, and hence the success rate would not be a function solely of
the bankruptcy proceedings. Second, this de…nition of “success” would reduce signi…cantly the number of successes in empirical studies samples. Instead, numerous
studies investigate whether the surviving entity remained out of bankruptcy after
the con…rmation of the reorganization plan within a certain period of time. LoPucki
and Whitford (1993) conducted an empirical study of 43 Chapter 11 cases involving
large, publicly held …rms.2 They report that 32% of the sample cases …led another
bankruptcy petition within four years. Hotchkiss (1995) examines 197 …rms that
emerged as public companies from Chapter 11 by 1989. The author …nds that 32%
1 See
Chapter 5 for a detailed description of these studies.
cases constitute the universe of cases …led under the Bankruptcy Code by publicly held companies reporting at least $100 million in assets at …ling and having been
con…rmed by March 1988.
2 These
191
of the sample restructured after emerging from bankruptcy either through a private
workout (36.5%), a second bankruptcy (55.5%), or through an out-of-court liquidation (8%). Gilson (1997) analyzes 108 publicly-traded …rms that recontracted with
their creditors during 1980-1989 period, either by reorganizing under Chapter 11, or
by restructuring their debt out-of-court. More than 25% of the sample …rms have
to …le for bankruptcy or restructure their debt a second time. Denis and Rodgers
(2007) examine post-reorganization outcome of 141 …rms that …le for Chapter 11
over the period 1985-1994 and that emerge as public going-concern. They …nd more
optimistic results: 5% of the reorganized …rms undergo a distressed restructuring,
12.1% …le again for Chapter 11, and 2.8% ultimately liquidate through the end of
the third full year following reorganization.
Many studies examine accounting measures to identify improvement in …rm performance following bankruptcy. Hotchkiss (1995) examines post-bankruptcy operating performance and industry-adjusted performance of the sample …rms. The
author …nds that over 40% of the …rms emerging from bankruptcy continue to experience operating losses in the three years following bankruptcy. Moreover, for all
years after bankruptcy, the operating margin and the return on assets for bankrupt
…rms remain signi…cantly lower than the industry. Kahl (2001) examines the postdistress operating performance of 30 …rms that had overcome …nancial distress and
remained independent. The author …nd that post-distress performance of the …rms
that avoid Chapter 11 is typically better than the post-Chapter 11 performance.3
Denis and Rodgers (2007) examine operating performance and industry-adjusted
performance subsequent to reorganization. They …nd that 61% of reorganized …rms
achieve positive operating margin in at least one of the three years following their
3 Kahl
(2001) de…nes a …rm in …nancial distress as a …rm that is in default or that
negotiates with its creditors to restructure its debt in order to avoid a default, or that has
…led for Chapter 11 between 1980 and 1983.
192
emergence from Chapter 11, while 52.5% do so in at least two of the three years.
When compared with industry performance, the authors …nd that 44% of reorganized …rms experience greater operating performance in at least one year of the three
years following emergence and only 28.4% achieve greater operating performance in
at least two of those years. Finally, Kalay et al. (2007) examine the operating performance of 113 …rms during Chapter 11 in 1991-1998 period. Using changes in
industry-adjusted normalized performance, the study shows that the sample …rms
experience signi…cant improvements in their operating performance during Chapter
11.
Another accounting measure of …nancial performance is whether the reorganized
entity emerges from bankruptcy with less debt. LoPucki and Whitford (1993) calculate debt ratios for 26 debtors from the …rst annual …nancial reports after con…rmation.4 Then, they calculate a benchmark ratio for each of the emerging companies
based on the size and industry. They …nd that the debt ratio exceeds the benchmark
ratio for 76% of the studied …rms. Gilson (1997) shows that leverage remains high
after Chapter 11 reorganization and, in general, sample …rms end up more highly
leveraged than they were before becoming …nancially distressed. According to the
author, the median ratio of long-term debt to the sum of long-term debt and common
shareholders’equity (market value) is 0.47 for …rms that reorganize in Chapter 11
while the median ratio of long-term debt to the sum of long-term debt and the book
value of shareholders’equity is 0.59. In addition, about 70% of the sample …rms that
reorganize in Chapter 11 have leverage ratio that exceeds industry median after
reorganization.
Other studies analyze post-bankruptcy performance by measuring the …rms’cash
‡ows. Among the earliest, Hotchkiss (1995) measures whether the …rm meets cash
4 The
debt ratio used in the analysis compares the value of debt to the value of debt
and equity combined.
193
‡ow projections provided at the time of reorganization for 72 …rms. The results show
that the median percentage deviation of the actual performance from the projected
one in each year is negative and signi…cantly di¤erent from zero. Alderson and Betker
(1999) examine the cash ‡ows for a sample of 89 …rms that emerged from Chapter
11 reorganization between 1983 and 1993. They evaluate the total cash ‡ows for
each …rm for up to …ve years following the con…rmation year. Then, they compare
the rate of return earned by the reorganization …rm to the rate of return that could
have been earned by liquidating the …rm and placing the proceeds in an alternative
investment. The authors …nd that reorganized …rms neither under nor over-perform
following bankruptcy.
Eberhart et al. (1999) analyse the stock performance for a sample of 131 …rms
emerging from Chapter 11 in the period 1980-1993. Contrary to the poor operating
results of …rms emerging from bankruptcy reported in previous work, the study shows
positive excess returns in the 200 days of returns following emergence. Speci…cally,
the ACAR (Average Cumulative Abnormal Returns) varies from 24.6% to 138.8%
depending on how the expected returns are estimated.
Several studies focus on understanding the factors that a¤ect subsequent performance. Hotchkiss (1995) examines several speci…cations of logistic regressions where
the dependent variable indicates …rms with poorer post-bankruptcy performance
based on 197 …rms and on three di¤erent de…nitions of “poor performance”.5 The
regressions show that retaining pre-bankruptcy management is strongly related to
worse post-bankruptcy performance. The results also show that larger …rms are
5 The
dependant variable in the …rst set of regressions equals 1 if the …rm restructured
through a private workout, second bankruptcy, or liquidation within 5 years of emerging
from bankruptcy. The dependant variable in the second set of regressions equals 1 if the …rm
reported negative operating income in 2 of the 3 years following bankruptcy or restructured
within 3 years of the …rst bankruptcy. The dependant variable in the third set of regressions
equals 1 if the …rm reported an operating margin lower than the industry median in each
of the 3 years following bankruptcy or restructured within 3 years of the …rst bankruptcy.
194
associated with a lower probability of reporting negative operating income and that
pre-bankruptcy pro…tability is associated with worse performance after bankruptcy.
In a recent paper, Denis and Rodgers (2007) examine the impact of pre-Chapter 11
operating and …nancial characteristics and changes in those characteristics on postreorganization performance. The results show that larger …rms are more likely to
survive three years following the reorganization than are smaller …rms. Contrary to
Hotchkiss (1995), Denis and Rodgers …nd that pre-…ling …rm operating pro…tability
is signi…cantly positively related to post-bankruptcy operating performance. The
regressions indicate that …rms whose industry-adjusted operating performance was
positive prior to entering Chapter 11 and that succeeded in improving this performance while in Chapter 11 are most likely to achieve future positive operating
performance. The results also indicate that …rms that reduce their size and their
liability ratio are most likely to achieve positive industry-adjusted operating performance. Finally, the combined measure indicates that a reorganized …rm is more
likely to both survive and achieve future positive operating performance following
emergence from Chapter 11 if it i) had a positive industry-adjusted operating performance prior to Chapter 11 …ling, ii) succeeded in improving this performance,
iii) reduced its liability ratio, and iv) took longer time in Chapter 11.6 For a more
recent time period, Altman (2009) uses a bankruptcy prediction model to assess the
future health of two Chapters 11 samples. The …rst sample includes 45 …rms that
emerged from Chapter 11 between 1993 and 2003 and that avoided a subsequent
distressed restructuring whereas the second sample includes 41 …rms that emerged
from Chapter 11 between 1993 and 2006 and that had …led again for bankruptcy.
The study reveals that …rms which …led for bankruptcy a second time emerged signif6 The
combined measure is a dummy variable that equals 1 if the …rm exists as an
independent going concern three years following the emergence from Chapter 11, does not
require subsequent reorganization over that period, and exhibits positive operating margin
in at least two of the three years following reorganization.
195
icantly less pro…table and with signi…cantly more leverage than those that emerged
and remained as a going-concern.
6.3
Data and sample
The sample used in the study was drawn from the list of …rms that …led for reorganization in the commercial Court of Paris between January 2001 and December
2004 and that had their continuation plan con…rmed.7 Although the French bankruptcy Code provides …rms with two forms of reorganization (the continuation of
the bankrupt …rm in the same entity or the sale of the …rm as going-concern to
another entity), we focused only on …rms that reorganized within the framework of
a continuation because post-con…rmation data for acquired …rms are not available.
The district of Paris was selected since it has the highest business …lings and for
ease of access to the data.8 The choice of the 2001-2004 period was based mainly on
…nancial data availability and on reforms timing.9
We identify 415 …rms in the full sample that will be used to measure the proportion of …rms that …led a second time for bankruptcy.10 For each …rm, we have
information on the con…rmation date and on the status of the case.11 In addition,
for …rms that have their plans cancelled, we have information on the date on which
the case was converted into liquidation.
Then, we collected from the full sample …les the SIREN (Système Informatique
pour le Répertoire des ENtreprises) number of the …rms to extract …nancial and
7 The
selection of the sample was facilitated by access to the list of commercial reorganizations in Paris by outcome (continuation/sale/liquidation) during the 2001-2004 period.
8 About 11% of the French bankrupt …rms had …led in the commercial Court of Paris
during the study period (Source: www.insee.fr).
9 The study period follows the reform of 1994 and precedes the reform of 2005.
10 The original list contained 459 …rms from which we excluded 44 …lings because they
relate to many …rms at the same time.
11 The date on which the companies’status was last observed is 1st July 2010.
196
accounting information from DIANE, our source for all accounting data.12 DIANE
database contains company accounts and …nancial ratios for the 1,500,000 companies in France that published their accounts in one of the 190 commercial Court
registries.13
Among the 415 …rms contained in the full sample, 172 are covered by DIANE
database. For these …rms, we collected balance sheet and income statement data
from three …scal years prior to …ling (year F-3) to the …scal year of …ling (year F)
and from the con…rmation year (year R) through the end of the third full …scal year
following the plan con…rmation (year R+3).14 We excluded 20 …rms due to data
limitations. Thus, the …nal sample consists of 152 …rms and will be used to examine
accounting measures of performance for reorganized …rms and to investigate the
factors that would distinguish successful from failing reorganizations.
We also used ALISSE database to compute industry-adjusted measures of performance.15 The ALISSE database provides annual accounting data on an aggregated
basis for each economic activity sector. We classi…ed the sample cases among 114
industry sectors de…ned by the NES classi…cation.16 Then, for each industry sector,
we used the income statement and the balance sheet data provided by ALISSE
database to compute annual industry measures of performance based on the same
de…nition used to compute …rm’s performance ratios.
12 The
SIREN number is an identi…cation number assigned to each commercial enterprise
or business in France. It was collected manually …le by …le in the commercial Court of Paris
because a list of reorganized …rms with the corresponding SIREN number was not available.
13 Unincorporated …rms are not concerned with this formality.
14 Year F represents the …scal year during which the Court opens the procedure, and
Year R represents the …scal year during which the Court con…rms the reorganization plan.
Years between F and R are not considered in measuring performance because, on the one
hand, the number of these years varies among …rms and, on the other hand, some reports
are not available for this period.
15 The access to ALISSE database is available at: www.alisse.insee.fr.
16 The NES (Nomenclature Economique de Synthèse) classi…cation is the French aggregated economic classi…cation and it is comparable to the SIC (Standard Industry Classi…cation) in the U.S.
197
The …rms contained in the …nal sample are distributed across 30 industry sectors.
Three industry sectors; “hotels and restaurants” (26 …rms), “wholesale trade” (17
…rms) and “IT activities”(15 …rms) together comprise almost 40% of the sample.
6.4
Measure of post-con…rmation performance
In this section, we use two measures to assess the post-con…rmation performance.
First, we measure whether the surviving entity remained out of bankruptcy after
the con…rmation of the reorganization plan. Second, we examine some accounting
measures to study the performance of reorganized …rms.
6.4.1
Post-con…rmation outcome
In France, when a reorganized …rm fails to meet the schedule of repayments …xed
in the reorganization’s plan, the Court orders the cancellation of the plan and the
commencement of a liquidation procedure.17
Of the 415 …rms in our original sample, 193 (47%) …led again for bankruptcy
between the con…rmation date and the survey date. This percentage could be underestimated for two reasons. First, it does not include …rms that restructured their
debts again through a private workout. Second, the time between the con…rmation
date and the survey date is relatively short for some …rms.
It is important to notice that the rate of …ling a second time for bankruptcy
reported in this study is much higher than for …rms that reorganize in the U.S.
[Hotchkiss (1995), Gilson (1997), Denis and Rodgers (2007)].18 The high rate suggests the presence of Type I error in the French bankruptcy system, i.e., a bias
towards continuation of ine¢ cient …rms. In fact, the French bankruptcy law is a
17 See
18 See
(L621.80) under the old commercial Code (2005).
Section 6.2 for a more detailed description of these studies.
198
debtor-oriented law (La Porta et al., 1998). Therefore, it favors the reorganization
of viable …rms and, inevitably leads to the continuation of non-viable …rms.
The average time between the con…rmation date and the second …ling is 2.42
years with a median time of 2.05 years. These …gures seem to be lower than those
reported by studies conducted on Chapter 11. Hotchkiss (1995) reported a median
time equal to 3.8 years after emerging from bankruptcy while Altman (2009) found
that the average duration between emergence and re…ling for bankruptcy is about
3.37 years. The range of durations from con…rmation to second bankruptcy …ling is
between 0.22 year and 6.82 years. Table 1 shows that 16.5% of the …rms …led for a
second bankruptcy within the …rst year following con…rmation whereas more than
48% of the …rms entered bankruptcy a second time within 2 years. We observe that
many …rms that had their plans con…rmed are forced to liquidate within a relatively
short period of time after con…rmation. This …nding suggests that the Court allows
some ine¢ cient …rms to continue their operations.
6.4.2
Accounting measures of performance
Based on prior research, we examine a number of accounting measures related to …rm
and industry-adjusted performance [Hotchkiss (1995), Gilson (1997), Alderson and
Betker (1999), Kahl (2001), Denis and Rodgers (2007)]. We measure (1) operating
margin de…ned as operating income before depreciation and amortization over sales
and (2) return on assets de…ned as the operating income before depreciation and
amortization over total assets. Moreover, we measure (3) the leverage using the
ratio of total debts to total assets.
Accounting measures of pro…tability (operating margin and return on assets) and
leverage are also computed on an industry-adjusted basis by subtracting from the
previous measures the corresponding average industry ratios. There is prior support
199
in the literature for the use of industry-adjusted operating performance in examining
distressed …rms [Hotchkiss (1995), Kahl (2001), Denis and Rodgers (2007)].
We begin by examining the performance of the reorganized …rms prior and following con…rmation. Table 2 reports the means and medians of operating margin,
return on assets, and leverage for the sample …rms from the year F-3 to the year R+3.
The percentage of observations with negative operating income is also reported. One
should note that the number of observations is not the same for all years due to data
availability. Additional missing observations in post-con…rmation years are due to
…rms that left the sample because of a second …ling for bankruptcy.
Starting at year F-3, the median measures on pro…tability are signi…cantly positive and most of the sample …rms (67.7%) have a positive operating income. However,
Table 2 shows that the …rms are already highly leveraged at year F-3 with an average
(median) ratio equal to 0.932 (0.881). These …gures related to leverage suggest that
some …rms have already …nancial di¢ culties. As one would expect, performance indicators reach their worst level closer to …ling. Thus, pro…tability measures are significantly negative at year F-1 and year F and the percentage of …rms with negative
income increases to more than 60% during these years. Following the con…rmation,
we note an improvement in the means and medians of pro…tability measures. Specifically, at the con…rmation year and during the next three years, the median value
of both operating margin and return on assets is signi…cantly positive and reaches
levels similar to year F-3. In addition, the percentage of …rms having negative income
is decreasing in the years following con…rmation and varies from 34.4% (at year R)
to 24.3% (at year R+3). The post-con…rmation pro…tability reported in this study is
better than the post-Chapter 11 operating performance results in Hotchkiss (1995),
who found that between 35% and 41% of all …rms have negative operating income
in each of the …ve years following the emergence from Chapter 11. The picture is
di¤erent for leverage ratio which remains very high from F-3 to R+3. Particularly,
200
the average (median) value of leverage ratio reaches 1.648 (1.217) at the con…rmation year (year R). This …nding is consistent with LoPucki and Whitford (1993) and
Gilson (1997).
We turn now to examine industry-adjusted performance measures. Table 3
shows the mean and median values of industry-adjusted operating margin, industryadjusted return on assets, and industry-adjusted leverage from the year F-3 to
the year R+3. Table 3 also reports the percentage of …rms showing a pro…tability
(leverage) measure lower (higher) than the industry average. One should note that
the number of observations in Table 3 is lower in comparison with Table 2 due to
missing data on industry average for some industries.
Table 3 indicates that the pro…tability measures are worse than the industry
average from two years prior to …ling until the con…rmation year. However, the percentage of …rms having a lower pro…tability than industry decreases from 82% at
the …ling year to 66% at the con…rmation year. Then, three years after the con…rmation the …gures on pro…tability are not signi…cantly di¤erent from industry and the
percentage of observations showing a return on assets lower than industry falls to
46.4%. These results are better than in Hotchkiss (1995). The author indicates that
71% of the …rms remain signi…cantly less pro…table than industry three years after
the emergence from bankruptcy. Table 3 also shows that the sample …rms are more
leveraged than industry over the eight-year study period (from F-3 to R+3). The
percentage of …rms that are more leveraged than industry is very high and exceeds
83% over the study period. This percentage exceeds 97% at the …ling year and it
remains very high (87.18%) three years following the con…rmation.
Table 4 shows the median variation for each pro…tability variable as well as the
percentage of …rms showing a positive change. The changes in operating margin and
in return on assets from year F-1 to year R are signi…cantly positive and about
60% of the …rms experience positive change in pro…tability during this period. We
201
believe that pro…tability improvement is related to the measures undertaken by the
Court, particularly the automatic stay ordered during the observation period. The
annual changes do not show strong increase during the post-con…rmation period. For
example, the median variation in return on assets is not signi…cant from year R to
year R+1 and becomes negative over the following periods. In addition, the proportion of …rms experiencing positive variations in pro…tability measures is decreasing
over the following periods.
In Table 5, we examine four dummy variables based on …rm post-con…rmation
performance from year R to year R+2. We …nd that 93.64% of reorganized …rms
achieve positive return on assets in at least one of the three studied years, whereas
74.49% achieve this in at least two of the three years. The percentage of …rms
exhibiting positive industry-adjusted return on assets in at least one of the three
years is 81.40% and it decreases signi…cantly to 41.18% for …rms achieving it in at
least two of the three years. The results shown in Table 5 are much better than those
reported by Denis and Rodgers (2007).19
6.5
Successful versus failing reorganizations
Our …nal question relates to the extent to which fundamental measures of operational
performance and …nancial structure impact the post-con…rmation outcome in France.
From the …nal sample composed of 152 …rms, we constitute two groups made
up of successful reorganizations and failing reorganizations. We adopt the following
de…nition to separate successful from failing reorganizations: a successful reorganization is one that results in the emergence of an independent entity that continue its
operations for at least four years from the con…rmation date. A failing reorganization
19 See
Section 6.2 for more details on Denis and Rodgers (2007) results.
202
is one that results in a second …ling for bankruptcy within four years from the con…rmation date. Following this de…nition, we identify 113 successful reorganizations
and 39 failing reorganizations.
In the …rst part of the analysis, we examine the accounting measures of performance by reorganization’s outcome (success or failure) prior and following con…rmation. Precisely, Table 6 reports the mean and median values of performance
measures, t-tests and Wilcoxon tests for successful and failing reorganizations at
year F-1 (Panel A), at year R (Panel B), and at year R+1 (Panel C).
As reported in Panel A, the average and median values of pro…tability are negative for both groups at the year preceding …ling for bankruptcy. Besides, both
groups exhibit lower pro…tability than industry. Some of the pro…tability measures
are statistically di¤erent between the two groups suggesting that …rms with higher
pro…tability at year F-1 are more successful. Panel A also shows that both groups
are in deep …nancial distress. In fact, the mean (median) of leverage ratio is equal
to 1.419 (1.125) for successful reorganizations and 1.362 (1.157) for failing reorganizations. The di¤erence between the two groups is not signi…cant.
Now, we examine performance measures at the con…rmation year. Panel B of
Table 6 shows that both groups exhibit better pro…tability measures compared with
those obtained at the year F-1. However, these measures are still lower than industry.
Moreover, the results from running Wilcoxon tests on operating margin and on
return on assets indicate that successful reorganizations have higher pro…tability
at the emergence year than failing reorganizations. This …nding suggests that the
bankruptcy process allows …rms with low pro…tability to emerge from bankruptcy
by con…rming their plans instead of ordering the liquidation of these …rms and the
redeployment of their assets. Other …gures con…rm this tendency. For example, we
…nd that more than 40% of the reorganized …rms in the sample experience lower
203
return on assets at the con…rmation year (R) than at the pre-…ling year (F-1). On
the other hand, Panel B indicates an increase in leverage ratio at the con…rmation
year for both groups. Successful reorganization exhibit lower leveraged ratios, but
the di¤erence is not signi…cant.
Finally, Panel C shows performance measures one year after con…rmation for
both groups. As one would expect, successful reorganizations have better …nancial
indicators than the previous year. There is an increase in pro…tability and a decrease
in leverage ratio. This is not the case for …rms that ultimately fail whose median value
of pro…tability becomes negative. In addition, Wilcoxon tests indicate that …rms that
ultimately …led for a second bankruptcy had a signi…cantly worse …nancial pro…le
one year after con…rmation than the sample of …rms that continue their operations
for at least four years.
In the second part of the analysis, we estimate logistic regressions to investigate
the factors that distinguish successful from failing reorganizations. The dependent
variable is a dummy variable that equals one if the reorganization succeeds i.e. the
…rm continues to exist as an independent entity for at least four years following the
con…rmation date, and it equals zero if the reorganization fails i.e. the …rm …les for
a second bankruptcy within four years from the con…rmation date. We introduce
in regression models the following explanatory variables: …rm size, return on assets
ratio, liquidity ratio, leverage ratio, and industry pro…tability. These variables are
measured at the year prior to …ling (year F-1) in the …rst regression and at the
con…rmation year (year R) in the second regression. An overview of the explanatory
variables’de…nition is presented in Table 7.
Table 8 displays the results estimated by logistic regression models. It reports
the estimated coe¢ cients, the standard errors, and the statistical signi…cance of
204
the coe¢ cients. The table also shows the number of observations, log-likelihood chi
square statistic, AIC, and BIC criteria.
In the …rst regression, we examine the impact of pre-…ling operating and …nancial
characteristics (measured at year F-1) on post-con…rmation outcome. Column (1)
indicates that the size, the pro…tability, the liquidity and the leverage of the …rm
prior to bankruptcy do not screen viable from non-viable …rms. The coe¢ cients
in all these variables are not statistically signi…cant. In counterpart, there is one
variable, the industry operating margin, that is found to be statistically signi…cant
at the 5% level. The positive coe¢ cient on this variable suggests that …rms operating
in pro…table industries prior to …ling are most likely to succeed in reorganization.
This …nding is not consistent with Denis and Rodgers (2007) who …nd this variable
non-signi…cant.
In the second regression, we assess the e¤ect of the previous characteristics (measured at year R) on post-con…rmation outcome. Consistent with Altman (2009), the
results presented in column (2) show that …rms that succeed in reorganization had
signi…cantly better pro…tability than …rms that …led again for bankruptcy. In addition, the coe¢ cients on two additional variables (…rm’s size and industry operating
margin) are positive and statistically signi…cant. Overall, larger …rms with higher
pro…tability and operating in pro…table industries at the con…rmation year are most
likely to continue their operations for at least four years following con…rmation.
Contrary to what one may expect, the leverage ratio at year R is found to be not
related to the post-con…rmation outcome. In fact, as previously noted, the overwhelming majority of the …rms emerge from reorganization with very high level
of debts. According to Gilson (1997), one plausible explanation for the increase of
leverage ratios during reorganization is that reorganized …rms bene…t from the added
discipline and control that high leverage forces on management. This explanation
is consistent with the theoretical models of Jensen (1986) and Stulz (1990). We
205
believe that there are two additional explanations for the increase of leverage ratio.
First, the majority of bankrupt …rms faces liquidity problems and needs additional
funds to continue their activity and to meet the …rst payouts of reorganization plans.
Therefore, they raise additional debt which increases the leverage ratios during reorganization. Second, the French bankruptcy law encourages banks and suppliers to
give new loans to bankrupt …rms. These claims are known as “article 40”debts and
confer to their holders the privilege to be paid in priority.
6.6
Conclusion
This study contributes to a better understanding of the reorganization of bankrupt
…rms in France. It sheds further light on the performance of reorganized …rms and
on the factors that a¤ect their post-con…rmation outcome. Several conclusions and
observations can be drawn from this study.
First, we found that about 47% of the sample …rms …led again for bankruptcy.
Among these failing …rms 48% enter bankruptcy a second time within 2 years. It
seems that there is a bias towards the continuation of unpro…table …rms. The occurrence of Type I error is predictable because the French bankruptcy law is a debtororiented system (La Porta et al., 1998). However, although the French bankruptcy
system may buy poorly performing …rms some more time to survive, it does not
seem to allow many of them to ultimately escape liquidation.
Second, the examination of accounting measures of performance prior to …ling
and following con…rmation shows that reorganized …rms have improved their profitability during the bankruptcy process. This increase in pro…tability may be
explained by the measures taken by the Court, such as the automatic stay. The
second stylized fact lies in the very high leverage observed prior and several years
following the emergence from reorganization.
206
Third, …rms that continue to exist as an independent entity for at least four
years show better performance measures, prior to …ling and following con…rmation,
than …rms that …le again for bankruptcy. This …nding con…rms that the failure of
some reorganized …rms is partly due to their poor performance at the con…rmation
year. The results of regression analysis show that pre-…ling pro…tability and leverage
have no e¤ect on the reorganization outcome. They also show that larger …rms with
higher pro…tability and …rms operating in pro…table industries at the con…rmation
year are most likely to continue their operations for at least four years following
con…rmation.
We conclude with the extension that could be addressed to the present study.
In Section 6.5, the de…nition of a “successful”reorganization is somewhat arbitrary
and may di¤er across studies. In addition, the logistic model does not consider
information on the progress and the dynamics of the failure process. These problems
may be avoided by using survival analysis method. In the following chapter (Chapter
7), we will apply survival analysis to investigate the survival prospects of reorganized
…rms.
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210
Table 1 : Distribution of Failing Firms by Time to Second Bankruptcy
Time between emerging and second bankruptcy
N
Percentage
Cumulative
less than 1 year
more than 1 year and less than 2 years
more than 2 years and less than 3 years
more than 3 years and less than 4 years
more than 4 years and less than 5 years
more than 5 years and less than 6 years
more than 6 years
32
61
39
30
16
10
5
16.58%
31.61%
20.21%
15.54%
8.29%
5.18%
2.59%
16.58%
48.19%
68.39%
83.94%
92.23%
97.41%
100.00%
Table 2 : Accounting Measures of Performance prior and Following Confirmation
Year
F-3
F-2
F-1
F
R
R+1
R+2
R+3
(a)
N
65
91
114
120
122
108
89
70
Percentage
of firms
with NOI(a)
32.31%
39.56%
60.53%
60.83%
34.42%
30.55%
24.72%
24.28%
Profitability Measures
Operating Margin
Return on Assets
Mean
Median
Mean
Median
- 0.031
- 0.090*
- 0.497**
- 0.095***
- 0.040
0.016
0.082***
0.098**
0.042**
0.018
- 0.040***
- 0.031***
0.044***
0.053***
0.062***
0.081***
0.043
- 0.030
- 0.213***
- 0.156***
0.014
0.041
0.074***
0.082***
0.087**
0.033
- 0.058***
- 0.048***
0.053***
0.074***
0.086***
0.072***
Leverage
Mean
0.932
0.976
1.404
1.603
1.648
1.576
1.518
1.292
Median
0.881
0.932
1.127
1.375
1.217
1.114
1.068
0.914
NOI = Negative Operating Income
*, **, *** denote mean (median) significantly different from zero based on t-test (Wilcoxon test) at 10%, 5%, and 1% level, respectively.
62
82
104
109
112
99
69
39
F-3
F-2
F-1
F
R
R+1
R+2
R+3
- 0.117***
- 0.185***
- 0.634***
- 0.179***
- 0.104***
- 0.069*
- 0.006
0.013
Mean
- 0.029***
- 0.054***
- 0.127***
- 0.115***
- 0.036***
- 0.021*
0.005
- 0.007
Median
61.67%
78.75%
86.00%
82.86%
66.67%
58.16%
46.97%
54.05%
- 0.043
- 0.128***
- 0.309***
- 0.244***
- 0.074***
- 0.056
- 0.021
0.007
- 0.025
- 0.068***
- 0.167***
- 0.144***
- 0.042***
- 0.011
0.030
0.008
Median
54.10%
76.54%
79.21%
82.24%
66.36%
53.54%
46.38%
46.15%
< Industry(b)
Industry-adjusted Return on Assets
< Industry(a) Mean
Industry-adjusted Operating Margin
0.302***
0.335***
0.799***
0.998***
1.034***
0.977***
0.919***
0.507***
Mean
0.231***
0.239***
0.533***
0.710***
0.576***
0.464***
0.381***
0.264***
Median
Leverage
*, **, *** denote mean (median) significantly different from zero based on t-test (Wilcoxon signed rank test) at 10%, 5%, and 1% level, respectively.
(a)
Percentage of firms with operating margin lower than industry
(b)
Percentage of firms with return on assets lower than industry
(c)
Percentage of firms with leverage ratio higher than industry
N
Year
Industry-adjusted Profitability Measures
Table 3 : Industry-adjusted Measures of Performance Prior and Following Reorganization
83.87%
84.15%
94.23%
97.25%
94.64%
90.91%
88.41%
87.18%
> Industry(c)
212
Table 4 : Changes in Accounting Measures of Profitability
Variables
F-1 to R
R to R+1
R+1 to R+2
R+2 to R+3
Variation in operating margin
0.046***
0.012*
- 0.005
- 0.013
Percentage of positive variation
59.78%
56.07%
45.98%
35.82%
Variation in return on assets
0.057***
0.020
- 0.006
- 0.018
Percentage of positive variation
59.78%
58.88%
49.42%
38.80%
N
92
107
87
67
*, **, *** denote mean (median) significantly different from zero based on t-test (Wilcoxon signed rank test) at
10%, 5%, and 1% level, respectively.
Table 5 : Post-confirmation Profitability
Variables
Positive return on assets in at least one year (from R to R+2)
Positive return on assets in at least two years (from R to R+2)
Positive industry-adjusted return on assets in at least one year (from R to R+2)
Positive industry-adjusted return on assets in at least two years (from R to R+2)
N
Percentage
103
73
70
35
93.64%
74.49%
81.40%
41.18%
213
Table 6 : Measures of Performance by Reorganization's Outcome
Panel A : Performance measures at Year F-1
Mean
Median
Variables
Success
Failure
t-test
Success
Failure
Wilcoxon test
Operating Margin
Return on assets
Leverage
N
- 0.598
- 0.185
1.419
85
- 0.205
- 0.296
1.362
29
- 1.355
1.094
0.324
- 0.034
- 0.042
1.125
85
- 0.126
- 0.227
1.157
29
2.130**
2.300**
- 0.205
Industry-adjusted margin
Industry-adjusted ROA
Industry-adjusted leverage
N
- 0.749
- 0.278
0.819
75
- 0.288
- 0.401
0.737
25
- 1.428
1.111
0.433
- 0.112
- 0.130
0.504
75
- 0.171
- 0.315
0.607
25
1.453
2.298**
- 0.008
Panel B : Performance measures at Year R
Mean
Variables
Operating Margin
Return on assets
Leverage
N
Industry-adjusted margin
Industry-adjusted ROA
Industry-adjusted leverage
N
Median
Success
Failure
t-test
Success
Failure
0.016
0.041
1.659
101
- 0.202
- 0.087
1.594
21
- 0.065
- 0.052
1.044
89
- 0.262
- 0.166
0.990
21
Wilcoxon test
1.421
1.668
0.243
0.053
0.063
1.204
101
0.004
0.011
1.395
21
1.903*
1.835*
- 1.034
1.257
1.429
0.190
- 0.032
- 0.037
0.546
89
- 0.042
- 0.051
0.749
21
0.897
1.388
- 1.368
Panel C : Performance measures at Year R+1
Mean
Variables
Operating Margin
Return on assets
Leverage
N
Industry-adjusted margin
Industry-adjusted ROA
Industry-adjusted leverage
N
Median
Success
Failure
t-test
Success
Failure
Wilcoxon test
0.040
0.076
1.517
94
- 0.144
- 0.195
1.964
14
2.075*
1.432
- 0.703
0.081
0.085
1.070
94
- 0.002
- 0.005
1.226
14
3.085***
2.387**
- 1.518
- 0.050
- 0.023
0.909
86
- 0.190
- 0.276
1.419
13
1.472
1.217
- 0.754
- 0.010
- 0.003
0.441
86
- 0.035
- 0.065
0.771
13
2.079**
1.471
- 1.709*
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
214
Table 7 : Definition of Explanatory Variables
Variables
Definition
Firm size
Natural logarithm of total assets
Return on assets ratio
(Earnings before interest and taxes)/(total assets)
Liquidity ratio
(Current assets)/(current liabilities)
Leverage ratio
(Total liabilities)/(total assets)
Industry profitability
Industry average of the operating margin (based on the NES 114 level)(a)
(a)
Operating margin is defined as the operating income before depreciation and amortization over sales.
Table 8 : Determinants of Post-confirmation Outcome
(1)
(2)
Variables
Year F-1
Year R(b)
Intercept
- 3.8063
(3.2110)
- 7.7621**
(3.7743)
Firm size
0.2024
(0.2067)
0.4989**
(0.2501)
Return on assets ratio
0.6122
(0.5326)
3.6052***
(1.3772)
Liquidity ratio
0.3562
(0.4340)
0.4884
(0.3328)
Leverage ratio
0.5110
(0.3926)
0.5179
(0.3195)
Industry profitability
19.97**
(8.1773)
21.8556***
(8.3892)
N
Chi-Square
pseudo-R²
AIC
BIC
(a)
101
9.83*
0.0870
1.14
- 335.22
Standard errors in parentheses
(a)
The explanatory variables are measured at Year F-1
The explanatory variables are measured at Year R
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
(b)
110
18.07***
0.1685
0.92
- 399.66
Chapter 7
Survival of Reorganized Firms in France
7.1
Introduction
The design of bankruptcy procedures varies widely across the world, but most bankruptcy codes provide two basic types of procedures: liquidation and reorganization.
An e¢ cient bankruptcy system would encourage the reorganization of viable …rms
and eliminate non-viable ones. When the …rm is allowed to reorganize, a reorganization plan is designed to provide a course of action for the …rm to pay creditors and
return to a healthy status. In practice, many reorganized …rms need to restructure
again through a private workout or go into liquidation. This assessment had given
rise to many studies relating to various post-bankruptcy aspects.
Several articles have focused on measuring post-bankruptcy performance of reorganized …rms. Measures of performance were mainly based on (i) accounting measures such as the operating performance [Hotchkiss (1995), Denis and Rodgers
(2007), Kalay et al. (2007)] and the leverage ratio [LoPucki and Whitford (1993),
Gilson (1997)], (ii) the reorganized …rms’cash ‡ows [Hotchkiss (1995), Alderson and
Betker (1999)], and (iii) the stock performance of …rms emerging from bankruptcy
(Eberhart et al., 1999).
215
216
Another measure of performance was to investigate whether the surviving entity
remained out of bankruptcy after the con…rmation of the reorganization plan [LoPucki and Whitford (1993), Hotchkiss (1995), Gilson (1997), Denis and Rodgers
(2007)].
Other studies were concerned with determining the factors that in‡uence the
outcome or the performance of the reorganized entity. Casey et al. (1986) used
a probit model to classify Chapter 11 …rms that successfully reorganized against
those that liquidated. Using logistic regressions, Hotchkiss (1995) investigated on
factors related to worse post-bankruptcy performance. Denis and Rodgers (2007)
examined the impact of pre-Chapter 11 operating and …nancial characteristics and
changes in those characteristics on post-reorganization performance using logistic
regressions. In a recent study, Altman et al. (2009) extended the applicability of
bankruptcy prediction to …rms emerging from reorganization using a model based
on discriminant analysis.
While an abundant literature examined post-bankruptcy performance and reorganization outcome, little attention has been devoted to temporal issues associated
with the survival prospects of …rms emerging from bankruptcy. Furthermore, to our
knowledge, no literature in France has been devoted to the survival prospects of
the reorganized …rms. The purpose of this chapter is to address this lack of data
by applying survival analysis techniques to reorganized …rms in France. The study
has four objectives as follows. First, the study aims to model the progress and the
dynamic aspects of the failure process after the con…rmation of a reorganization
plan. Second, the study seeks to identify the determinants that accelerate or reduce
the time to failure of reorganized …rms using survival analysis techniques. Third,
the study compares a model with time-invariant covariates and a model with timevarying covariates. The basic idea underlying the use of time-varying covariates in
this study is that many of the predictors of …nancial distress change during the
217
period of time that precedes …nancial distress. Finally, the study provides information regarding survival probabilities at a given time horizon.
To achieve these objectives, we used a sample of 131 reorganized …rms that …led
for bankruptcy in the commercial Court of Paris between 2001 and 2004 and that
had their reorganization plan con…rmed. Then, we applied two survival analysis
techniques in the study: Kaplan-Meier technique was used to perform a descriptive
analysis, and the Cox regression model was used to explore the relative strength of
explanatory variables. There are two main reasons for the use of Cox model. First,
in contrast to most other survival analysis models, Cox model is a semi-parametric
approach which does not require a particular probability distribution to represent
survival times. Second, a key feature of Cox regression model is that it allows for
time-variation in the covariates which seems theoretically justi…ed when modeling
…nancial distress.
The remainder of this chapter is set out as follows. Section 7.2 reviews the classical
methodologies and the survival analysis techniques used in the area of …nancial
distress. Section 7.3 presents the survival analysis methodology putting the emphasis
on Kaplan-Meier technique and on Cox regression model. Section 7.4 describes the
data and the explanatory covariates used in the study. Section 7.5 presents the
empirical results. The …nal section of the chapter contains a summary and some
concluding remarks.
7.2
7.2.1
Literature review
Classic statistical methods versus survival analysis
The classic statistical methods based on cross-sectional data have been widely used
in the area of …nancial distress for the development of corporate failure predic-
218
tion models or for the identi…cation of covariates that distinguish distressed from
non-distressed …rms. The most popular classic methods include univariate analysis,
multivariate discriminant analysis (MDA), and conditional probability models.
Beaver (1966) developed the …rst failure prediction model using an univariate
discriminant analysis. This analysis involves the use of a single …nancial ratio in a
failure prediction model. Although the univariate analysis is extremely simple and
its application does not require any statistical knowledge, it shows some limitations
discussed, for example, by Altman (1968). On the one hand, the most e¤ective
predictor ratio may change across the studies. On the other hand, the univariate
nature of the method may lead to con‡icting predictions for di¤erent ratios on the
same …rm.
To overcome these problems, Altman (1968) pioneered the use of multivariate
discriminant analysis to predict company failure. The MDA technique is used to classify an observation into one of several a priori groups (bankrupt and non-bankrupt)
depending on the observations’characteristics. A score based on a linear combination
of independent predictors is calculated for each …rm. Then a cut-o¤ point is established to classify the observations. The main advantage of the MDA method is its
potential to combine the information of several predictors into a single score rather
than sequentially examining individual characteristics. However, the main criticism
of MDA lies in three restrictive assumptions. First, discriminant analysis requires
that the independent variables are multivariate normally distributed. Second, the
failing and non-failing groups have equal variance-covariance matrices. Third, prior
probabilities of the two groups and the misclassi…cation costs are speci…ed. The data
rarely satisfy the three assumptions and most MDA failure prediction studies do not
test their data against these assumptions. As a result, the MDA technique is often
applied in an inappropriate way and some questions raise about the conclusions and
generalizations resulting from the discriminant analysis.
219
To avoid the assumptions regarding prior probabilities of bankruptcy and/or
the distribution of predictors with respect to the MDA technique, Ohlson (1980)
pioneered the application of a logit analysis to bankruptcy failure prediction. The
logit model estimates the probability of occurrence of an outcome conditional on
a range of …rm characteristics. A score is created for each …rm based on a linear
combination of independent predictors and is converted into a probability value
using a cumulative logistic distribution function. In addition to logit analysis, probit
analysis has also been applied to bankruptcy failure prediction. The only di¤erence
is that probit analysis uses the cumulative standard normal distribution function
instead of the cumulative logistic distribution function. Thus, conditional probability
models are less demanding than MDA as regards assumptions.
However, there are some other common problems related to the use of the classic
statistical methods mentioned above. First, most classic methods assume a dichotomous dependent variable, i.e. the data set is assumed to be composed of two distinct
and separate populations (failed and non-failed …rms). In reality, corporate failure
is not a well-de…ned dichotomy (Balcaen and Ooghe, 2006). On the one hand, the
de…nition of failure itself is arbitrary and may di¤er across studies. On the other
hand, the failure de…nition is always applied to a certain arbitrary chosen year or
time period. Thus, the two populations are only mutually exclusive within the chosen
time period. Second, these kinds of cross-sectional models assume that the failure
process remains stable over time, which means that the distributions of the variables
involved in the model do not change over time, and there are stable inter-correlations
between the independent variables. This assumption is usually violated in the real
world (Luoma and Laitinen, 1991). For example, pooling data across di¤erent years
is popular because bankruptcy occurs infrequently. Thus, data instability may result
from changes in in‡ation, interest rates, business cycle, competitive nature of the
market, corporate strategy, and/or technology (Balcaen and Ooghe, 2006). Third,
220
the classic statistical models neglect the time dimension of failure. They assume
that failure is a steady state and do not consider information on the progress and
dynamics of the failure process (Luoma and Laitinen, 1991). By ignoring the fact
that …rms change through time, static models produce bankruptcy probabilities that
are biased and inconsistent (Shumway, 2001).
The problems associated with classic statistical models may be avoided by using
survival analysis method. The survival analysis uses survival time when calculating
the hazard rate to measure the risk to fail. It also permits the estimation of survival
probabilities in a given time which is an advantage in itself. According to Luoma
and Laitinen (1991), another advantage of survival analysis is that, contrary to
MDA and conditional probability models, it does not assume that failed and nonfailed …rms come from two distinct populations. Survival analysis rather assumes
that …rms come from the same population and treats non-failed …rms as censored
observations, i.e. their time of failure is not yet known. This assumption models the
failure process more accurately. Furthermore, survival analysis method resolves the
problems of static models by explicitly accounting for time and by allowing the use
of time-varying covariates to take into account the changes in explanatory variables
over time. Thus, survival analysis is more appropriate for modeling the dynamics of
failure process than static cross-sectional models. This also means that theoretically
survival analysis techniques are more consistent and accurate than are static models
[Luoma and Laitinen (1991), Shumway (2001)].
7.2.2
Review of survival analysis in …nancial distress
Existing studies that applied survival analysis in …nancial distress include studies
that use time-invariant covariates versus those that use time-varying covariates.
Early empirical research relied on static models by using one set of explanatory
221
variables at a point of time. Lane et al. (1986) …rst applied the static Cox proportional hazard model to predict bank failure in the U.S. They developed an early
warning model with one and two-year predictions for a selection of 334 successful
and 130 failed banks from the period 1979 to 1983. The authors found that the
prediction accuracy of the Cox model was comparable with discriminant analysis,
but it produced lower Type I errors. Whalen (1991) also used the static Cox model
to predict bank failures in the U.S. between 1987 and 1990. They measured the
covariates at the end of 1986. Luoma and Laitinen (1991) applied the Cox model
to business failure prediction using 36 Finnish failed limited companies and their
non-failed peers, and they compared the results with those of the discriminant and
logistic model. The comparison showed that survival analysis in the study sample
was outperformed by discriminant and also logistic analysis. Using a sample of 59
…rms from the period 1984-1993, Partington et al. (2001) developed a Cox model
to predict whether shareholders would receive any value upon a …rm’s exit from
Chapter 11 bankruptcy. Five explanatory variables were identi…ed as signi…cant:
company’s pro…tability, liquidity and market value in addition to two other covariates related to general economic factors. In a more recent study, Partington et al.
(2007) extended the previous study by incorporating additional data covering the
period from 1984 to 1996. They found that only two covariates of the original model
remain signi…cant: the covariates related to general economic factors.
Although the papers mentioned above assume that the values of the explanatory
variables remain constant over the time horizon, most of them acknowledge that a
dynamic model with time-varying covariates might provide a richer analysis than a
static model [Whalen (1991), Luoma and Laitinen (1991), Chen and Lee (1993)].
LeClere (2005) explicitly examined the e¤ect of covariate selection (time-invariant
versus time-varying) on the estimation of a Cox proportional hazards model using
a sample of …nancially and non-…nancially distressed …rms. The results indicate
222
that the proportional hazards model with time-varying covariates outperforms proportional hazards model with time-invariant covariates. In practice, the decision to
eliminate time dependence is principally related to the problem of data gathering.
In fact, when the covariates are time-invariant, only one observation is needed to
be gathered per subject and per covariate. However, when the covariates are timevarying, the data gathering process becomes more complicated. For each subject,
observations need to be made along the time path. Moreover, LeClere (2005) refers
to software limitations as a second reason for ignoring time dependence dimension
especially in past studies. Recent advances in software made the estimation of timevarying models less di¢ cult, and as a consequence many studies tend to use timevarying instead of time-invariant covariates when modeling the relationship between
duration dependence and covariates. For example, Helwege (1996) used a Cox timevarying model to identify the determinants of savings and loan failures. Wheelock
and Wilson (1995) also used a Cox time-varying model to examine the causes of
bank failure. Few years later, Wheelock and Wilson (2000) identi…ed the characteristics that make individual U.S. banks more likely to fail or to be acquired using
this time competing risks hazard model with time-varying covariates. More recently,
Brown and Dinc (2011) also used competing risks hazard model with time-varying
covariates to investigate on the Too-Many-to-Fail phenomenon in bank regulation.
7.3
Survival analysis methodology
There are three techniques in survival analysis: non-parametric, parametric and
semi-parametric models. The di¤erence between the three models lies in the assumption underlying the distribution of the survival data. Non-parametric models do not
impose that the data come from a speci…ed distribution and explanatory variables
cannot be used in these models. Parametric models assume that the distribution
223
of the survival data is known. Semi-parametric models do not require specifying
the distribution of the survival data. However, there is a parameterization of the
relationship between the explanatory variables and the survival or hazard function.
In what follows, we will present the basic concepts of survival analysis. Then, we
will focus on two survival analysis techniques that will be applied to the empirical
analysis: the Kaplan-Meier estimator and the Cox proportional hazards model. The
Kaplan-Meier method will be used to conduct a preliminary analysis of survival data
and to estimate the survivor function. The Cox model will be used to explore the
relationship between survival of the reorganized …rms and time-varying explanatory
variables.
7.3.1
Basic concepts
Survival analysis is a class of statistical methods concerned with studying the time to
the occurrence of an event (such as failure). A signi…cant feature of survival analysis
is that the event of interest may be not observed for all individuals. Such survival
times are termed right-censored times. A typical right censored data set includes
a variable which measures the time from a particular starting point to a certain
endpoint of interest and an indicator of whether the associated time is known or
right-censored. We usually use an indicator variable equal to 1 if the survival time
is known and equal to 0 for right-censored times.
There are two key functions in survival analysis called the survival function and
the hazard function. The survival function, S(t), gives the probability that the time
until the …rm experiences the event, T , is greater than a given time t. In other words,
the survival function represents the probability that a business will survive past a
certain time t. Given that T is a random variable which de…nes the event time for
some particular observation, then the survival function is de…ned as:
224
S(t) = P (T > t) = 1
(7.1)
F (t)
The survival function, given the probability of surviving to time t, is the complement of the cumulative distribution function de…ned as follows:
F (t) = P (T
Rt
t) = f (x)dx
(7.2)
0
The probability density function represents the unconditional instantaneous
probability that failure occurs in the period of time from t to t +
t per unit width
t. It is given by:
f (t) = lim
P (t
t!0
T <t+
t
t)
=
dF (t)
=
dt
S(t)
dt
(7.3)
Finally, the hazard function, h(t), gives the instantaneous risk that an event will
occur at time t given that the …rm survives to time t. The hazard function is also
known as the “hazard rate” because it also has the form of number of events per
interval of time. The hazard function is de…ned as:
h(t) = lim
t!0
P (t
T <t+
t
tjT
t)
=
f (t)
S(t)
(7.4)
The interpretation of the survival function and the hazard function is di¤erent,
but either one can be derived from the other.
7.3.2
Kaplan-Meier estimator
The K-M (1958) method is a strictly empirical non-parametric approach to survival
and hazard function estimation. As previously mentioned, non-parametric methods
do not impose that the data come from a speci…ed distribution. The K-M estimator
is de…ned as follows:
225
^ = Q ni
S(t)
t(i) t
di
ni
(7.5)
Where t1 denotes the …rst observed failure time, di represents the number of failures at time t, and ni indicates the number of individuals who have not experienced
the event of interest, and have also not been censored, by time t.
From equation (7.5), we notice that before the …rst failure happens, the survival
probability is always equal to 1. Once the failures occur, the K-M estimator of the
survival function decreases. A step function with jumps at the observed event times
will be obtained. The jumps on the survival curve would depend on the number of
failures observed as well as the number of censored observations before the event
time.
7.3.3
Cox proportional hazards model
Semi-parametric models do not require specifying the distribution of the survival
data. As far as time is concerned, these models are non-parametric, but because
we are still parameterizing the e¤ect of the covariates, there exists a parametric
component to the analysis. The most widely used semi-parametric regression model
for survival data is the Cox proportional hazards model proposed by Cox (1972).
Time-invariant Cox regression model
Cox’s hazards model with time-invariant covariates can be expressed as:
hj (tjxj ) = h0 (t) exp(xj )
(7.6)
hj (t) is the hazard function for …rm j at time t. h0 (t) is an arbitrary unspeci…ed
baseline hazard rate which measures the e¤ect of time on the hazard rate for an
individual whose all covariates are equal to zero. The baseline hazard is given no
226
particular parameterization and can be left unestimated. It represents the non parametric component of the model. exp(xj ) represents the parametric component of
the model where xj represents the vector of covariates that in‡uence the hazard and
is the vector of their coe¢ cients. We notice that the constant term is absorbed in
the baseline hazard.
The Cox regression model is a proportional hazards model because a key assumption of the model is that the hazard rates for two observations are proportional to one
another and that proportionality is maintained over time. In fact, although the Cox
model makes no assumption about the shape of the hazard over time, it assumes that
the shape is the same for every observation. Thus, if we consider two observations,
j and m, that di¤er in their x-values, the hazard ratio for these two observations is
expressed as follows:
exp(xj )
hj (tjxj )
=
hm (tjxm )
exp(xm )
(7.7)
which is constant given that the values of the covariates xj and xm do not change
over time.
Cox proportional hazards model is estimated with the method of maximum partial likelihood (Cox, 1972). Partial likelihood estimation allows the estimation of
the
parameter in equation (7.7) without requiring estimation of h0 . The partial
likelihood function is derived by taking the product of the conditional probability
of a failure at time ti given the number of cases that are at risk of failing at time ti .
The conditional probability that the j th case will fail at time ti is given by:
h0 (t) exp(xi )
exp(xi )
=P
j2R(ti ) h0 (t) exp(xj )
j2R(ti ) exp(xj )
Pr(tj = ti jR(ti )) = P
(7.8)
where R(ti ), the risk set, is de…ned as the set of observations that are at risk of
experiencing a failure at time ti .
227
Equation (7.8) expresses the hazard function for subject i at time ti , divided by
the cumulative hazard for all subjects at risk just before the occurrence of time ti .
h0 is eliminated since it is common to every term in the equation.
Taking the product of the conditional probabilities in (7.8) over all n …rms yields
the partial likelihood function:
Lp ( ) =
n
Q
i=1
"
exp(xi )
P
j2R(ti ) exp(xj )
# ci
(7.9)
where ci is the censoring indicator variable. ci is set to 1 if the failure time for
the ith subject is observed and to 0 if it is censored.
The corresponding log-partial-likelihood function is given by:
ln Lp ( ) =
n
P
i=1
2
ci 4xi
log
X
j2R(ti )
3
exp(xj )5
By maximizing the log-likelihood in (7.10), estimates of the
(7.10)
may be obtained.
An important thing to note in the partial likelihood function is that censored
cases contribute information only to the risk set (i.e. the denominator, not the
numerator).
Time-varying Cox regression model
In a time-varying model, the values of the covariates change with time, and therefore,
the model in equation (7.6) becomes:
hj (tjxj(t) ) = h0 (t) exp(xj(t) )
(7.11)
hj (t) is the hazard function for …rm j at time t. h0 (t) is an arbitrary unspeci…ed
baseline hazard rate. xj(t) denote the value of the covariates vector at time t for the
…rm j.
228
For each …rm j, we focus on each time interval for which data are available,
recording the start time of the interval (t0j ), the end time (tj ), whether or not
the event of interest occurred during the interval, and the values of all covariates
during the interval (xj ). Each time interval for each case constitutes an observation.
Contrary to the time-invariant case, we obtain a number of observations that may
exceed the number of studied cases.
In the time-varying case, equation (7.8) is modi…ed and the conditional probability that the j th case will fail at time ti is given by:
exp(xi(t) )
j2R(ti ) exp(xj(t) )
Pr(tj = ti jR(ti )) = P
(7.12)
where R(ti ) is the set of observations k that are at risk at time ti (i.e., all k such
that t0k < ti
tk ).
The partial likelihood function with time-varying covariates, can then be obtained
by taking the product of the conditional probabilities in (7.12) across all n …rms,
such that:
Lp ( ) =
n
Q
i=1
Estimates of the parameter
"
exp(xi(t) )
P
j2R(ti ) exp(xj(t) )
# ci
(7.13)
may be obtained by maximising the following
partial log-likelihood function obtained from equation (7.13):
ln Lp ( ) =
n
P
i=1
2
ci 4xi(t)
log
X
j2R(ti )
3
exp(xj(t) )5
(7.14)
Testing the proportional hazards assumption
One of the main assumptions of the Cox proportional hazards model is proportionality, i.e. the e¤ect of each covariate is the same at all point in time. The consequences
of non-proportionality include biased parameter values, incorrect standard errors
229
and biased estimates of the hazard rate. In this study, we will check proportionality
assumption by using the Schoenfeld and scaled Schoenfeld residuals.
The Schoenfeld residual for covariate xk ; k = 1 : : : K; and for observation j is:
rkj = cj (xkj
P
i2R(tj)
P
xki exp(xi ^ )
)
exp(xi ^ )
(7.15)
i2R(tj )
Grambsch and Therneau (1994) provide a method of scaling the Schoenfeld
residual. The rescaled residual is given by:
rskj = mV ar( ^ )rkj
(7.16)
where m is the number uncensored survival times.
The scaling provides that:
E(rskj +
k)
=
k (t)
Consequently, under the null hypothesis of proportional hazards, the rescaled
residuals plotted against time should show no slope.1
7.4
Data and explanatory variables
7.4.1
Data and sample
The event of interest in this study is de…ned as a reorganized company entering
into liquidation. Time to event or survival time is de…ned as the time spent from the
con…rmation date of the reorganization plan to the liquidation date of the reorganized
1 Stata
software automates this process and tests for individual and, globally, the null
hypothesis of zero slope. Speci…cally, we use the command “estat phtest”in Stata 10 after
the estimation of the Schoenfeld and scaled Schoenfeld residuals.
230
…rm or to the date on which the company was last observed as active.2 The sample
used in the study was drawn from the list of …rms that …led for reorganization
in the commercial Court of Paris between January 2001 and December 2004 and
that had their continuation plan con…rmed by the Court.3 The period was chosen
based mainly on …nancial data availability and on reforms timing.4 The district of
Paris was selected since it has the highest business …lings and for ease of access to
the data.5 Although the French bankruptcy Code provides …rms with two forms of
reorganization (the continuation of the bankrupt …rm as the same entity or the sale
of the …rm as a going-concern to another entity), we examine only those …rms that
reorganize through the framework of a continuation because post-con…rmation data
for acquired …rms are not available.
We excluded 44 …lings from the list because they relate to many …rms at the same
time. Therefore, we identify 415 …rms sample for which we have information on the
state of the case, the con…rmation date, and for …rms that have their plans cancelled,
we have information on the date on which the case was converted into liquidation.
Then, we collected manually from the …les the SIREN (Système Informatique pour le
Répertoire des ENtreprises) number of the …rms to extract …nancial and accounting
information from DIANE, our source for all accounting data.6 DIANE database
2 (i)Three
signi…cant dates are referred to frequently in this chapter: the …ling date, the
con…rmation date, and the liquidation date. The …ling date is the date on which formal
bankruptcy reorganization proceedings commence. The con…rmation date is the date on
which the continuation plan is con…rmed by the Court. The liquidation date is the date
on which the Court orders the cancellation of the plan and the reorganization proceedings
are converted into liquidation proceedings.
(ii) The date on which the companies’status was last observed is 1st July 2010.
3 The selection of the sample was facilitated by access to the list of commercial reorganizations in Paris by outcome (continuation/sale/liquidation) during the 2001-2004 period.
4 The study period follows the reform of 1994 and precedes the reform of 2005.
5 About 11% of the French bankrupt …rms had …led in the commercial Court Paris
during the study period (Source: www.insee.fr).
6 The SIREN number is an identi…cation number assigned to each commercial enterprise
or business in France. It was collected manually …le by …le in the commercial Court of Paris
because a list of reorganized …rms with the corresponding SIREN number was not available.
231
contains company accounts and …nancial ratios for the 1,500,000 companies in France
that published accounts in one of the 190 commercial Court registries.7
Among the 415 …rms contained in the sample, 172 are covered by DIANE database. For these …rms, we collected balance sheet and income statement data from
the …scal year of con…rmation through the last year available in the database. We
eliminate 41 …rms due to data limitations. Thus, the …nal sample consists of 131
…rms.
We also used ALISSE database to compute industry-adjusted measures of performance.8 The ALISSE database provides annual accounting data on an aggregated
basis for each economic activity sector. We classi…ed the sample cases among 114
industry sectors de…ned by the NES classi…cation.9 Then, for each industry sector,
we used the income statement and the balance sheet data provided by ALISSE
database to compute annual industry measures of performance.
7.4.2
Explanatory variables
Financial variables have long been widely used in predicting failure and …rm’s performance [Beaver (1966), Altman (1968), Ohlson (1980), Zavgren (1985), Luoma and
Laitinen (1991), Altman et al. (2009)]. The explanatory variables used in the empirical analysis are constructed based on the balance sheet and the income statement
data. These variables are chosen on the basis of their relevancy in the literature and
on their predictive success in previous research. They include …rm’s size, pro…tability,
liquidity, leverage, and industry pro…tability.
7 Unincorporated
…rms are not concerned with this formality.
access to ALISSE database is available at: www.alisse.insee.fr
9 The NES (Nomenclature Economique de Synthèse) classi…cation is the French aggregated economic classi…cation and it is comparable to the SIC (Standard Industry Classi…cation) in the U.S.
8 The
232
We use logarithm of total assets as the proxy for size of the company. Prior
research suggests that smaller …rms are more likely to fail than bigger …rms. We
measure return on assets ratio as the proxy for …rm’s pro…tability. This ratio is
particularly appropriate for studies dealing with corporate failure since it re‡ects
the earning power of the …rm’s assets. Firms with low pro…tability are more likely
to fail. The liquidity ratio is measured in this study as current assets divided by
current liabilities. This ratio assesses the …rm’s ability to meet its currents liabilities
as they become due. It is frequently considered as a diagnostic tool for identifying
…nancially distressed companies. Firms having liquidity problems are more likely to
fail. We use two measures for leverage in the present study. First, we examine the
leverage ratio measured as total debts divided by total assets. This ratio is often used
in predicting failure. Businesses with high total debt ratios are in danger of becoming
insolvent and going into liquidation. Second, as a proxy for …rm’s leverage, we use a
dummy variable that takes the value 1 if the …rm is “insolvent”, and zero otherwise.10
The choice of this variable is motivated by the study context. In fact, the sample
is composed of bankrupt …rms that are expected to have a large amount of debt.
The high-leverage dummy is expected to accelerate the failure process. Finally, we
introduced …rm’s industry pro…tability ratio; a …rm operating in pro…table industry
is expected to survive longer. An overview of the variables’ de…nitions and their
expected signs is contained in Table 1.
10 We
consider that a …rm is “insolvent” if it has more debts than assets, and “solvent”
otherwise.
233
7.5
7.5.1
Empirical implementation
Kaplan-Meier estimation
Table 2 summarizes what happens at each "survival time" in our data.11 The …rst
column (Time) is the time (measured in years) at occurrence of failure or censoring,
ti . The second column (At Risk) is the total number of …rms at risk of failure at time
ti . This number decreases progressively as the number of failures and the number
of censored observations are subtracted. The third column (Fail) is related to the
number of failures at that time. The fourth column (Censored) gives the number of
censored observations at that time. The …fth column (Prob. Fail) is the probability
of failure at time ti . It is computed as the number of failures at time ti (column 3)
divided by the number of …rms at risk (column 2). The censored …rms are dropped
from the total number of …rms at risk of failure in the next time without processing
the censored subject as having failed. The sixth column (Cond. Prob. Surv.) is the
(conditional) probability of survival beyond time ti given survival up until ti . It is
computed as the complement of the probability of failure (column 5). The seventh
column (Survival) represents the probability of survival from time 0 until ti . The
probability for the …rst row coincides with the survival probability during the …rst
interval. Subsequent probabilities are computed by multiplying the (conditional)
survival probability at time ti into the survival probability of the prior row. The
estimates of the statistical signi…cance are shown in the remaining column.
Table 2 shows that about 90% of the sample remained alive after t = 2:433
years (with a 95% con…dence interval of 0.83; 0.94). We may also notice that the
table shows the same survival probabilities for many successive times. The reason
11 Survival
time is de…ned as the time spent from the con…rmation date of the reorganization plan to the liquidation date of the reorganized …rm or to the date on which the
company was last observed as active.
234
is that there are many censored observations in the data. In fact, K-M estimate in
equation (7.5) operates only on observed failure times (and not on censoring times),
the conditional probability at censoring times is equal to 1 because the probability
of failure at censoring times is equal to 0, and consequently these probabilities are
ignored when calculating the survival probabilities. For example, the table reports
the same survival probability (68.25%) for many successive times (from t = 5:773 to
t = 6:310) because all the other times are related to censored observations. At the
end of the study, only about 60% of the sample …rms remained active (40% had been
liquidated). We can see this directly from a graph of the survivor function (Figure
1).
7.5.2
Cox model estimation
Time-varying versus time-invariant covariates models
The …rst question of interest in this subsection is to estimate Cox proportional
hazards models with time-invariant covariates and with time-varying covariates in
order to compare between them. For time-invariant Cox model, the covariates are
…xed at their values at the con…rmation year, whereas, for time-varying Cox model,
the covariates’values are measured at each "survival time".
Table 3 displays the estimation results of four Cox hazards models. Models (1)
and (2), in Panel A, are estimated with time-invariant covariates (measured at the
con…rmation year) while models (1’) and (2’), in Panel B, are estimated with timevarying covariates. The covariates used in the Cox regression models are the size, the
…rm’s pro…tability ratio, the liquidity ratio, the leverage ratio, the leverage dummy
variable, and the industry pro…tability. The di¤erence between the two models in
each panel lies in the variable used to measure the …rm’s leverage. In models (1)
235
and (1’) we used the debts-to-assets ratio whereas in models (2) and (2’), we used
high-leverage dummy variable.
For each model, we present the coe¢ cient estimation, the standard error of this
estimate, p-value for testing the null hypothesis that the coe¢ cient of each covariate
is equal to zero, and …nally the hazard ratio. The sign of a coe¢ cient gives an
indication of the directional e¤ect on the risk. A positive regression coe¢ cient for
an explanatory variable means that the hazard rate is higher, and thus the risk of
failing is higher. Conversely, a negative regression coe¢ cient implies a lower risk of
failing for …rms with higher values of that covariate.
After the estimation of the models, we checked proportionality assumption by
using the Schoenfeld and scaled Schoenfeld residuals (Grambsch and Therneau,
1994). The result of proportional hazards assumption testing is displayed in Table 4.
There is no evidence that our speci…cations violate the proportional hazards assumption.
We turn now to the comparison between time-invariant and time-varying models.
According to LeClere (2005), a direct comparison is not possible. First, there are no
statistical tests that allow for such comparison. Second, the models are not nested
which makes di¢ cult a comparison of the incremental contribution of one model
relative to the other. Third, the proportional hazards model provides no statistic
that compares indices of explained variance like for example, the OLS R2 . For these
reasons, the comparison of the models will be restricted to examining the sign and
the signi…cance of the estimates, and the overall …t of the models.
To compare between time-invariant and time-varying models, we should compare
models with the same covariates. Consequently, we will compare Model (1) to Model
(1’), on the one hand, and Model (2) to Model (2’), on the other hand. As shown
in Table 3, models (1) and (1’), respectively models (2) and (2’), show that all
236
parameters have the expected signs except for leverage ratio covariate which is not
signi…cant in both models (1) and (1’).
By considering the p-value, both time-invariant models (Panel A) show that there
is only one covariate that has a signi…cant e¤ect on the risk of failing. This covariate
is …rm’s pro…tability and is highly signi…cant at the 1% level. The negative sign of
the coe¢ cient indicates that the more pro…table a …rm at the con…rmation year,
the lower the probability that it will fail at a given point of time. On the other
hand, time-varying models (Panel B) show more signi…cant variables in explaining
failure risk. Three of the covariates in Model (1’) and four of the covariates in Model
(2’) are signi…cant and the sign of their coe¢ cients are consistent with theoretical
predictions.
Table 3 also presents the partial likelihood ratio test and the associated signi…cance. This test compares the log partial likelihood for a model without covariates
where all coe¢ cients are simultaneously equal to zero, Lp (0), and the log partial
likelihood for the full model with covariates, Lp ( ^ ). The test statistic is calculated
as follows:
G=
It is compared with a
2
2(Lp (0)
Lp ( ^ ))
distribution. The models with time-varying covariates
have the largest test statistic. It is signi…cant at the 5% level for time-invariant
models while it is highly signi…cant at the 1% level for time-varying models. Nevertheless, this result does not imply that time-varying models are better than timeinvariant models because models (1) and (1’) or models (2) and (2’) are not nested
and, therefore, a direct comparison based on the partial likelihood test statistics
cannot be made. The only conclusion that can be drawn from the partial likelihood
test is that the improvement of the full model over the model without covariates is
237
greater for time-varying models. In this sense, models in Panel B can be considered
more appropriate than models in Panel A.
Additionally, Table 3 reports the pseudo-R2 of the Cox models. The pseudo-R2 is
not measured in terms of variance but quanti…es a proportion in terms of the partial
log likelihood. It indicates how useful the explanatory variables are in predicting the
response variable. The pseudo-R2 , is de…ned as:
pseudo-R2 = 1
Lp ( ^ )
Lp (0)
Time-varying models have the largest pseudo-R2 (0.1064 versus 0.0370 and 0.1139
versus 0.0349) indicating that they o¤er the largest improvement against the model
without covariates.
Table 3 also presents the Akaike Information Criterion (AIC) and the Bayesian
Information Criterion (BIC) statistics. These measures are popular for comparing
maximum likelihood models. AIC and BIC are de…ned as:
AIC =
BIC =
2 Lp ( ^ ) + 2 k
2 Lp ( ^ ) + ln(N ) k
where k is the number of parameters in the model and N is the number of …rms.
Since the number of …rms and the number of parameters is the same, the AIC and
BIC statistics will depend on the partial likelihood test statistics. Based on these
criteria, time-varying models are considered better than time-invariant model since
they show smaller values of AIC and BIC. For example, BIC statistic value is equal
to 369.16 in Model (2) and 302.01 in model (2’).
Overall, time-varying models provide more statistically signi…cant coe¢ cients
with the expected signs and a better …t. This result is consistent with the …ndings of
238
LeClere (2005). This latter invokes two potential problems resulting from the treatment of time-varying covariates as invariant. First, the value of many covariates
may change during time that precedes the event. Thus, the use of time-invariant
covariates eliminates the variation in the covariates and important information is
lost. Second, many phenomena are generated by dynamic, longitudinal processes.
The value of a covariate along the time a¤ects the probability of the event occurrence, and consequently the decision to eliminate the time dependence may result
in incorrect modeling or speci…cation error.
Cox regression model with time-varying covariates
The results of comparison suggest that a model with time-varying covariates is more
appropriate than a model with time-invariant covariates. Consequently, in what follows more attention will be paid to Cox regression models in Panel B (Table 3).
Interpreting estimation results
The estimation results show that the covariates related to …rm’s pro…tability,
liquidity, and industry’s pro…tability are statistically signi…cant in both models (1’)
and (2’) and have the expected signs. Moreover, the coe¢ cient on …rm’s size is not
signi…cant for both models while the leverage variable is signi…cant only for Model
(2’). Precisely, …rm’s leverage does not have an impact on the risk of failing when it
is measured as a debts-to-assets ratio, but it has an impact when it is measured as
a dummy variable. This …nding suggests that leverage has a threshold e¤ect on the
risk of failing. Our interpretation for this …nding lies in the speci…city of the sample
used in the study. In fact, the sample is exclusively composed of bankrupt …rms. An
important stylized fact is that leverage ratios of bankrupt …rms in France, remain
very high at the con…rmation year and even the years following the con…rmation. In
239
the previous chapter (Chapter 6), the results report an average (median) value of
leverage ratio equal to 1.648 (1.217) at the con…rmation year.12
Therefore, a decrease in the leverage ratio following con…rmation from 1.1 to 0.9,
for example, may have a signi…cant impact for those reorganized companies because
the …rm will move from an “insolvent”entity to a “solvent”one. This change would
be perceived as a positive signal about the …rm’s future prospects.
Table 3 also shows that Model (2’) has higher values for partial likelihood ratio
test and pseudo-R2 and lower values for AIC and BIC criteria than Model (1’)
con…rming that Model (2’) is preferred to Model (1’). Consequently, in what follows
we will focus on the estimation results of Model (2’).
Although the signs of coe¢ cients indicate the directional impact of an increase
in coe¢ cients on risk, the magnitudes of the coe¢ cients are not so easy interpreted.
For this reason, we choose to interpret the hazard ratios obtained by exponentiating
the coe¢ cients, which is more straightforward.
The coe¢ cient of …rm’s pro…tability is highly signi…cant and has a negative sign
which means that an increase in pro…tability decreases the risk of failing. Precisely, a
10% increase in pro…tability decreases the risk of failing by 11.6%.13 Similarly, a 10%
increase in liquidity ratio decreases the risk of failing by 10.95%.14 The coe¢ cient on
leverage dummy variable is signi…cantly positive. It means that a 1-unit increase in
this covariate moves the …rm from having less debts than assets (leverage dummy=0)
to having more debts than assets (leverage dummy=1). The reported hazard ratio
for the leverage dummy is equal to 2.4524, meaning that an “insolvent” …rm faces
a risk 2.538 times greater than a “solvent” …rm. In the same way a “solvent” …rm
12 See
Section 6.4.2 of Chapter 6 for more details.
hazard ratio corresponding to an increase of 10 units in the covariate xprof itability
is obtained by exp(10 ^ prof itability ) = 0:8839:
14 The hazard ratio corresponding to an increase of 10 units in the covariate x
liquidity is
^
obtained by exp(10
liquidity ) = 0:8905:
13 The
240
faces a risk 0.4077 lower than an “insolvent” one.15 Finally, a 1% increase in the
…rm’s industry pro…tability decreases the risk of failing by 10.83%.
Risk scores and survival probabilities
Once the model has been estimated, a time-varying risk score de…ned as (xi(t) ^ )
can be calculated for each …rm by time horizon t, where t varies from one year to nine
years after the plan’s con…rmation. ^ is the vector of estimated coe¢ cients shown in
Table 3 and xi(t) is the vector of covariates for a given …rm at time t. According to
equation (7.11), the larger the value of the risk score, the higher the risk of failing
is.
Figure 2 presents the relationship between the risk score and time by …rm status,
“active”or “failing”. For the time horizon t, active …rms are de…ned as reorganized
…rms that have survived up to year t + 1, while failing …rms are de…ned as …rms
that have failed between year t and year t + 1. Following Chancharat et al. (2007),
the risk scores shown in this graph were produced by averaging the estimated risk
scores for each year by …rm status. As expected, Figure 2 shows that the risk scores
of failing companies are higher than active companies at every time horizon.
As noted in Section 7.3, the survival function represents the probability that
a business will survive past a certain time t. Survival probabilities can be easily
generated using the above estimated risk scores. Figure 3 presents the survival function of an average business. Speci…cally, the survival probabilities used to create this
graph were calculated by averaging the estimated survival probabilities at every time
horizon. This graph reveals a linear decline in the survival rate of a …rm over the …rst
four years following plan’s con…rmation. During this period the survival probability
of a …rm reduces by approximately 2.5% each year. Then, the survival probability
15 The
hazard ratio corresponding to a 1-unit decrease in the dummy variable xleverage
is obtained by exp( ^ leverage ) = 0:4077.
241
reduces by more than 10% from the fourth year to the …fth year. However, after …ve
years the survival probability does not drop signi…cantly and it is still reasonably
high. This means that assuming a business has survived for …ve years or more, the
likelihood it will fail in the near future is low. One can notice that the failure process
of a reorganized …rm in France is similar to the failure process of a new …rm which
takes at least …ve years to be considered as an established …rm, and therefore much
less likely to fail than a new …rm.
Finally, in Figure 4 we present the survival functions for a typical active …rm
and a typical failing …rm. Speci…cally, the survival functions shown in the graph are
produced by averaging the estimated survival probability by …rm status, "active" or
"failing". Refer to this …gure, the top curve depicts the survival pro…le for a typical
active …rm whereas the bottom curve shows the survival pro…le for a typical failing
…rm. As expected, the survival probabilities of failing …rms are lower than active ones
at every time horizon. In fact, the values of explanatory variables used to estimate
the risk score in Figure 2 are indicative of higher risk and greater likelihood of failure
for failing …rms relative to active ones which explain lower survival probabilities for
this group of …rms. Moreover, the vertical distance between the two curves represents
the estimated reduction in survival probability for the failing …rms relative to the
active ones at every time horizon.
7.6
Conclusion
This chapter contributes to the existing literature on corporate …nancial distress
in several ways. First, using a sample of reorganized …rms at a particular commercial Court in France, the study examines the future prospects of reorganized
…rms using survival analysis techniques. The logic behind this methodology is that
a model used to detect corporate distress, might also be e¤ective in assessing the
242
risk of failing of reorganized …rms. Second, the study determines the in‡uence of
…nancial factors on the risk of failing of reorganized …rms using two types of Cox
models: time-invariant models versus time-varying models. The estimation results of
time-invariant models show that only …rm’s pro…tability (measured at the con…rmation year) has a signi…cant positive e¤ect on the survival of the reorganized …rms.
On the other hand, the estimation of time-varying models identi…es four signi…cant
explanatory variables. Three of these covariates have a positive e¤ect on survival
including the company’s pro…tability, liquidity, and the industry pro…tability while
the leverage has a negative e¤ect. The results, however, do not support the importance of the company’s size. Third, evidence suggests that leverage has a threshold
e¤ect. Precisely, …rm’s leverage does not have an impact on the risk of failing when
it is measured as a debts-to-assets ratio, but it has an impact when the …rm’s status
moves from “solvent”to “insolvent”entity and vice-versa. One possible explanation
lies in the speci…city of the sample used in the study which is exclusively composed
of bankrupt …rms. Fourth, relative to time-invariant covariates model, time-varying
covariates model provide a better …t and has more statistically signi…cant coe¢ cients
with the expected signs. The superiority of time-varying model is predictable since
a dynamic model that takes into account the progress of the reorganization process
and the change of …rm’s characteristics over time is more appropriate than a static
model. Finally, Cox model with time-varying covariates provides the survival probability for reorganized …rms in a given time. The survival function suggests that the
failure process of a reorganized …rm in France is similar to the failure process of a
new …rm. Once the …rm has survived for …ve years or more, the likelihood it will fail
in the near future becomes low.
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Table 1 : Definition of Variables and Expected Signs
Exp. Sign(a)
Variables
Definition
Firm size
Natural logarithm of total assets
-
Profitability ratio (%)
Return on assets ratio(b)
-
Liquidity ratio (%)
(Current assets)/(current liabilities)
-
Leverage ratio (%)
(Total liabilities)/(total assets)
+
High-leverage dummy
Dummy variable, equal to 1 if the firm's leverage ratio exceeds 1
+
(b)
Industry profitability (%) Industry average of return on assets ratio (based on the NES 114 level)
(a)
(b)
-
A positive (negative) sign implies an increase (a decrease) in the risk of failing.
Return on assets is defined as the operating income before depreciation and amortization over assets.
Table 2 : Kaplan-Meier Estimation
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Time
At Risk
Fail
Censored
Prob. Fail
Cond. Prob. Surv.
Survival
[95% Conf. Int.]
0.709
131
1
0
0.0076
0.9923
0.9923
0.9471
0.9989
0.868
130
1
0
0.0076
0.9923
0.9847
0.9403
0.9962
0.983
129
1
0
0.0077
0.9922
0.9770
0.9307
0.9926
1.337
128
1
0
0.0078
0.9921
0.9694
0.9207
0.9884
1.381
127
1
0
0.0078
0.9921
0.9618
0.9107
0.9839
1.474
126
1
0
0.0079
0.9920
0.9541
0.9009
0.9792
1.496
125
1
0
0.0080
0.992
0.9465
0.8912
0.9742
1.822
124
1
0
0.0080
0.9919
0.9389
0.8816
0.9690
1.860
123
1
0
0.0081
0.9918
0.9312
0.8721
0.9636
2.104
122
1
0
0.0081
0.9918
0.9236
0.8628
0.9582
2.301
121
1
0
0.0082
0.9917
0.9160
0.8535
0.9526
2.425
120
1
0
0.0083
0.9916
0.9083
0.8443
0.9469
2.433
119
1
0
0.0084
0.9915
0.9007
0.8352
0.9411
2.597
118
1
0
0.0084
0.9915
0.8931
0.8262
0.9353
2.721
117
1
0
0.0085
0.9914
0.8854
0.8173
0.9293
2.814
116
1
0
0.0086
0.9913
0.8778
0.8084
0.9233
2.912
115
1
0
0.0086
0.9913
0.8702
0.7996
0.9172
3.315
114
1
0
0.0087
0.9912
0.8625
0.7908
0.9111
3.411
113
1
0
0.0088
0.9911
0.8549
0.7821
0.9049
3.458
112
1
0
0.0089
0.9910
0.8473
0.7734
0.8987
3.512
111
1
0
0.0090
0.9909
0.8396
0.7648
0.8924
3.641
110
1
0
0.0090
0.9909
0.8320
0.7563
0.8860
3.959
109
1
0
0.0091
0.9908
0.8244
0.7477
0.8797
3.970
108
0
2
0
1
0.8244
0.7477
0.8797
3.986
106
1
0
0.0094
0.9905
0.8166
0.7390
0.8731
248
Table 2 : Kaplan-Meier Estimation (continued)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Time
At Risk
Fail
Censored
Prob. Fail
Cond. Prob. Surv.
Survival
[95% Conf. Int.]
4.008
4.014
4.038
4.047
4.085
4.123
4.126
4.129
4.142
4.159
4.186
4.195
4.197
4.244
4.438
4.458
4.493
4.526
4.564
4.592
4.603
4.660
4.685
4.688
4.699
4.745
4.756
4.764
4.784
4.986
5.014
5.025
5.044
5.047
5.052
5.071
5.101
5.145
5.197
5.200
5.236
5.321
5.326
5.332
5.337
5.375
5.378
5.425
5.427
5.529
5.581
5.584
105
104
103
102
101
99
97
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81
80
79
78
77
76
75
74
73
72
71
70
69
68
67
65
64
61
60
59
58
57
56
55
54
53
52
51
50
49
1
0
1
0
0
0
0
0
0
1
1
1
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
0
0
1
1
0
0
0
0
1
0
0
0
0
0
1
0
1
2
2
1
1
1
0
0
0
0
1
1
1
1
1
1
1
1
0
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
3
1
1
0
0
1
1
1
1
0
1
1
1
1
0.0095
0
0.0097
0
0
0
0
0
0
0.0106
0.0107
0.0108
0.0109
0
0
0
0
0
0
0
0
0.0121
0
0
0
0
0
0.0131
0
0
0
0
0
0
0
0
0.0149
0
0
0
0
0.0169
0.0172
0
0
0
0
0.0188
0
0
0
0
0.9904
1
0.9902
1
1
1
1
1
1
0.9893
0.9892
0.9891
0.9890
1
1
1
1
1
1
1
1
0.9878
1
1
1
1
1
0.9868
1
1
1
1
1
1
1
1
0.9850
1
1
1
1
0.9830
0.9827
1
1
1
1
0.9811
1
1
1
1
0.8088
0.8088
0.8010
0.8010
0.8010
0.8010
0.8010
0.8010
0.8010
0.7924
0.7839
0.7754
0.7669
0.7669
0.7669
0.7669
0.7669
0.7669
0.7669
0.7669
0.7669
0.7575
0.7575
0.7575
0.7575
0.7575
0.7575
0.7476
0.7476
0.7476
0.7476
0.7476
0.7476
0.7476
0.7476
0.7476
0.7364
0.7364
0.7364
0.7364
0.7364
0.7239
0.7114
0.7114
0.7114
0.7114
0.7114
0.6980
0.6980
0.6980
0.6980
0.6980
0.7304
0.7304
0.7217
0.7217
0.7217
0.7217
0.7217
0.7217
0.7217
0.7121
0.7025
0.6931
0.6836
0.6836
0.6836
0.6836
0.6836
0.6836
0.6836
0.6836
0.6836
0.6731
0.6731
0.6731
0.6731
0.6731
0.6731
0.6618
0.6618
0.6618
0.6618
0.6618
0.6618
0.6618
0.6618
0.6618
0.6488
0.6488
0.6488
0.6488
0.6488
0.6340
0.6194
0.6194
0.6194
0.6194
0.6194
0.6035
0.6035
0.6035
0.6035
0.6035
0.8666
0.8666
0.8599
0.8599
0.8599
0.8599
0.8599
0.8599
0.8599
0.8528
0.8455
0.8383
0.8310
0.8310
0.8310
0.8310
0.8310
0.8310
0.8310
0.8310
0.8310
0.8231
0.8231
0.8231
0.8231
0.8231
0.8231
0.8147
0.8147
0.8147
0.8147
0.8147
0.8147
0.8147
0.8147
0.8147
0.8055
0.8055
0.8055
0.8055
0.8055
0.7954
0.7852
0.7852
0.7852
0.7852
0.7852
0.7742
0.7742
0.7742
0.7742
0.7742
249
Table 2 : Kaplan-Meier Estimation (continued)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Time
At Risk
Fail
Censored
Prob. Fail
Cond. Prob. Surv.
Survival
[95% Conf. Int.]
5.699
5.704
48
47
0
0
1
1
0
0
1
1
0.6980
0.6980
0.6035
0.6035
0.7742
0.7742
5.723
5.773
5.781
5.855
5.868
5.951
6.003
6.022
6.027
6.099
6.107
6.142
6.162
6.184
6.258
6.310
6.386
6.411
6.463
6.540
6.660
6.663
6.671
6.718
6.721
6.890
7.101
7.118
7.134
7.189
7.247
7.252
7.282
7.329
7.479
7.564
7.622
7.737
7.753
8.016
8.074
8.156
8.293
46
45
44
43
42
41
40
39
38
36
35
34
33
32
31
30
29
28
27
25
24
23
22
21
20
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
1
1
1
1
1
2
1
1
1
1
1
1
1
0
1
2
1
0
1
1
0
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0.0222
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.0344
0
0
0
0.0416
0
0
0.0476
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0.9777
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.9655
1
1
1
0.9583
1
1
0.9523
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.6980
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6825
0.6590
0.6590
0.6590
0.6590
0.6315
0.6315
0.6315
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6015
0.6035
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5847
0.5526
0.5526
0.5526
0.5526
0.5149
0.5149
0.5149
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.4748
0.7742
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7620
0.7459
0.7459
0.7459
0.7459
0.7275
0.7275
0.7275
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
0.7068
250
Table 3 : Cox Proportional Hazards Models Estimation
Panel A : Time-invariant covariates (measured at the confirmation year)
Model (1)
Model (2)
Covariate
Coefficient
SE(a)
p-value
HR(b)
Coefficient
SE
p-value
HR
Size
- 0.1864
0.1410
0.186
0.9981
- 0.1204
0.1364
0.377
0.9987
Firm Profitability
- 0.0166***
0.0062
0.008
0.9835
- 0.0135***
0.0052
0.009
0.9865
- 0.0025
0.0020
0.234
0.9975
0.1202
0.4309
0.780
1.1277
- 0.0496
0.0488
0.309
0.9515
Liquidity Ratio
- 0.0028
0.0021
0.178
0.9971
Leverage Ratio
- 0.0011
0.0012
0.386
0.9988
- 0.0422
0.0494
0.393
0.9585
High-Leverage Dummy
Industry Profitability
Number of firms
131
131
Number of observations
131
131
Partial LR test
13.24**
12.48**
Probability >Chi2
0.0213
0.0287
pseudo-R²
0.0370
0.0349
AIC
354.04
354.79
BIC
368.41
369.16
Panel B : Time-varying covariates
Model (1')
Covariate
Coefficient
SE
p-value
Model (2')
HR
Coefficient
SE
p-value
HR
Size
- 0.1853
0.1305
0.156
0.9981
- 0.0415
0.1378
0.763
0.9995
Firm Profitability
- 0.0178***
0.0069
0.010
0.9822
- 0.0123**
0.0049
0.013
0.9877
- 0.0115**
0.0048
0.017
0.9884
0.8970*
0.5241
0.087
2.4524
- 0.1145**
0.0533
0.032
0.8917
Liquidity Ratio
- 0.0143***
0.0048
0.003
0.9857
Leverage Ratio
- 0.0011
0.0012
0.354
0.9988
High-Leverage Dummy
Industry Profitability
- 0.1084**
0.0520
0.037
0.8972
Number of firms
131
131
Number of observations
448
448
Partial LR test
33.34***
35.72***
Probability >Chi2
0.0000
0.0000
pseudo-R²
0.1064
0.1139
AIC
290.01
287.63
BIC
304.39
302.01
(a)
(b)
SE= Standard Error
HR= Hazard Ratio
* significant at 10% level, ** significant at 5% level, *** significant at 1% level
251
Table 4 : Testing the Proportional Hazards Assumption
Covariate
(1)
(2)
(1')
(2')
Size
0.0341
(0.8443)
0.0358
(0.8195)
- 0.0606
(0.7863)
- 0.1426
(0.4281)
Firm Profitability
- 0.0967
(0.8140)
- 0.0629
(0.6859)
0.1281
(0.4919)
0.0464
(0.8109)
Liquidity Ratio
0.0967
(0.6200)
0.1098
(0.6129)
- 0.1062
(0.5896)
- 0.1619
(0.4052)
Leverage Ratio
0.0768
(0.7289)
High-Leverage Dummy
0.1510
(0.4689)
0.0576
(0.7016)
- 0.1284
(0.4083)
Industry Profitability
0.2345
(0.1173)
0.2335
(0.1161)
0.0877
(0.7147)
0.1535
(0.5082)
Global test
(0.6944)
(0.7211)
(0.8317)
(0.7787)
p-value in parentheses
252
0.00
Survival Probability
0.25
0.50
0.75
1.00
Figure 1: Kaplan-Meier Survival Estimate
0
2
4
Time (Years)
6
8
-2
-1
Risk Score
0
1
2
Figure 2 : Graph of Risk Scores by Firm Status
1
2
3
4
5
6
Survival T ime (Years)
Active
7
Fai ling
8
9
253
.6
.7
Survival Probability
.8
.9
1
Figure 3 : Graph of Survival Function
1
2
3
4
5
6
Survival Time (Years)
7
8
9
.4
Survival Probability
.6
.8
1
Figure 4 : Graph of Survival Function by Firm Status
1
2
3
4
5
6
Survival Ti me (Years)
Active
7
Faili ng
8
Conclusion
This thesis focuses on examining the reorganization of bankrupt …rms in France.
On the one hand, we study the particularity of the French bankruptcy law which
consists in providing bankrupt …rms with two forms of reorganization (continuation
as the same entity or sale as a going-concern). On the other hand, we examine the
French bankruptcy system e¢ ciency by assessing the performance of the reorganized
…rms in three ways. First, we investigate the consummation of the reorganization
plans. Second, we assess accounting measures of performance. Third, we investigate
the survival prospects of the reorganized …rms.
Five main essays are developed and presented in Chapters 3, 4, 5, 6, and 7. The
details of these chapters can be summarized as follows.
Chapter 3 contributes to a better understanding of the reorganization of bankrupt …rms in France by providing a description of an original data set of 500 …rms
which …led for reorganization under the French bankruptcy Code during the 19952004 period and that had led to the con…rmation of a reorganization plan within
the framework of a continuation or a sales plan. The data reported in this chapter
were manually collected from a speci…c commercial Court in France during the early
stages of this thesis.
The sample is marked by its diversity; it includes a large number of small businesses and a small number of large businesses. The study also shows that …rms which
reorganize via sale are signi…cantly larger than …rms that continue as the same entity.
254
255
Although the French bankruptcy law encourages alert procedures and provides
extra-judicial reorganization measures to detect any problems within the company
as soon as possible, the study reveals that bankrupt …rms are highly levered when
they enter the bankruptcy process suggesting that …rms …le too late for bankruptcy.
The …gures suggest that the …rst priority of judges is to maintain the …rm in
activity to preserve employment, come then the reimbursement of creditors. First,
data speci…c to continuations show that the Court con…rms continuation plans that
last several years and whose …rst repayments to creditors are very low. Moreover,
the payo¤ rate to creditors was very low for failing continuation plans. Second, data
speci…c to sales report low sale prices and low payo¤ rate to creditors.
The most frequently listed reasons for bankruptcy are those related to the
"external business environment", the "internal operations of the business", and
those related to "…nancing". In addition, data show some di¤erences among the two
forms of reorganization. Overall, "…nancing problems" and "business operations and
management" are mentioned more often in continuation cases whereas "personal
problems" and "strategy" are listed much more often in sales cases.
Finally, the study shows that the French bankruptcy system provides a rapid
solution to bankrupt …rms. However, the implementation of this solution takes much
more time especially for continuations.
Chapter 4 investigates the factors that in‡uence the reorganization form (continuation versus sale) using an original data set. In the French context, Blazy et al.
(2011) compare …rms that are reorganized (within the framework of a continuation
or a sale) relative to those that are liquidated. To our knowledge, our study is the
…rst to compare …rms that reorganize as the same entity and those that are acquired
256
by another …rm as a going-concern in the French context.16 The regression results
indicate that larger …rms are more likely to be acquired. Our …rst interpretation to
this result is that buyers are interested in larger …rms. Our second interpretation
is that the Court may face a real dilemma when a large …rm cannot continue its
operations and includes many employees. In such conditions, it may prefer ordering
the sale of the bankrupt …rm instead of liquidating it to avoid massive layo¤s.
The study reveals that …rms that are more pro…table are more likely to emerge
as independent entities. Thus, sale alternative is chosen in the less favorable cases,
i.e. when the …rm is unable to generate su¢ cient cash ‡ow to reimburse its creditors
which is consistent with the objectives of the French bankruptcy law.
The results also show that the higher the value of secured debt to assets ratio
is, the less likely the bankrupt …rm will continue as the same entity. This result can
…nd its explanation in the fact that creditors refuse to take additional risk.
Moreover, the probability of reorganizing in the same entity increases in the
fraction of intangible assets in the …rm’s industry because the value of these assets
may be dissipated in sales.
Finally, the results provide strong support for the importance of the causes of
default in determining the reorganization form. Particularly, …rms su¤ering from
"personal problems" are more likely to be sold whereas …rms having "…nancing"
and/or "business operations and management" problems are more likely to continue
their activity as the same entity.
Chapter 5 contributes to the existing literature on bankruptcy in the French
context by addressing the issue of plans’consummation. Speci…cally, we use a sample
16 Blazy
R., Chopard B., Fimayer A., and Guigou J.D. (2011), “Employment Preservation
vs. Creditors’Repayment under Bankruptcy Law : the French Dilemma ?”, International
Review of Law and Economics, Vol. 31, No. 2, pp. 126-141.
257
of …rms that …led for reorganization between 1995 and 2004 and that had their continuation plan con…rmed by the commercial Court of Paris. The study reveals that
only 44% of con…rmed cases result in a consummated plan. The poor consummation rate supports the view that the French bankruptcy system is biased towards the
reorganization of unpro…table …rms. First, the Court maintains the original management in most cases which may result in ine¢ cient decisions. Second, the Court often
con…rms continuation plans that last for many years suggesting that the reorganized
…rms are not enough pro…table to meet the …nancial requirements of a short plan. In
the end, although the French bankruptcy system may buy poorly performing …rms
some more time to survive, it does not seem to allow many of them to ultimately
escape liquidation.
Additionally, empirical results indicate that the probability of plans’consummation increases with the age of the …rm, the percentage of the plan’s …rst payout, the
relative size of banking claims, the …rms’industry pro…tability, and the presence of
"accidental problems". In particular, the percentage of the …rst payout to creditors
re‡ects the …rm’s ability to generate cash ‡ow and its rapidity in resolving the …nancial crisis. Besides, even if creditors are not actively associated to the reorganization
process, the study suggests that the reorganized …rms may bene…t from a concentrated bank lender. Our interpretation of this result is that banks may be inclined to
play a monitoring role or to support …rms with concentrated debt structure to ensure
the reimbursement of their claims. The reorganized …rm is also forced to respect the
installments since it relies on bank debt.
Finally, the prediction model presented in this chapter correctly identi…es around
71% of the sample …rms as either successes or failures. This prediction model could
be useful when forming an opinion regarding the plan’s likelihood consummation.
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Chapter 6 sheds further light on the performance of reorganized …rms and on
the factors that a¤ect their post-con…rmation outcome. Speci…cally, the examination of accounting measures of performance prior to …ling and following con…rmation
shows that reorganized …rms have improved their pro…tability during the bankruptcy
process. This increase in pro…tability may be explained by the measures taken by
the Court, such as the automatic stay. Another stylized fact is the very high leverage
observed at the con…rmation year and several years following the con…rmation. We
believe that there are two possible explanations for the increase of leverage. First,
most of bankrupt …rms face liquidity problems and need additional funds to continue their activity and to meet the …rst payouts of reorganization plans. Therefore,
they raise additional debt which increases the leverage ratios during reorganization.
Second, the French bankruptcy law encourages banks and suppliers to give new loans
to bankrupt …rms. These claims are known as "article 40" debts and confer to their
holders the privilege to be paid in priority.
Moreover, the results of regression analysis show that pre-…ling pro…tability and
leverage have no e¤ect on the reorganization outcome. They also show that larger
…rms with higher pro…tability and …rms operating in pro…table industries at the
con…rmation year are most likely to continue their operations for at least four years
following con…rmation.
Chapter 7 focuses on examining the future prospects of the reorganized …rms
using survival analysis techniques (Kaplan-Meier and Cox models). The logic behind
this methodology is that a model used to detect corporate distress, might also be
e¤ective in assessing the risk of failing of reorganized …rms. The ability to incorporate
time in these models is the major advantage of survival analysis techniques compared
to others techniques, multivariate discriminant analysis, logit and probit. As far as
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is known, there is no previous literature applying survival analysis to reorganized
…rms in the French context.
Furthermore, the study uses two types of Cox models to determine the in‡uence
of …nancial factors on the risk of failing of reorganized …rms: time-invariant models
versus time-varying models. The comparison between the two types of model shows
that time-varying covariates model provides a better …t and has more statistically
signi…cant coe¢ cients with the expected signs. The superiority of time-varying model
is predictable since a dynamic model that takes into account the progress of the
reorganization process and the change of …rm’s characteristics over time is more
appropriate than a static model.
The estimation results of time-varying Cox model identify four signi…cant
explanatory variables. Three of these covariates have a positive e¤ect on survival
including the company’s pro…tability, liquidity, and the industry pro…tability while
the leverage has a negative e¤ect. In particular, the results indicate that leverage
has a threshold e¤ect: …rm’s leverage does not have an impact on the risk of failing
when it is measured as a debts-to-assets ratio, but it has an impact when the …rm’s
status moves from "insolvent" to "solvent" entity and vice-versa. One reasonable
explanation lies in the speci…city of the sample used in the study which is exclusively
composed of bankrupt …rms.
Finally, the survival function suggests that the failure process of a reorganized
…rm in France is similar to the failure process of a new …rm. Once the …rm has
survived for 5 years or more, the probability of failing in the near future becomes
low.
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Limitations of the study and suggestions for future research
1) Improvement on explanatory variables
The bankruptcy process in France is under the Court control. Thus, the reorganization form (Chapter 4) or the plan’s outcome (Chapter 5) may di¤er according
to the experience of the judge and the measures undertaken during the observation
period. It would be interesting to investigate the role of the Court in the reorganization’s form and its success.
It would also be interesting to include in Chapter 4 characteristics that are speci…c
to each alternative and to study the extent to which they in‡uence the form of
reorganization such as the price o¤ered by potential buyers, the plan’s duration, and
the number of dismissals.
In Chapter 6 and 7, we use exclusively …nancial variables; one may include
market-based variables, corporate governance attributes, company-speci…c variables,
and macroeconomic variables.
2) Improvement on the sample
The samples of …rms included in this thesis are restricted to …rms that …led
for bankruptcy in the commercial Court of Paris. Accordingly, incorporating further samples from other commercial Courts would be interesting. First, it would
permit the generalization of the empirical results. Second, one may investigate the
di¤erences between the Courts with regards to the form of reorganization and the
performance of the reorganized …rms.
3) Impact of the 2005 bankruptcy reform
The French bankruptcy system was substantially reformed by the law of July
26, 2005 regarding the …rms’safeguard. The goal of the new bankruptcy law is to
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improve the procedures to prevent enterprises’default at an early stage and to avoid
that their …nancial di¢ culties lead to bankruptcy proceedings.
The study in the present thesis does not cover the most recent reform. Thus, it
would be interesting to examine reorganized …rms under the new law and investigate
to what extent such reform has improved the performance of the reorganized …rms.