Physical Real Estate : Risk Factors and Investor Behaviour

Transcription

CENTRE
DE RECHERCHE
RESEARCH CENTER
DOCUMENTS DE RECHERCHE
WORKING PAPERS
– N° 01020 –
Physical Real Estate : Risk Factors and Investor Behaviour
Michel BARONI
ESSEC Business School
Fabrice BARTHELEMY
THEMA, University of Cergy-Pontoise
Mahdi MOKRANE
THEMA, University of Cergy-Pontoise
June 2001
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- DR 01020 -
Physical Real Estate :
Risk Factors and Investor Behaviour
Michel Baroni∗
Fabrice Barthélémy**
Mahdi Mokrane***
June 2001
∗
ESSEC Business School, Avenue Bernard Hirsch – B.P. 105, 95021, Cergy-Pontoise Cedex, France.
E-Mail : [email protected]
** THEMA, University of Cergy-Pontoise, 33, Bd du Port, 95011, Cergy-Pontoise Cedex, France.
E-Mail : [email protected]
*** THEMA, University of Cergy-Pontoise, 33, Bd du Port, 95011, Cergy-Pontoise Cedex, France, and ESSEC
Business School. E-Mail : [email protected]
1
Physical Real Estate : Risk Factors and Investor
Behaviour1
Abstract
In this paper we investigate the risk factors associated with real estate investment. We explore a rich
database of over 100 000 transactions mainly for residential properties in the Paris area over the 1973 –
1998 period. The main risk factors are identified using a Principal Component Analysis as well as a
Stepwise WLS Regression Method. The first method indicates that linear or log-linear combinations of
factors such as interest rates, interest rate spreads, equity market returns, rents, unemployment, or even
market traded real estate cannot wholly capture physical real estate return risk. The second method
indicates it is nevertheless possible to derive a factor model for real estate risk, and that the consistent
factors are rents, unemployment, and listed real estate. Comparisons of our factor model index with the
IPD index and the Notaires/INSEE square-metre price index, as well as statistical probe of the database,
yield interesting implications concerning real estate risk, market participant behaviour, and the nature of
the so-called 1990s ‘speculative bubble’.
1
The authors wish to thank the Bureau Van Dijk for graciously providing us with the data base CD-Bien. The usual
disclaimer applies.
2
Introduction
Every real estate investor faces an objective difficulty concerning the measurement of real estate
investment performance and risk. The reasons explaining this difficulty are numerous : an absence of
centralised trading, or even price lists, a low degree of buildings or apartments turnover in investor
portfolios, a lack of transparency in transactions, the heterogeneity and indivisibility of real estate
properties, and a tradition of confidentiality in the industry.
Does this imply that investors should disregard investing in real estate? This would be a mistake if real
estate investments represented a consistent diversification vehicle from a global portfolio management
perspective. This mistake would be even greater if real estate provided an efficient inflation hedge.2
Real estate markets are relatively often subject to price shocks whose amplitude prove to be very high
and welfare decreasing. According to R. Shiller (1998)3, these shocks are as difficult to explain as those
that affect equity or debt markets. One of the main problems in trying to measure real estate volatility in
France is that there does not exist satifactory historically long time series for price and rent evolution (see
Section 1 of the present paper). A possibility for creating such indices would be to use a methodology
based on observed price transactions (Section 2). To achieve this goal we explore a rich transactions
database containing information on single-family homes transactions, as well as office, mixed
(professional and housing) and commerce properties for the Paris and its surrounding area.
Such indices may prove very useful, for example, in serving as “benchmarks” or in risk measurement.
Indeed, real estate performance is today at the heart of investor focus, whome, after a period of withdrawl
in the mid nineties, are flowing back, but with the concern of trying to better control for the risk and return
of real estate investments. According to F. Savel (1998)4, delegated real estate management seems to
benefit from a promising future, at the condition that this sector’s risk be well identified and hedged.
Section 3 presents a statistical analysis of our database and highlights interesting specific investor
behavior.
Identifying risk factors for real estate enables the investor, be he or she a landowner, a multi-billion
dollar institutional investor or a real estate debt holder, to measure and therefore hedge his (her)
investment position. This process also permits the debt holder to assess the risk of a real estate loan. A
unified approach to real estate risk is the only way to bring market participants to trade risks using real
estate derivatives. In this context, we isolate real estate risk factors (Section 4), and construct a factorial
model capable of synthetising real estate systematic price dynamics (Section 5). Our synthesis in the form
of risk-returns comparisons is presented in Section 6. The last section gathers our concluding remarks.
1. Existing Indices and Risk Measures
1.1 Existing Indices
There are three measures capable of calibrating real estate risk in France (and in particular in the Paris
area) today. They correspond to three indices of relatively different nature:
♦ The square metre index provided by the Chambre des Notaires de Paris and INSEE. This index is
computed every six months using a sample of transactions of unoccupied apartments aged five
years and over. The index for a given date is the weighted average of transactions prices per square
metre.
♦ The IPD index (International Property Databank) : This index is constructed using property
appraisal estimates covering a representative sample of real estate properties owned by majors
2
For a study of the link between inflation and real estate in the US, see Sirmans and Sirmans (1987). For the case of
France, see Friggit (1999).
3 Shiller (1998).
4 Savel (1998).
3
insurance and banking institutions in the Paris area. The methodology adopted consists in gathering
a representative sample whose value is periodically appraised using expert valuation models. The
aggregation of appraised values provides the index’s value for a given date. For the case of France,
IPD publishes such an index every year5.
♦ The index for listed real estate is published each day by Datastream-Financial Times (code
RLDEVFR) based on the liquidation prices of the following listed investment trusts : GECINA,
INTERBAIL, KLEPIERRE (CIE FONCIERE), LOCINDUS, SEFIMEG, SILIC, SIMCO,
SOCIETE FONCIERE LYONNAISE, SOGEPARC, UIF, UNIBAIL.
1.2 Inability of theses Indices to Measure Real Estate Risk
The following figure illustrates the evolution of the above-mentioned indices since 1986. The IPD and
Notaires/INSEE indices represent the return on capital for housing, whereas the type of market sector
represented by the listed real estate index depends on the type of assets the investment trusts holds.
IPD, Notaires/INSEE and Listed Real Estate Indices (return on capital)
250
200
150
100
50
Notaires/INSEE
IPD
01
-9
9
01
-9
8
01
-9
7
01
-9
6
01
-9
5
01
-9
4
01
-9
3
01
-9
2
01
-9
1
01
-9
0
01
-8
9
01
-8
8
01
-8
7
01
-8
6
0
Listed Real Estate
Figure 1
The main drawback of the Notaires/INSEE index is that it is based on a weighted average of prices for
heterogeneous real estate properties. This implies that, even if the general market trend may indeed be
correctly captured, the volatility measurement by the index is biased.
For the case of the IPD index, its main drawback is linked to the fact that it is not based on real
transactions prices, but rather on appraised values. This induces a certain degree of inertia in the index that
takes its source in:
♦ the fact that the appraisal experts periodically valuing a property generally tend to adjust preceding
valuations, conditioning valuations period to period.
♦ the time interval separating transactions information and the processing of this information in the
form of an appraised value. This bias is an increasing function of the index’s periodicity (note for
example that the IPD index is monthly in Great-Britain and annual in France).
5
For more details on the IPD index as well as other related information surf the following web site
www.ipdindex.co.uk, http://www.propertymall.com/ipdindex/ipfrisk.html.
4
These elements have a non negligible impact when one attempts to measure real estate risk, since they
both lead to an underestimation of volatility (inertia leads to a lower index volatility).
Listed real estate naturally contains real estate risk, but the total risk measured is simultaneously
affected by two other sources of risk. One is linked to the relatively high liquidity (daily listing) of
investment trusts, which is not representative of physical real estate whose markets are relatively illiquid
in comparison. The second is linked to the role that these trusts play in global portfolio diversification,
which implies that demand for these securities is more directly linked to capital markets fluctuations. This
risk is for example illustrated by the “kink” in the index during the year 1987, the same year securities
markets began to experience rapid growth and developed liquid and organised derivatives compartments
(MATIF, MONEP etc…).
One may then suggest that listed real estate may have been turned down in favour of then more
attractive securities such as stocks and bonds for which risk management and hedging became easier
thanks to the development of sophisticated equity and FX derivatives. If one believes that listed real estate
is perceived by capital market participants as an alternative investment with respect to other capital
markets securities, then it may not be surprising that listed real estate is much more highly sensitive to
capital markets risk factors than physical real estate, that may have its own factorial risk representation.
For all these reasons, the former may thus not satisfactorily represent the latter’s risk structure. One of the
aims of this paper is to shed light on this question.
Based on the above analysis, one may temporarily conclude that it is indeed very difficult to obtain
consistent and reliable results into the risk-return measurement of physical real estate based on existing
market representations, in particular when historical time series are short. What’s more, as stressed by
Hoesli (1993) 6, the evidence suggests a clear difference in terms of the relationship between inflation and
listed real estate on the one hand and physical real estate on the other hand, which confirms this risk
measurement difficulty. The real estate investor therefore is in search of a transactions-based index, and
therefore a listing of transactions prices. One such database exists for the case of Paris and the
neighbouring “départements” : the CD-Bien database. Note that this base contains a very high proportion
of housing transactions (more than 80%).
2
The Database
To analyse real estate returns, we constructed a database containing not only real estate returns but also
corresponding returns from economic or financial variables as well as hedonic7 information for each
transaction. The latter are extracted for the CD-Bien database who lists all real estate transactions written
in front of a notary for the Paris and near surrounding area (Hauts-de-Seine, Seine Saint-Denis, and Val de
Marne). From this database, we extracted 121 327 transactions for which we had the information on both
the initial price and date (post 1st of January 1973) at which the properties had been bought as well as the
price and date for the following resale8. These “complete” transactions represent 22,2% of the total
number of transactions.
Having at our disposal both the initial price of the property P1 as well as its resale price P2, we may
calculate more than 120 000 returns R = P2/P1. Using the dates for both transactions, T1 and T2, we may
annualise these returns in the following way Rannual = (P2/P1)365/(T2-T1).
To every observation in the database, the following hedonic characteristics can be associated :
-
Holding duration (duration) : duration is simply the difference T2 – T1 expressed in days.
6
See Hoesli (1993).
In this paper hedonic is to be taken in the loose sense of transactions characteristics.
8 We have to note an important feature concerning the database’s structure: we only observe those transactions
whose second transaction has taken place after 1990. We will come back to this point and point out where it may be
cause of concern in the course of the analysis presented below.
7
5
-
Holding horizon (horiz) : to facilitate statistical processing and interpretation, variable duration
has been translated9 into a discrete variable (horiz).
-
Type of purpose (purpose) : variable purpose may take any one of four values depending on the
type of purpose declared : 1 for family housing, 2 for commerce, 3 for a mixed-purpose (housing
and professional), and 4 for offices (commercial or professional).
-
Catgeo is a variable that classifies transactions according to a semi-geographical partition based
on the square-metre average price of 1997. Its value for a given transaction depends on
P2/(number of m2) : it will take a value of 1 if the price is lower than 10 000 FF, 2 for a price
falling between 10 and 15 000 FF, 3 if the price is comprised between 15 and 20 000 FF, and
finally 4 for a transaction price greater than 20 000 FF.
The quest for explanatory factors of real estate capital returns necessitates the selection of indicators
that one a priori believes to have some form of explanatory power. Ten factors were selected based on two
criteria. The first asked of potential factors to have a clear economic interpretation and presupposed links
with real estate markets. The second was that it was necessary for the times series to run back as far as
possible in time. The data we explored in Datastream ran back, for France, as far as the first of January
1973.
The indices selected to serve as factors were thus constructed with base 100 at the start of 1973. They
are the following : long term rate (LtR), short term rate (StR), consumer price index (Consum), MSCI10
equity market index (Equity), listed real estate (ListRE), rents (Rent), demographic index (Demog),
unemployment (Unemp), savings as a percentage of disposable income (Saving), and yield spread
(Spread).
For each transaction, we computed the corresponding return of every potential factor for the period
separating date T1 from T2. The whole set of returns was then transformed into semester returns11. The
resulting variables are thus the following: Rs, Equitys, Consums, Rents, LtRs, StRs, Demogs, ListREs,
Unemps, Savings, Spreads.
3
Statistical Analysis of the Database : The Broad View
3.1 Extreme Value Elimination
Let us begin by pointing out at the presence of a significant number of extreme values for variable Rs,
the presence of whom may severely bias statistical estimation. We have therefore begun by eliminating
transactions whose semester return exceeded 10 (or 1000%). One may note that all of these excluded
transactions correspond either to very short holding durations, for which one of the two prices (at date 1 or
date 2) is clearly not a market price, or to transactions conducted using a symbolic 1 FF price.
The following table illustrates the major differences between transactions based real estate returns
(variable Rs) and those of other variables namely on the grounds of the extent or dispersion (standard-
9 The partitioning of variable duration is arbitrary and corresponds to a number of observations concerning market
participants and their presumed investment horizons. We will come back to this point to motivate it. Variable horiz
will take value 1 if duration is lower than 3 years, 2 if it is comprised between 3 and 5 years, 3 if duration is between
5 and 10 years, 4 if it is comprised between 10 and 15 years, and finally 5 if duration exceeds 15 years.
10 We used the Morgan Stanley Capital International (MSCI) Index for France, which runs farther back in time than
the CAC40 Index .
11 The choice of the semester as a unit period is linked to the fact that, as we will see in the next sections, this time
step suits best our factorial model of index construction Hence, for every transaction i, characterised by dates T1 and
T2, we construct a series of variables Fjs(i), using the following formula: Fjs(i) = (Fj(T2)/Fj(T1))182.5/(T2-T1), where Fj(T)
represents the level of variable (time series) Fj (the MSCI index for example) for any date T.
6
deviation), of the asymmetric feature or skewness (numerous returns above the average), of the presence
of persistent extreme values (excess kurtosis12).
Minimum
RS
Equit
Consum
Rent
LtR
StR
Demog
ListRE
Unemp
Saving
Spread
Maximum
0,00
0,36
0,97
1,00
1,02
1,02
1,00
0,53
0,90
0,97
0,12
Mean
9,77
2,44
1,04
1,04
1,05
1,06
1,01
1,81
1,12
1,04
2,72
1,032
1,054
1,014
1,022
1,041
1,038
1,002
1,009
1,015
1,003
1,027
Standard
deviation
0,196
0,052
0,007
0,010
0,006
0,009
0,001
0,047
0,015
0,011
0,073
Skewness
22,93
4,14
1,06
-0,52
-0,16
-0,97
-0,95
1,30
-0,50
0,14
2,44
Excess
Kurtosis
734,40
85,53
0,71
-0,67
-0,29
0,21
1,07
27,57
4,01
1,20
31,58
Table 1
These results suggest pursuing the analysis by taking the natural logarithm of returns of all the above
variables, will be the resulting variable names being prefixed by an Ln. Remark that this method is rather
classical in finance when analysing return distributions. The histogram for variable Rs, for values
comprised between 0,7 and 1,3 is the following.
12500
Count
10000
7500
5000
2500
0,800
0,900
1,000
1,100
1,200
Ris
Figure 2
3.2
« No-Loss » Behaviour and Real Estate Crisis
The above figure points to an anomaly corresponding to a large number of transactions at or very near
a return of 1, or equivalently a rate of return of zero. Taking a close-up of the 11 491 observations whose
returns lie between 0,9975 and 1,0025, yields the following results:
12 Skewness measures the tendency of a distribution to give more weights to values greater than (positive skewness)
or lower than (negative skewness) the mean. Kurtosis measures the degree of flatness of a distribution. A normal
distribution has a kurtosis of 3 or equivalently an excess kurtosis of 0. An positive (negative) excess kurtosis
indicates a distribution with fat (thin) tails with respect to the normal distribution, which indicates the presence
(absence) of extreme values.
7
Rs
Date 1
Date 2
Price1
Price2
Duration
Purpose
Horiz
CatGeo
Minimum
0,998
01/03/73
01/11/91
14 000
14 000
28
1
1
1
Maximum
1,002
01/11/98
01/12/98
130 000 000
131 000 000
9 345
4
5
4
Mean
1,000
01/07/92
01/10/96
806 865
807 243
1 535,91
1,03
1,96
1,92
Table 2
This portion of returns represent nearly 9% of our observations, and correspond to the histogram’s
peak. Remark that all these transactions exhibit a resell date T2 post November 1991, that is after the
beginning of the real estate crisis in France. Observing the Average column of this table helps characterise
these transactions. The average acquisition date of these properties is July 1992, whereas the average
resale date is October 1996. The type of property is quasi-exclusively housing.
If one considers the Notaires/INSEE index during the same period, its level dropped by 10,5%. One
may conclude that an important number of property sellers had a “No-loss” behaviour during this crisis
period, in which they refused to sell their property at a price lower than the one they paid for it. A more
thorough analysis of variables P2 and CatGeo indicates that these properties had a resale price not
exceeding 1 000 000 FF and located in areas with an average square-foot price below 15 000 FF/ m2.
The type of property described above exhibits a relatively high resistance to price drops even in the
context of a rough downside market. One may also interpret this behaviour as being one of owners willing
to sell only at the condition that they do not loose in terms capital, or accepting to sell with no gain rather
than waiting for a hypothetical market upturn. This behaviour also illustrates the relatively dominant
weight of the seller over the acquirer for this type of property. For the analysis in the next sections, we
exclude these transactions based on the assumptions that they correspond to very particular types of
market participant behaviour during a peculiar period.
3.3 Investor Behaviour During the Crisis
The second conclusion worth mentioning here concerns the market behaviour of “retired” individuals
during the 1987-1997 period. Thanks to the precision of the database information concerning the status
active/retired of the acquirer and seller, we were able to see that the retired population massively entered
the physical real estate market during the end of the 1980s, early 1990s. Indeed, during this period, more
than 25% of the market entrants were retired individuals. What’s more, it is the retired who marched out
of this same market during the period 1996-1997, probably to profit from the bullish capital markets
France experienced at that time.
We may also note that only 7% of market participants with a an investment horizon lower than three
and a half years are property traders. Hence, it appears that the market participants that have the possibility
of profiting from arbitrage opportunities from the capital markets are not the legal entities, but the
individual entities, and more precisely retired individuals. We will come back to this point when
presenting our results on factorial models and their link with listed real estate.
8
4
Common Risk Factors
4.1 Preliminary Analysis : Horizon Threshold and Data Selection
On the basis of the above analysis (descriptive statistics and out-of-market data elimination) we may
now proceed with a Principal Component Analysis (PCA13) whose goal is to isolate the common risk
factors associated with real estate returns.
A first result of our exploration stresses the absence of a clear linear relationship between physical real
estate returns and the macroeconomic and financial variables selected14. A PCA analysis on hedonic
variables shows the relative importance of variable horizon and more specifically of the atypical behaviour
of returns associated with short holding durations (less than three years). This result is confirmed and
refined by the study of the error terms in regressions of variable LnRs on the selected variables. Indeed, it
seems suitable to treat the short-horizon transactions separately. The main partition appears at horizon 3,5
years. The characteristics of return distributions for short holding periods (less than 3,5 years) are
markedly different from those of longer holding periods. Note that this result is consistent with the
findings of the previous section, where we stressed “No-loss” and “retired” behaviours which were both
associated to short horizon.
It seems therefore reasonable to assume that transactions whose duration is less than 3,5 years behave
according to a model that cannot be correctly captured by combining our variables. For longer durations
the prospects of elaborating a consistent and reliable model seems more encouraging. For these
transactions we have proceeded using a similar systematic analysis of error terms, leading to a further
screening of outliers and/or influential data.
Data selection and screening is a delicate and rather cumbersome exercise15 since one has to both
eliminate unsuitable or outlying data and at the same time be careful not to discard valuable information.
This often implies a careful examination of a large number of observations on a case to case basis: sale
condition, price comparisons, property inhabited or not at the time of sale, transaction parties’ status,
symbolic francs transaction…). This screening is not that penalising for those property purposes for which
we had relatively few observations originally, i.e. mixed (952 observations before and 632 after
screening), commerce (1 500 before and 1 199 after screening), and office (572 before and 435 after
screening). For the housing purpose we had more than 100 000 transactions at our disposal, of which we
extracted a random sample of 7 000 observations. After screening, this led to a total of 5 609 observations
for the housing purpose. We believe this provides us with a suitable amount of relevant information to
derive real estate factors.
4.1.1
Results Per Property Purpose for LnRs
Before moving further, let us make sure the screened data imply a reasonably normal distribution for
variable LnRs. Table 3 shows that for all property purposes, semester log-returns distributions exhibit a
significant positive excess kurtosis, which means that the distributions tails are still relatively thicker than
normal. However, these statistics are much less alarming than before data screening (see Table 2).
Skewness to the right or to the left (for mixed purpose) seems very reasonable, being quite close to zero.
Finally, the examination of kurtosis and skewness suggests differentiating the analysis with respect to
property purpose. This will be further confirmed later on in the analysis.
13 PCA is a data analysis method used in a number of management disciplines (marketing, finance, insurance…).
Consider a table containing individuals (lines) and many variables measured on each individual (columns), PCA
aims at creating a restricted number of linear variable combinations (called factors) capable of summarising the
essence of information contained in the initial table.
14 More detailed results, concerning “outlier detection” in particular, are presented in Barthélémy, Baroni and
Mokrane (2001).
15 For a more thorough discussion on outlier detection see the seminal paper of Cook (1977), and the more recent
book by Atkinson (1985).
9
Purpose
Number of
observations.
Housing
5 609
-0,126
0,168
0,020
0,028
0,128
2,072
632
-0,073
0,128
0,026
0,031
-0,395
0,691
1 199
-0,075
0,143
0,024
0,032
0,017
0,581
435
-0,060
0,130
0,025
0,028
0,091
0.616
Mixed
Commerce
Office
Minimum Maximum
Mean
Standard
deviation
Skewness
Excess
Kurtosis
Table 3
4.1.2
Bivariate analysis on the temporal structure per type of purpose
The following figure represents, for the Housing purpose, and for variables date1, date2, duration and
LnRS, a set of univariate sorting (frequency distributions on the diagonal) as well as cross-sorting
(bivariate) of selected variables. For example, the lower left-hand side graph indicates the distribution of
values taken by variable LnRS as a function (sorted by) of date1.
For graph readability, we have randomly selected a set of 1 000 transactions for Housing (similar
results obtain but are not shown here for Commerce, and for the sets of available transactions for Mixed
and Office purposes). Note that this does not imply any loss of generality of the qualitative and
quantitative insights these graphs enable us to draw.
Transactions dates, returns and market volume
Whereas the negative linear relationship between variables date1 and duration is obvious, it is worth
underlining the absence of any linear relationship between date2 and duration. Indeed, we believe the very
small positive linear relationship between variables date2 and duration is due to the database’s own
structure : we only observe those transactions whose second transaction has taken place after 1990.
Variable date1’s distribution illustrates, to a certain extent, the real estate market’s activity. The
graph’s observation leads us to a time partition into three broad phases : a relatively low but increasing
volume of home acquisitions from 1973 to the mid-1980s, a strong increase in market activity
(acquisitions) from 1985 to 1990, followed by a brutal decline in buys coinciding with the real estate bust
of 1991, with the mention that the slow acquisitions activity has lasted till the end of 1998.
By comparing real estate returns with the market volume as measured by date1, we are able to relate
LnRS to the three distinct phases identified above : until the mid 1980s, real estate returns are relatively
stable both in level and variability. During the 1985-1990 phase, returns decreased steeply with time
(date1) and their variability is distinctly higher than during the preceding phase. Finally, during the post1990, returns relate positively to date1, but one observes an even higher variability.
Heteroscedasticity
The analysis of the figure’s last line (corresponding to variable LnRS) exhibits strong heteroscedasticity
for physical real estate log returns as a function of duration. Indeed, the shorter the holding period, the
higher the log-return variability. We believe that part of this variability takes its source in the three-phase
structure linked with date1 indicated above. This holding period-linked heteroscedasticity will have to be
corrected when specifying our factorial model for real estate physical returns.
10
Figure 3
4.1.3
How Many Real Estate Risk Factors?
Let us now turn to the search for systematic relationships between real estate returns and
macroeconomic, financial and hedonic variables. PCA indicates that only four factors (linear combinations
of 12 variables) are sufficient to capture nearly 85% of total variance of our dataset. The first factor is able
to explain roughly 51% of total variance, followed by Factor 2 (15,9%), Factor 3 (10,3%), and finally
Factor 4 (7,7%). The following table indicates linear correlations between variables and factors:
Variables
LnRS
Horiz
LnConsumS
LnRentS
LnLtRS
LnCtRS
LnDemogS
LnListRES
LnSavingS
LnEquityS
LnUnempS
CatGeo
LnSpreadS
4.1.4
Factor 1
0,551
0,825
0,920
0,906
0,970
0,858
0,750
0,752
-0,716
0,381
0,388
0,047
-0,593
Factor 2
0,152
-0,281
-0,010
0,389
0,144
0,473
0,235
-0,551
0,522
-0,854
0,454
-0,079
-0,041
Factor 3
-0,388
0,056
0,260
-0,047
0,043
0,007
-0,369
0,099
-0,318
-0,106
0,719
0,002
0,577
Factor 4
0,084
-0,027
-0,013
-0,004
-0,007
0,002
0,023
-0,023
0,011
-0,035
0,016
0,992
0,060
Table 4
Interpretations
The first factor comprises interest rate –linked (long and short term rates) as well as economic variables
(consumer price, rents, demographic index, and to a lesser extent savings rate and listed real estate). Note
that all of these variables are linked to investment horizon and hence to holding duration. The second
factor reflects the volatility of equity market returns, whereas the third factor captures business cycles by
11
combining unemployment and interest rate spreads. Finally, the fourth factor sorts returns using the
geographical variable (average price per square metre).
Introducing real estate returns into the analysis does not significantly change the results (coefficients).
Real estate returns react positively to Factor 1 shocks (an increase in long term rates being the clearest
example), negatively to Factor 2 shocks (MSCI French Equity index). Factor 3 opposes physical real
estate variations to those of cyclical variables such as unemployment and interest rate spreads.
Variable LnRs is essentially captured by Factors 1 and 3 (their combined explanatory power roughly
45%16). We might add that since the first four factors explain less than 48% of real estate returns, this
level constitutes somewhat the maximum R2 any regression model of these returns on linear combinations
of explanatory variables might attain. Remark that Factor 4 is not correlated with real estate return, which,
to some, might come as a surprise. Indeed, this means that physical real estate returns are not linked to
properties’ average square metre prices.
Finally, note the very different factor projections of physical real estate and listed real estate (apart
from Factor 1 coefficients, the other three have opposite signs). What’s more, listed real estate variance is
almost entirely captured by the fist two factors (loosely speaking interest rate and equity market returns
explain more than 87% of variance). This comes as a confirmation of the elements presented in the
previous sections, and reinforces the conclusion that physical and listed real estate consistently behave
differently, and are thus subject to different risk factor structures.
5
Towards a Factor Model of Physical Real Estate
A factor model enables to “synthetize” a real estate index capable of representing systematic risk per
property purpose. The selected methodology is that of a multi-factor model resulting from a linear
regression on the selected explanatory variables presented above. We will now analyse, thanks to a
“stepwise” regression method, the relationship between physical real estate, macroeconomic, financial,
and idiosyncratic factors. For each transaction i, the estimator for LnRis is thus:
LnRi s ( i ) = α +
k
j =1
β j LnF js ( i ) + ε ( i )
(1)
where α is the regression’s constant estimator, FjS(i) represents the semester return for variable Fj during
period [T1, T2] separating the two sales of property i (see footnote n°11), β j is the loading of the jth
variable LnFjS, and finally ε(i) is a normally distributed random variable with mean 0 and constant
variance σ2. It represents the error term for transaction i. We assume away any correlation between any
two transactions’ error terms.
Ordinary Least Squares (OLS) are used to estimate the above model’s parameters. The following table
summarises selected models as well as the corresponding coefficient estimates. The value in parentheses
represent the Student-t estimates for each coefficient17.
The explanatory power of a factor with respect to a variable’s variance (the R2 obtained by regressing the variable
on the factor) is obtained by taking the squared value of the corresponding coefficient. Hence, Factor 1 explains
(0,551)2 = 30,4% of real estate returns, whereas Factor 2 explains (-0,388)2 = 15,1%, with a combined explanatory
power of 45,5%.
17 Note here that all coefficients are significant to the 99.9% confidence level.
16
12
Constant
LnRents
LnUnempls
LnListREs
R2 (%)
Housing
-0.0278
(-22.6)
2.38
(42.1)
-0.75
(-18.5)
0.091
(4.9)
31.4
Mixed
-0.0193
(-4.4)
2.40
(11.9)
-1.11
(-8.5)
0.200
(3.2)
28.2
Commerce
-0.0194
(-5.8)
1.95
(13.6)
-0.41
(-3.7)
-
14.3
Office
-0.0330
(-6.1)
2.57
(11.0)
-0.73
(-4.5)
-
24.1
Purpose
Table 5
5.1 Residuals Analysis : Heteroscedasticity
The above proposed modelling assumes that the variance associated to each purpose does not depend
on observation (i). If these assumptions are not validated, the model must be amended so that its
specification corresponds to our data structure. Inside each purpose class, the White test18 clearly
indicates heteroscedasticity. To study its correct nature (the search for variables that are at the source of
heteroscedasticity), we use the Goldfeld-Quant (GQ) test.
We begin by ordering regression residuals as functions of variables, and then study whether residual
variance is constant across classes. Several variables may be candidate sources for heteroscedasticity : the
ones contained in the table above, which were identified by the White test, as well as temporal variables
such as duration, date1, and date2. Table 6 below indicates the p-values for different variables and the
four purposes.
Housing
Mixed
Commerce
Office
duration
e-175
e-22
e-28
e-8
date1
e-137
e-18
e-21
e-6
date2
e-26
e-6
e-7
e-4
LnUnempls
0.001
0.62
0.88
0.85
LnListREs
e-8
e-13
e-24
e-5
LnRents
e-15
0.002
e-4
0.04
Table 6
By gathering these results with those of the bivariate analysis (see 4.1.2), the variable at the source of
heteroscedasticity is clearly duration. The study of the graph mapping the residuals as a function of
duration logically suggests an inverse relationship between the error term’s variance for observation i and
the total holding period for the asset as measured by duration.
18
The tests presented thereafter are described in detail in Greene (1997).
13
The new model19 selected is thus a modified version of (1) in which ε(i) is now considered to be a
random variable that follows a normal distribution with zero mean and variance equal to σ2/duration(i).
This model can then be estimated using Weighted Least Squares (WLS).
In modifying the model’s specification to take into account this variance’s modelling, we are able to
eliminate the sources of heteroscedasticity that appeared in Table 6. Indeed, the White test does not detect
any other source of heteroscedasticity based on our WLS estimates. As for the GQ tests, all p-values
become high except for variable date2, and only for the case of the housing purpose. Our conclusion is
that the test results in Table 6 for the case of variables LnUnempls, LnListREs, and LnRents were
significant only due to their correlation with duration.
This new specification for the factorial model illustrates the importance of variable duration ; by being
able to include it in the variance but not in the level (different levels of returns depending on horizon and
different factorial relations) enables us to construct a synthetic index for mid-term and long-term physical
real estate20.
5.2 Selected WLS Factor Models for Real Estate Risk
The following table summarises selected models as well as the corresponding WLS coefficient
estimates21.
Constant
LnRents
LnUnempls
LnListREs
R2 (%)
Housing
-0.0314
(-23.9)
2.50
(40.46)
-0.72
(-17.74)
0.065
(3.47)
45.3
Mixed
-0.0213
(-4.28)
2.37
(10.26)
-0.92
(-6.67)
0.166
(2.53)
40.8
Commerce
-0.0227
(-5.8)
2.12
(13.6)
-0.52
(-3.7)
-
25.5
Office
-0.0391
(-5.69)
2.84
(9.0)
-0.81
(-4.58)
-
31.1
Purpose
Table 7
A first comment on these results is that the variables selected are similar for the four types of property
purposes, with the exception of variable ListRE (listed Real Estate) which comes significantly into action
for housing and mixed (professional and housing) purposes. The message delivered by this result is that,
even if the levels of return demanded by investors differ according to the property purpose, the sources of
systematic risk are the same for housing/mixed and commerce/office, noting however that variables
LnRents (rents) and LnUnempls (level of unemployment) come into action whatever the property purpose.
It may appear at first glance quite surprising that listed real estate intervenes in property purposes such
as housing and not in office or commerce purposes. However, this result is to be paralleled with the one
put to light concerning the retired individuals during the real estate crisis period (see section 3.3). Indeed,
we had stressed an arbitrage-type behaviour between physical real estate and capital markets on the part,
not of professional real estate investors, but of individual buyers. This arbitrage is therefore to be found in
It may be possible to try and find α in the specification σ2(i) = σ2/duration(i)α using the maximum likelihood
method, but this is rendered very difficult by the fact that we do not know the residuals distribution function
(normality is rejected here).
20 Recall that in Section 4.1 we had shown that it was necessary not to include transactions whose durations were
less than 3.5 years because of their very different correlation structure with our then potential risk factors.
21 Note here again that all coefficients are significant to the 99.9% confidence level.
19
14
the returns demanded by these market participants in the form of the listed real estate factor for risk, as
illustrated in Table 7.
5.3 Visualisation of indices
The indices constructed using the above factor models are represented in the following figure, which
also contains the listed real estate index to facilitate comparisons.
The factorial indices for the four purposes are quite similar (see Figure 3) and move significantly away
from the listed real estate index starting from the beginning of 1982. One may however remark that
notwithstanding the July 1990-July 1994 period corresponding to the real estate crisis, the physical real
estate changes in trend seem to be portended by the listed index, in the sense that the trend kinks seem to
be ‘anticipated’ by a whole year or even more by the listed index.
Factor Indices / Listed Real Estate
700
600
500
400
300
200
100
ju
il7
ju 3
il7
ju 4
il7
ju 5
il7
ju 6
il77
ju
il7
ju 8
il7
ju 9
il8
ju 0
il8
ju 1
il8
ju 2
il8
ju 3
il8
ju 4
il8
ju 5
il8
ju 6
il8
ju 7
il8
ju 8
il8
ju 9
il9
ju 0
il91
ju
il9
ju 2
il9
ju 3
il9
ju 4
il9
ju 5
il9
ju 6
il9
ju 7
il98
0
Housing
Commerce
Mixed
Office
Listed Real Estate
Figure 4
Representing the Housing Factor Index, the Notaires/INSEE index and the factor variables (rents,
unemployment and listed real estate), yields the following figure.
15
Housing Factor Index - Notaires/INSEE Index/ Factor Variables
700
600
500
400
300
200
100
ju
il7
ju 3
il7
ju 4
il7
ju 5
il7
ju 6
il7
ju 7
il7
ju 8
il7
ju 9
il8
ju 0
il8
ju 1
il8
ju 2
il8
ju 3
il8
ju 4
il8
ju 5
il8
ju 6
il8
ju 7
il8
ju 8
il8
ju 9
il9
ju 0
il9
ju 1
il9
ju 2
il9
ju 3
il9
ju 4
il9
ju 5
il9
ju 6
il9
ju 7
il98
0
Housing Factor Index
Rents
Unemployment
Listed Real Estate
Notaires/INSEE
Figure 5
It seems interesting to note that the Housing Factor Index’s trend is driven by the Rents Index whereas
its departures from its central trend are linked to the Listed Real Estate and Unemployment Indices.
Whenever the latter drop, the Factor Index climbs and conversely. This feature is particularly notable for
the period 1987-1990, when real estate price experienced fast growth. Note that the Notaires/INSEE Index
depicted in a rather exaggerated manner this fast growth. An explanation of this feature may be that the
Notaires/INSEE index includes all types of transactions, and does not control for those with very short
holding periods (durations) which we have analysed separately since they corresponded to significantly
different investment behaviours. Therefore, our factor model may be seen as representing the fundamental
real estate market evolution. Note finally that the Notaires/INSEE index moves away from the Factorial
Index only during the 1987-1994 period which is precisely the time when the so called “real estate
bubble” formed and deflated.
6
Risk and Return
This section extends the analysis to the nature of the return and risk (standard-deviation) characteristics
of physical real estate. Assuming that real estate log-returns (LnRs), are indeed normally distributed,
enables us to consider that our factorial indices follow standard geometric brownian motion dynamics.
The estimated model for Rs is hence a diffusion process whose instantaneous expected mean is exp( µ )
where : µ = m + 1 σ 2 , and variance is σ 2 (m, resp. σ,=being the historical average, resp. standard-deviation,
2
of log-returns). The following table presents the characteristics of mean returns and a measure for risk
(standard-deviation of rates of return) per property purpose:
16
Return : µ = m + ½ σ2
Volatility : σ
Annualised moments (%)
Empirical
Measure22
Factor Model
Empirical
Measure
Factor Model
Housing
6,01
6,54
4,02
6,99
Mixed
7,31
7,26
4,42
8,66
Commerce
7,05
6,56
4,49
5,27
Office
6,99
6,06
3,90
7,74
Table 8
Note that empirical returns are approximately the same as those computed using the Factor Models.
However empirical volatilities are very significantly lower than those of the factor model. This is probably
due to the returns’ heteroscedasticity that is not corrected for in the empirical measure.
Also, note the apparent homogeneity of returns, and the relatively low Commerce volatility. By
construction, a given Factor Index volatility is linked to the volatilities of selected explanatory variables.
This does not prevent Factor volatility from being greater than empirical volatility. The transcription of
theses results in terms of Factor rates of nominal return and risk is given in Table 7.
Annualised moments (%)
Rate of Return (R)
Risk (Standard deviation)
Housing
6,76
7,47
Mixed
7,52
9,33
Commerce
6,78
5,63
Office
6,25
8,24
Table 9
Finally, comparing the above results to inflation behaviour during the 1973-1998 period confirms the
traditional view that real estate is a hedge for inflation risk. Indeed, average inflation was 6,4% annually
which is very close, while being slightly lower than average physical real estate returns. What’s more,
note in Table 10 the very strong correlation between physical real estate multi-factor indices and inflation
during the 1973-1998 period. This feature is present to a lower extent if one uses the INSEE/Notaires
Index, and is quite absent if one were to use the IPD Index.
Correlation
Coefficient
Price Index
Housing
Index
0,955
Mixed
Index
0,943
Commerce
Index
0,966
Office
Index
0,949
INSEE/Not IPD Index
aires Index
0,815
0,504
Table 10
22
The empirical measures are simply the mean and standard deviation as measured directly from the dataset
observations.
17
Conclusion
Our study has enabled us to answer a number of questions concerning real estate risk :
♦ Are we capable of identifying real estate risk factors? Yes.
♦ Can we distinguish between systematic risk and idiosyncratic risk in real estate? Expressed
differently, amongst the risk factors identified, can we point to those that investors really value? Yes.
♦ What is the maximum number of systematic factors? Two or three.
♦ Is it necessary to proceed to separate analysises depending on property purposes? Yes.
♦ Can a thourough analysis of transactions data put to light certain specific market participant
behaviour? Yes.
♦ Has there been a real estate speculative bubble during the late 80s-early 90s? Yes and no depending on
the investment horizon.
In this paper we have tried to exhibit systematic sources of risk on the basis of real estate transactions
data. We have started by studying the particularities of the semester capital return variable. Interesting
behaviours appeared, and in particular one which opposes market participants whose investment horizon is
rather short and are keen on arbitrage opportunities (with capital markets for instance), to those with a
much longer investment horizon who await a return linked to more fundamental factors such as rents and
unemployment.
We then explored the possibility of deriving a factor model of real estate returns, capable of capturing
the market’s fundamental movements. Our methodology, backed by both Principal Component Analysis
and “stepwise” WLS regression techniques, was aimed at bringing forward consistent explanatory
variables.
The results are globally encouraging. Firstly, they provide intuition and explanations as to the role
played by such variables as rents, listed real estate, and unemployment in return formation. Next, they
indicate that there exist combinations of a priori explanatory variables capable of representing in a
satisfactory manner systematic real estate returns for different market sectors.
What’s more, the results obtained point to the geographical variable as being of little use in explaining
real estate risk or return. This might seem surprising to certain categories of real estate professionals. It
seems here that location may indeed play a role in the determination of the transaction price level but not
in real estate returns or rates of return.
Our study, grounded in observed transactions prices and dates, has the merit of exposing risk factors,
but is not totally operational from the point of view of the real estate investor. These are two reasons to
this. The first is that the specific dynamics of risk are neglected since they are considered diversifiable.
For such a huge and fragmented market, diversification is not always possible of feasible, in particular
when specific risk represents nearly half total risk as it seems to be the case here. The second is linked to
the predictability of the factor model which is not necessarily an easy exercise. This question is also linked
to the question of whether such a factor model could prove useful in elaborating hedging strategies in real
estate investment management.
In sum, the real estate investor is in need of an index representing, in a precise manner, the physical
market’s movements. Such an index has to be grounded in a method that is both able to capture and
separate the systematic as well as the specific market dynamic and that would not be too sensitive to the
choice of explanatory variables. Our focus is now turned to this precise direction.
18
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19
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LISTE OF ESSEC RESEARCH CENTER WORKING PAPERS
(Contact the ESSEC RESEARCH CENTER for information on how to obtain copies of these papers)
[email protected]
1997
97001 BESANCENOT D., VRANCEANU Radu
Reputation in a Model of Economy-wide Privatization.
97002 GURVIEZ P.
The Trust Concept in the Brand-consumers Relationship.
97003 POTULNY S.
L’utilitarisme cognitif de John Stuart Mill.
97004 LONGIN François
From Value at Risk to Stress Testing: The Extreme Value Approach.
97005 BIBARD Laurent, PRORIOL G.
Machiavel : entre pensée du pouvoir et philosophie de la modernité.
Value at Risk: une nouvelle méthode fondée sur la théorie des valeurs extrêmes.
97007 CONTENSOU François, VRANCEANU Radu
Effects of Working Time Constraints on Employment: A Two-sector Model.
Reputation in a Model of Exchange Rate Policy with Incomplete Information.
97009 AKOKA Jacky, BRIOLAT Dominique, WATTIAU Isabelle
La reconfiguration des processus inter-organisationnels.
97010 NGUYEN. P
Bank Regulation by Capital Adequacy and Cash Reserves Requirements.
Beyond the VaR.
Optimal Margin Level in Futures Markets: A Method Based on Extreme Price Movements.
97013 GROUT DE BEAUFORT Viviane
Maastricth II ou la copie à réviser.
97014 ALBIGOT J.G., GROUT DE BEAUFORT V., BONFILLON P.O., RIEGER B .
Perspectives communautaires et européennes sur la réduction du temps de travail.
97015 DEMEESTERE René, LORINO Philippe, MOTTIS Nicolas
Business Process Management: Case Studies of Different Companies and Hypotheses for Further
Research.
Page 1
97016 PERETTI Jean-Marie, HOURQUET P.G., ALIS D.
Hétérogénéité de la perception des déterminants de l’équité dans un contexte international.
97017 NYECK Simon, ROUX Elyette
WWW as a Communication Tool for Luxury Brands: Compared Perceptions of Consumers and
Managers.
97018 NAPPI-CHOULET Ingrid
L’analyse économique du fonctionnement des marchés immobiliers.
97019 BESANCENOT D., ROCHETEAU G., VRANCEANU Radu
Effects of Currency Unit Substitution in a Search Equilibrium Model.
97020 BOUCHIKHI Hamid
Living with and Building on Complexity: A Constructivist Perspective on Organizations.
97021 GROUT DE BEAUFORT V., GRENOT S., TIXIER A . TSE K.L
Essai sur le Parlement Européen.
97022 BOULIER J.F., DALAUD R., LONGIN François
Application de la théorie des valeurs extrêmes aux marchés financiers.
97023 LORINO Philippe
Théorie stratégique : des approches fondées sur les ressources aux approches fondées sur les processus.
97024 VRANCEANU Radu
Investment through Retained Earnings and Employment in Transitional Economies.
97025 INGHAM M., XUEREB Jean-Marc
The Evolution of Market Knowledge in New High Technology Firms: An Organizational Learning
Perspective.
97026 KOENING Christian
Les alliances inter-entreprises et la coopération émergente.
97027 LEMPEREUR Alain
Retour sur la négociation de positions : pourquoi intégrer l’autre dans mon équation personnelle ?
97028 GATTO Riccardo
Hypothesis Testing by Symbolic Computation.
97029 GATTO Riccardo , JAMMALAMADAKA S. Rao
A conditional Saddlepoint Approximation for Testing Problems.
97030 ROSSI (de) F.X., GATTO Riccardo
High-order Asymptotic Expansions for Robust Tests.
Negotiation and Mediation in France: The Challenge of Skill-based Learnings and Interdisciplinary
Research in Legal Education.
Pédagogie de la négociation : allier théorie et pratique.
97033 WARIN T.
Crédibilité des politiques monétaires en économie ouverte.
97034 FRANCOIS P.
Bond Evaluation with Default Risk: A Review of the Continuous Time Approach.
97035 FOURCANS André, VRANCEANU Radu
Fiscal Coordination in the EMU: A Theoretical and Policy Perspective.
97036 AKOKA Jacky, WATTIAU Isabelle
MeRCI: An Expert System for Software Reverse Engineering.
97037 MNOOKIN R. (traduit par LEMPEREUR Alain)
Page 2
Surmonter les obstacles dans la résolution des conflits.
97038 LARDINOIT Thierry, DERBAIX D.
An Experimental Study of the Effectiveness of Sport Sponsorship Stimuli.
97039 LONGIN François, SOLNIK B.
Dependences Structure of International Equity Markets during Extremely Volatile Periods.
Stress Testing : application de la théorie des valeurs extrêmes aux marchés des changes.
1998
98001 TISSOT (de) Olivier
Quelques observations sur les problèmes juridiques posés par la rémunération des artistes interprètes.
98002 MOTTIS Nicolas, PONSSARD J.P.
Incitations et création de valeur dans l’entreprise. Faut-il réinventer Taylor ?
98003 LIOUI A., PONCET Patrice
Trading on Interest Rate Derivatives and the Costs of Marking-to-market.
98004 DEMEESTERE René
La comptabilité de gestion : une modélisation de l’entreprise ?
La mise en œuvre du droit à rémunération d’un comédien ayant « doublé » une œuvre audiovisuelle
er
(film cinématographique ou fiction télévisée ) avant le 1 janvier 1986.
98006 KUESTER Sabine, HOMBURG C., ROBERTSON T.S.
Retaliatory Behavior to New Product Entry.
98007 MONTAGUTI E., KUESTER Sabine, ROBERTSON T.S.
Déterminants of « Take-off » Time for Emerging Technologies: A Conceptual Model and Propositional
Inventory.
98008 KUESTER Sabine, HOMBURG C .
An Economic Model of Organizational Buying Behavior.
98009 BOURGUIGNON Annick
Images of Performance: Accounting is not Enough.
A model of Manager Corruption in Developing Countries with Macroeconomic Implications.
98011 VRANCEANU Radu, WARIN T.
Une étude théorique de la coordination budgétaire en union monétaire.
98012 BANDYOPADHYAU D. K.
A Multiple Criteria Decision Making Approach for Information System Project Section.
98013 NGUYEN P., PORTAIT Roland
Dynamic Mean-variance Efficiency and Strategic Asset Allocation with a Solvency Constraint.
98014 CONTENSOU François
Heures supplémentaires et captation du surplus des travailleurs.
98015 GOMEZ M.L.
De l’apprentissage organisationnel à la construction de connaissances organisationnelles.
98016 BOUYSSOU Denis
Using DEA as a Tool for MCDM: some Remarks.
98017 INDJEHAGOPIAN Jean-Pierre, LANTZ F., SIMON V.
Page 3
Dynamique des prix sur le marché des fiouls domestiques en Europe.
98019 PELISSIER-TANON Arnaud
La division du travail, une affaire de prudence.
Prudence et qualité totale. L’apport de la philosophie morale classique à l’étude du ressort psychologique
par lequel les produits satisfont les besoins de leurs utilisateurs.
98021 BRIOLAT Dominique, AKOKA Jacky, WATTIAU Isabelle
Le commerce électronique sur Internet. Mythe ou réalité ?
98022 DARMON René
Equitable Pay for the Sales Force.
Working Time in a Model of Wage-hours Negociation.
98024 BIBARD Laurent
La notion de démocratie.
Recherche et expertise.
Les étapes du processus de conciliation.
Exchange Rate and Medium Distillates Distribution Margins.
Dialogue national pour l’Europe. Essai sur l’identité européenne des français.
98029 TIXIER Maud
What are the Implications of Differing Perceptions in Western, Central and Eastern Europe for Emerging
Management.
98030 TIXIER Maud
Internal Communication and Structural Change. The Case of the European Public Service: Privatisation
And Deregulation.
La crise des bureaux : retournement de cycle ou bulle ? Une revue internationale des recherches.
La comptabilité de gestion dans le secteur public en France.
The Minimum Variance Hedge Ratio Revisited with Stochastic Interest Rates.
Is the Bernoulli Speculator always Myobic in a Complete Information Economy?
More on the Optimal Portfolio Choice under Stochastic Interest Rates.
98036 FAUCHER Hubert
The Value of Dependency is Plant Breeding: A Game Theoretic Analysis.
98037 BOUCHIKHI Hamid, ROND (de) Mark., LEROUX V.
Alliances as Social Facts: A Constructivist of Inter-Organizational Collaboration.
98038 BOUCHIKHI Hamid, KIMBERLY John R.
In Search of Substance: Content and Dynamics of Organizational Identity.
98039 BRIOLAT Dominique, AKOKA Jacky, COMYN-WATTIAU Isabelle
Electronic Commerce on the Internet in France. An Explanatory Survey.
Page 4
Réduction de la durée du travail et complémentarité des niveaux de qualification.
98041 TIXIER Daniel
La globalisation de la relation Producteurs-Distributeurs.
L’évaluation de la performance : un instrument de gestion éclaté.
Benchmarking: from Intentions to Perceptions.
Management Accounting and Value Creation: Value, Yes, but What Value?
A Simple Matching Model of Unemployment and Working Time Determination with Policy Implications.
98046 PORTAIT Roland, BAJEUX-BESNAINOU Isabelle
Pricing Contingent Claims in Incomplete Markets Using the Numeraire Portfolio.
98047 TAKAGI Junko
Changes in Institutional Logics in the US. Health Care Sector: A Discourse Analysis.
98048 TAKAGI Junko
Changing Policies and Professionals: A Symbolic Framework Approach to Organizational Effects on
Physician Autonomy.
L’apprentissage organisationnel bloquée (Groupe Bull 1986-1992) : du signe porteur d’apprentissage au
Piège de l’habitude et de la représentation-miroir.
98050 TAKAGI Junko, ALLES G.
Uncertainty, Symbolic Frameworks and Worker Discomfort with Change.
1999
99001 CHOFFRAY Jean-Marie
Innovation et entreprenariat : De l’idée… au Spin-Off.
99002 TAKAGI Junko
Physician Mobility and Attidudes across Organizational Work Settings between 1987 and 1991.
99003 GUYOT Marc, VRANCEANU Radu
La réduction des budgets de la défense en Europe : économie budgétaire ou concurrence budgétaire ?
99004 CONTENSOU François, LEE Janghyuk
Interactions on the Quality of Services in Franchise Chains: Externalities and Free-riding Incentives.
99005 LIOUI Abraham, PONCET Patrice
International Bond Portfolio Diversification.
99006 GUIOTTO Paolo, RONCORONI Andrea
Infinite Dimensional HJM Dynamics for the Term Structure of Interest Rates.
99007 GROUT de BEAUFORT Viviane, BERNET Anne-Cécile
Les OPA en Allemagne.
99008 GROUT de BEAUFORT Viviane, GENEST Elodie
Les OPA aux Pays-Bas.
99009 GROUT de BEAUFORT Viviane
Les OPA en Italie.
Page 5
99010 GROUT de BEAUFORT Viviane, LEVY M.
Les OPA au Royaume-Uni.
Les OPA en Suède.
st
The Customized Workplace: A New Management Paradigm for the 21 Century.
The Perception of Performance Evaluation Criteria (1): Perception Styles
Performance et contrôle de gestion.
99015 BAJEUX-BESNAINOU Isabelle, JORDAN J., PORTAIT Roland
Dynamic Asset Allocation for Stocks, Bonds and Cash over Long Horizons.
On the Bonds-stock Asset Allocation Puzzle.
99017 TIXIER Daniel
La logistique est-elle l’avenir du Marketing ?
99018 FOURCANS André, WARIN Thierry
Euroland versus USA: A Theoretical Framework for Monetary Strategies.
99019 GATTO Riccardo, JAMMALAMADAKA S.R.
Saddlepoint Approximations and Inference for Wrapped α-stable Circular Models.
99020 MOTTIS Nicolas, PONSSARD Jean-Pierre
Création de valeur et politique de rémunération. Enjeux et pratiques.
99021 STOLOWY Nicole
Les aspects contemporains du droit processuel : règles communes à toutes les juridictions et procédures
devant le Tribunal de Grande Instance.
Les juridictions civiles d’exception et l’étude des processus dans le droit judiciaire privé.
Multivariate Saddlepoint Test for Wrapped Normal Models.
99024 LORINO Philippe, PEYROLLE Jean-Claude
Enquête sur le facteur X. L’autonomie de l’activité pour le management des ressources humaines et pour
le contrôle de gestion.
99025 SALLEZ Alain
Les critères de métropolisation et les éléments de comparaison entre Lyon et d’autres métropoles
françaises.
Réflexions sur l’actualité des procédures pénales et administratives.
99027 MOTTIS Nicolas, THEVENET Maurice
Accréditation et Enseignement supérieur : certifier un service comme les autres…
99028 CERDIN Jean-Luc
International Adjustment of French Expatriate Managers.
99029 BEAUFORT Viviane, CARREY Eric
L’union européenne et la politique étrangère et de sécurité commune : la difficile voie de la construction
d’une identité de défense européenne.
Page 6
How French Law Treats Fraudulent Bankruptcy.
99031 CHEVALIER Anne, LONGIN François
Coût d’investissement à la bourse de Paris.
Les indicateurs de performance dans le pilotage organisationnel.
99033 LARDINOIT Thierry, QUESTER Pascale
Prominent vs Non Prominent Bands: Their Respective Effect on Sponsorship Effectiveness.
Working Time and Unemployment in an Efficiency Wage Model.
99035 EL OUARDIGHI Fouad
La théorie statistique de la décision (I).
2000
00001
CHAU Minh, LIM Terence
The Dynamic Response of Stock Prices Under Asymetric Information and Inventory Costs: Theory and
Evidence
00002
BIBARD Laurent
Matérialisme et spiritualité
00003
BIBARD Laurent
La crise du monde moderne ou le divorce de l’occident.
00004
MATHE Hervé
Exploring the Role of Space and Architecture in Business Education.
00005
MATHE Hervé
Customer Service: Building Highly Innovative Organizations that Deliver Value.
00006
BEAUFORT (de) Viviane
L’Union Européenne et la question autrichienne, ses conséquences éventuelles sur le champ de révision
de la CIG.
00007
MOTTIS Nicolas, PONSSARD Jean-Pierre
Value Creation and Compensation Policy Implications and Practices.
00009
BOURGUIGNON Annick
The Perception of Performance Evaluation Criteria (2): Determinants of Perception Styles.
00010
EL OUARDIGHI Fouad
The Dynamics of Cooperation.
00011
CHOFFRAY Jean-Marie
Innovation et entrepreneuriat : De l’Idée…au Spin-Off. (Version révisée du DR 99001).
00012
LE BON Joël
De l’intelligence économique à la veille marketing et commerciale : vers une nécessaire mise au point
conceptuelle et théorique.
00013
ROND (de) Mark
Reviewer 198 and Next Generation Theories in Strategy.
00014
BIBARD Laurent
Amérique latine : identité, culture et management.
00016
BIBARD Laurent
Les sciences de gestion et l’action.
Page 7
00017
BEAUFORT (de) V.
Les OPA au Danemark.
00018
BEAUFORT (de) V.
Les OPA en Belgique.
00019
BEAUFORT (de) V.
Les OPA en Finlande.
00020
BEAUFORT (de) V.
Les OPA en Irlande.
00021
BEAUFORT (de) V.
Les OPA au Luxembourg.
00022
BEAUFORT (de) V.
Les OPA au Portugal.
00023
BEAUFORT (de) V.
Les OPA en Autriche.
00024
KORCHIA Mickael
Brand Image and Brand Associations.
00025
L’impact des FIE sur les firmes françaises et allemandes : épiphénomène ou influence réelle ?
00026
BIBARD Laurent
Penser la paix entre hommes et femmes.
00027
BIBARD Laurent
Sciences et éthique (Notule pour une conférence).
00028
MARTEL Jocelyn, C.G. FISHER Timothy
Empirical Estimates of Filtering Failure in Court-supervised Reorganization.
00029
MARTEL Jocelyn
Faillite et réorganisation financière : comparaison internationale et évidence empirique.
00030
The Effect of Bankruptcy Reform on the Number of Reorganization Proposals.
00031
The Bankruptcy Decision: Empirical Evidence from Canada.
00032
CONTENSOU François
Profit-sharing Constraints, Efforts Output and Welfare.
00033
CHARLETY-LEPERS Patricia, SOUAM Saïd
Analyse économique des fusions horizontales.
00034
BOUYSSOU Denis, PIRLOT Marc
A Characterization of Asymmetric Concordance Relations.
00035
Nontransitive Decomposable Conjoint Measurement.
00036
A Comparison of Business Bankruptcies across Industries in Canada, 1981-2000.
2001
01001
DEMEESTERE René
Pour une vue pragmatique de la comptabilité.
Page 8
01002
DECLERCK Francis
Non Disponible.
01003
EL OUARDIGHI Fouad, GANNON Frédéric
The Dynamics of Optimal Cooperation.
01004
DARMON René
Optimal Salesforce Quota Plans Under Salesperson Job Equity Constraints.
01005
BOURGUIGNON Annick, MALLERET Véronique, NORREKLIT Hanne
Balanced Scorecard versus French tableau de bord : Beyond Dispute, a Cultural and Ideological
Perspective.
01006
CERDIN Jean-Luc
Vers la collecte de données via Internet : Cas d’une recherche sur l’expatriation.
01012
VRANCEANU Radu
Globalization and Growth: New Evidence from Central and Eastern Europe.
01013
BIBARD Laurent
De quoi s’occupe la sociologie ?
01014
BIBARD Laurent
Introduction aux questions que posent les rapports entre éthique et entreprise.
01015
BIBARD Laurent
Quel XXIème siècle pour l’humanité ?
01016
Value-based Management at the Profit Center Level.
01017
BESANCENOT Damien, KUYNH Kim, VRANCEANU Radu
Public Debt : From Insolvency to Illiquidity Default.
01018
BIBARD Laurent
Ethique de la vie bonne et théorie du sujet : nature et liberté, ou la question du corps.
01019
INDJEHAGOPIAN Jean-Pierre, JUAN S . LANTZ F., PHILIPPE F.
La pénétration du Diesel en France : tendances et ruptures.
01020
BARONI Michel, BARTHELEMY Fabrice, MOKRANE Mahdi
Physical Real Estates: Risk Factors and Investor Behaviour.
01021
01022
BESANCENOT Damien, VRANCEANU Radu
Quality Leaps and Price Distribution in an Equilibrium Search model
01023
BIBARD Laurent
Gestion et Politique
01024
Technological Change, Acquisition of Skills and Wages in a search Economy
01025
Quality Uncertainty and Welfare in a search Economy
01026
MOTTIS N. , PONSARD J.P.,
L’impact des FIE sur le pilotage de l’entreprise
01027
TAPIERO Charles, VALOIS Pierre
The inverse Range Process in a Random Volatibility Random Walk
01028
ZARLOWSKI Ph., MOTTIS N.
Making Managers into Owners An Experimental Research on the impact of Incentive Schemes on
Shareolder Value Creation
Page 9
01029
Incertitude, bien-être et distribution des salaires dans un modèle de recherche d’emploi
Page 10
ESSEC
CE NTRE
DE RECHERCHE
LISTE DES DOCUMENTS DE RECHERCHE DU CENTRE DE RECHERCHE DE L’ESSEC
(Pour se procurer ces documents, s’adresser au CENTRE DE RECHERCHE DE L’ESSEC)
LISTE OF ESSEC RESEARCH CENTER WORKING PAPERS
(Contact the ESSEC RESEARCH CENTER for information on how to obtain copies of these papers)
[email protected]
1997
Reputation in a Model of Economy-wide Privatization.
97002 GURVIEZ P.
The Trust Concept in the Brand-consumers Relationship.
97003 POTULNY S.
L’utilitarisme cognitif de John Stuart Mill.
From Value at Risk to Stress Testing: The Extreme Value Approach.
97005 BIBARD Laurent, PRORIOL G.
Machiavel : entre pensée du pouvoir et philosophie de la modernité.
Value at Risk: une nouvelle méthode fondée sur la théorie des valeurs extrêmes.
Effects of Working Time Constraints on Employment: A Two-sector Model.
Reputation in a Model of Exchange Rate Policy with Incomplete Information.
97009 AKOKA Jacky, BRIOLAT Dominique, WATTIAU Isabelle
La reconfiguration des processus inter-organisationnels.
97010 NGUYEN. P
Bank Regulation by Capital Adequacy and Cash Reserves Requirements.
Beyond the VaR.
Optimal Margin Level in Futures Markets: A Method Based on Extreme Price Movements.
97013 GROUT DE BEAUFORT Viviane
Maastricth II ou la copie à réviser.
97014 ALBIGOT J.G., GROUT DE BEAUFORT V., BONFILLON P.O., RIEGER B .
Perspectives communautaires et européennes sur la réduction du temps de travail.
97015 DEMEESTERE René, LORINO Philippe, MOTTIS Nicolas
Business Process Management: Case Studies of Different Companies and Hypotheses for Further
Research.
Page 1
97016 PERETTI Jean-Marie, HOURQUET P.G., ALIS D.
Hétérogénéité de la perception des déterminants de l’équité dans un contexte international.
97017 NYECK Simon, ROUX Elyette
WWW as a Communication Tool for Luxury Brands: Compared Perceptions of Consumers and
Managers.
L’analyse économique du fonctionnement des marchés immobiliers.
97019 BESANCENOT D., ROCHETEAU G., VRANCEANU Radu
Effects of Currency Unit Substitution in a Search Equilibrium Model.
97020 BOUCHIKHI Hamid
Living with and Building on Complexity: A Constructivist Perspective on Organizations.
97021 GROUT DE BEAUFORT V., GRENOT S., TIXIER A . TSE K.L
Essai sur le Parlement Européen.
97022 BOULIER J.F., DALAUD R., LONGIN François
Application de la théorie des valeurs extrêmes aux marchés financiers.
Théorie stratégique : des approches fondées sur les ressources aux approches fondées sur les processus.
Investment through Retained Earnings and Employment in Transitional Economies.
97025 INGHAM M., XUEREB Jean-Marc
The Evolution of Market Knowledge in New High Technology Firms: An Organizational Learning
Perspective.
97026 KOENING Christian
Les alliances inter-entreprises et la coopération émergente.
Retour sur la négociation de positions : pourquoi intégrer l’autre dans mon équation personnelle ?
Hypothesis Testing by Symbolic Computation.
97029 GATTO Riccardo , JAMMALAMADAKA S. Rao
A conditional Saddlepoint Approximation for Testing Problems.
97030 ROSSI (de) F.X., GATTO Riccardo
High-order Asymptotic Expansions for Robust Tests.
Negotiation and Mediation in France: The Challenge of Skill-based Learnings and Interdisciplinary
Research in Legal Education.
Pédagogie de la négociation : allier théorie et pratique.
97033 WARIN T.
Crédibilité des politiques monétaires en économie ouverte.
97034 FRANCOIS P.
Bond Evaluation with Default Risk: A Review of the Continuous Time Approach.
97035 FOURCANS André, VRANCEANU Radu
Fiscal Coordination in the EMU: A Theoretical and Policy Perspective.
97036 AKOKA Jacky, WATTIAU Isabelle
MeRCI: An Expert System for Software Reverse Engineering.
97037 MNOOKIN R. (traduit par LEMPEREUR Alain)
Page 2
Surmonter les obstacles dans la résolution des conflits.
97038 LARDINOIT Thierry, DERBAIX D.
An Experimental Study of the Effectiveness of Sport Sponsorship Stimuli.
97039 LONGIN François, SOLNIK B.
Dependences Structure of International Equity Markets during Extremely Volatile Periods.
Stress Testing : application de la théorie des valeurs extrêmes aux marchés des changes.
1998
Quelques observations sur les problèmes juridiques posés par la rémunération des artistes interprètes.
98002 MOTTIS Nicolas, PONSSARD J.P.
Incitations et création de valeur dans l’entreprise. Faut-il réinventer Taylor ?
Trading on Interest Rate Derivatives and the Costs of Marking-to-market.
La comptabilité de gestion : une modélisation de l’entreprise ?
La mise en œuvre du droit à rémunération d’un comédien ayant « doublé » une œuvre audiovisuelle
er
(film cinématographique ou fiction télévisée ) avant le 1 janvier 1986.
98006 KUESTER Sabine, HOMBURG C., ROBERTSON T.S.
Retaliatory Behavior to New Product Entry.
98007 MONTAGUTI E., KUESTER Sabine, ROBERTSON T.S.
Déterminants of « Take-off » Time for Emerging Technologies: A Conceptual Model and Propositional
Inventory.
98008 KUESTER Sabine, HOMBURG C .
An Economic Model of Organizational Buying Behavior.
Images of Performance: Accounting is not Enough.
A model of Manager Corruption in Developing Countries with Macroeconomic Implications.
98011 VRANCEANU Radu, WARIN T.
Une étude théorique de la coordination budgétaire en union monétaire.
98012 BANDYOPADHYAU D. K.
A Multiple Criteria Decision Making Approach for Information System Project Section.
98013 NGUYEN P., PORTAIT Roland
Dynamic Mean-variance Efficiency and Strategic Asset Allocation with a Solvency Constraint.
98014 CONTENSOU François
Heures supplémentaires et captation du surplus des travailleurs.
98015 GOMEZ M.L.
De l’apprentissage organisationnel à la construction de connaissances organisationnelles.
98016 BOUYSSOU Denis
Using DEA as a Tool for MCDM: some Remarks.
Page 3
Dynamique des prix sur le marché des fiouls domestiques en Europe.
La division du travail, une affaire de prudence.
Prudence et qualité totale. L’apport de la philosophie morale classique à l’étude du ressort psychologique
par lequel les produits satisfont les besoins de leurs utilisateurs.
98021 BRIOLAT Dominique, AKOKA Jacky, WATTIAU Isabelle
Le commerce électronique sur Internet. Mythe ou réalité ?
98022 DARMON René
Equitable Pay for the Sales Force.
Working Time in a Model of Wage-hours Negociation.
La notion de démocratie.
Recherche et expertise.
Les étapes du processus de conciliation.
Exchange Rate and Medium Distillates Distribution Margins.
Dialogue national pour l’Europe. Essai sur l’identité européenne des français.
98029 TIXIER Maud
What are the Implications of Differing Perceptions in Western, Central and Eastern Europe for Emerging
Management.
98030 TIXIER Maud
Internal Communication and Structural Change. The Case of the European Public Service: Privatisation
And Deregulation.
La crise des bureaux : retournement de cycle ou bulle ? Une revue internationale des recherches.
La comptabilité de gestion dans le secteur public en France.
The Minimum Variance Hedge Ratio Revisited with Stochastic Interest Rates.
Is the Bernoulli Speculator always Myobic in a Complete Information Economy?
More on the Optimal Portfolio Choice under Stochastic Interest Rates.
98036 FAUCHER Hubert
The Value of Dependency is Plant Breeding: A Game Theoretic Analysis.
98037 BOUCHIKHI Hamid, ROND (de) Mark., LEROUX V.
Alliances as Social Facts: A Constructivist of Inter-Organizational Collaboration.
In Search of Substance: Content and Dynamics of Organizational Identity.
98039 BRIOLAT Dominique, AKOKA Jacky, COMYN-WATTIAU Isabelle
Electronic Commerce on the Internet in France. An Explanatory Survey.
Page 4
Réduction de la durée du travail et complémentarité des niveaux de qualification.
98041 TIXIER Daniel
La globalisation de la relation Producteurs-Distributeurs.
L’évaluation de la performance : un instrument de gestion éclaté.
Benchmarking: from Intentions to Perceptions.
Management Accounting and Value Creation: Value, Yes, but What Value?
A Simple Matching Model of Unemployment and Working Time Determination with Policy Implications.
98046 PORTAIT Roland, BAJEUX-BESNAINOU Isabelle
Pricing Contingent Claims in Incomplete Markets Using the Numeraire Portfolio.
98047 TAKAGI Junko
Changes in Institutional Logics in the US. Health Care Sector: A Discourse Analysis.
98048 TAKAGI Junko
Changing Policies and Professionals: A Symbolic Framework Approach to Organizational Effects on
Physician Autonomy.
L’apprentissage organisationnel bloquée (Groupe Bull 1986-1992) : du signe porteur d’apprentissage au
Piège de l’habitude et de la représentation-miroir.
98050 TAKAGI Junko, ALLES G.
Uncertainty, Symbolic Frameworks and Worker Discomfort with Change.
1999
99001 CHOFFRAY Jean-Marie
Innovation et entreprenariat : De l’idée… au Spin-Off.
99002 TAKAGI Junko
Physician Mobility and Attidudes across Organizational Work Settings between 1987 and 1991.
99003 GUYOT Marc, VRANCEANU Radu
La réduction des budgets de la défense en Europe : économie budgétaire ou concurrence budgétaire ?
99004 CONTENSOU François, LEE Janghyuk
Interactions on the Quality of Services in Franchise Chains: Externalities and Free-riding Incentives.
99005 LIOUI Abraham, PONCET Patrice
International Bond Portfolio Diversification.
99006 GUIOTTO Paolo, RONCORONI Andrea
Infinite Dimensional HJM Dynamics for the Term Structure of Interest Rates.
99007 GROUT de BEAUFORT Viviane, BERNET Anne-Cécile
Les OPA en Allemagne.
Les OPA aux Pays-Bas.
99009 GROUT de BEAUFORT Viviane
Les OPA en Italie.
Page 5
99010 GROUT de BEAUFORT Viviane, LEVY M.
Les OPA au Royaume-Uni.
Les OPA en Suède.
st
The Customized Workplace: A New Management Paradigm for the 21 Century.
The Perception of Performance Evaluation Criteria (1): Perception Styles
Performance et contrôle de gestion.
Dynamic Asset Allocation for Stocks, Bonds and Cash over Long Horizons.
On the Bonds-stock Asset Allocation Puzzle.
99017 TIXIER Daniel
La logistique est-elle l’avenir du Marketing ?
99018 FOURCANS André, WARIN Thierry
Euroland versus USA: A Theoretical Framework for Monetary Strategies.
99019 GATTO Riccardo, JAMMALAMADAKA S.R.
Saddlepoint Approximations and Inference for Wrapped α-stable Circular Models.
99020 MOTTIS Nicolas, PONSSARD Jean-Pierre
Création de valeur et politique de rémunération. Enjeux et pratiques.
Les aspects contemporains du droit processuel : règles communes à toutes les juridictions et procédures
devant le Tribunal de Grande Instance.
Les juridictions civiles d’exception et l’étude des processus dans le droit judiciaire privé.
Multivariate Saddlepoint Test for Wrapped Normal Models.
99024 LORINO Philippe, PEYROLLE Jean-Claude
Enquête sur le facteur X. L’autonomie de l’activité pour le management des ressources humaines et pour
le contrôle de gestion.
99025 SALLEZ Alain
Les critères de métropolisation et les éléments de comparaison entre Lyon et d’autres métropoles
françaises.
Réflexions sur l’actualité des procédures pénales et administratives.
99027 MOTTIS Nicolas, THEVENET Maurice
Accréditation et Enseignement supérieur : certifier un service comme les autres…
99028 CERDIN Jean-Luc
International Adjustment of French Expatriate Managers.
99029 BEAUFORT Viviane, CARREY Eric
L’union européenne et la politique étrangère et de sécurité commune : la difficile voie de la construction
d’une identité de défense européenne.
Page 6
How French Law Treats Fraudulent Bankruptcy.
99031 CHEVALIER Anne, LONGIN François
Coût d’investissement à la bourse de Paris.
Les indicateurs de performance dans le pilotage organisationnel.
99033 LARDINOIT Thierry, QUESTER Pascale
Prominent vs Non Prominent Bands: Their Respective Effect on Sponsorship Effectiveness.
Working Time and Unemployment in an Efficiency Wage Model.
99035 EL OUARDIGHI Fouad
La théorie statistique de la décision (I).
2000
00001
CHAU Minh, LIM Terence
The Dynamic Response of Stock Prices Under Asymetric Information and Inventory Costs: Theory and
Evidence
00002
BIBARD Laurent
Matérialisme et spiritualité
00003
BIBARD Laurent
La crise du monde moderne ou le divorce de l’occident.
00004
MATHE Hervé
Exploring the Role of Space and Architecture in Business Education.
00005
MATHE Hervé
Customer Service: Building Highly Innovative Organizations that Deliver Value.
00006
BEAUFORT (de) Viviane
L’Union Européenne et la question autrichienne, ses conséquences éventuelles sur le champ de révision
de la CIG.
00007
Value Creation and Compensation Policy Implications and Practices.
00009
BOURGUIGNON Annick
The Perception of Performance Evaluation Criteria (2): Determinants of Perception Styles.
00010
EL OUARDIGHI Fouad
The Dynamics of Cooperation.
00011
CHOFFRAY Jean-Marie
Innovation et entrepreneuriat : De l’Idée…au Spin-Off. (Version révisée du DR 99001).
00012
LE BON Joël
De l’intelligence économique à la veille marketing et commerciale : vers une nécessaire mise au point
conceptuelle et théorique.
00013
ROND (de) Mark
Reviewer 198 and Next Generation Theories in Strategy.
00014
BIBARD Laurent
Amérique latine : identité, culture et management.
00016
BIBARD Laurent
Les sciences de gestion et l’action.
Page 7
00017
BEAUFORT (de) V.
Les OPA au Danemark.
00018
BEAUFORT (de) V.
Les OPA en Belgique.
00019
BEAUFORT (de) V.
Les OPA en Finlande.
00020
BEAUFORT (de) V.
Les OPA en Irlande.
00021
BEAUFORT (de) V.
Les OPA au Luxembourg.
00022
BEAUFORT (de) V.
Les OPA au Portugal.
00023
BEAUFORT (de) V.
Les OPA en Autriche.
00024
KORCHIA Mickael
Brand Image and Brand Associations.
00025
L’impact des FIE sur les firmes françaises et allemandes : épiphénomène ou influence réelle ?
00026
BIBARD Laurent
Penser la paix entre hommes et femmes.
00027
BIBARD Laurent
Sciences et éthique (Notule pour une conférence).
00028
Empirical Estimates of Filtering Failure in Court-supervised Reorganization.
00029
MARTEL Jocelyn
Faillite et réorganisation financière : comparaison internationale et évidence empirique.
00030
The Effect of Bankruptcy Reform on the Number of Reorganization Proposals.
00031
The Bankruptcy Decision: Empirical Evidence from Canada.
00032
CONTENSOU François
Profit-sharing Constraints, Efforts Output and Welfare.
00033
CHARLETY-LEPERS Patricia, SOUAM Saïd
Analyse économique des fusions horizontales.
00034
A Characterization of Asymmetric Concordance Relations.
00035
Nontransitive Decomposable Conjoint Measurement.
00036
A Comparison of Business Bankruptcies across Industries in Canada, 1981-2000.
2001
01001
DEMEESTERE René
Pour une vue pragmatique de la comptabilité.
Page 8
01002
DECLERCK Francis
Non Disponible.
01003
EL OUARDIGHI Fouad, GANNON Frédéric
The Dynamics of Optimal Cooperation.
01004
DARMON René
Optimal Salesforce Quota Plans Under Salesperson Job Equity Constraints.
01005
BOURGUIGNON Annick, MALLERET Véronique, NORREKLIT Hanne
Balanced Scorecard versus French tableau de bord : Beyond Dispute, a Cultural and Ideological
Perspective.
01006
CERDIN Jean-Luc
Vers la collecte de données via Internet : Cas d’une recherche sur l’expatriation.
01012
VRANCEANU Radu
Globalization and Growth: New Evidence from Central and Eastern Europe.
01013
BIBARD Laurent
De quoi s’occupe la sociologie ?
01014
BIBARD Laurent
Introduction aux questions que posent les rapports entre éthique et entreprise.
01015
BIBARD Laurent
Quel XXIème siècle pour l’humanité ?
01016
Value-based Management at the Profit Center Level.
01017
BESANCENOT Damien, KUYNH Kim, VRANCEANU Radu
Public Debt : From Insolvency to Illiquidity Default.
01018
BIBARD Laurent
Ethique de la vie bonne et théorie du sujet : nature et liberté, ou la question du corps.
01019
INDJEHAGOPIAN Jean-Pierre, JUAN S . LANTZ F., PHILIPPE F.
La pénétration du Diesel en France : tendances et ruptures.
01020
BARONI Michel, BARTHELEMY Fabrice, MOKRANE Mahdi
Physical Real Estates: Risk Factors and Investor Behaviour.
01021
01022
Quality Leaps and Price Distribution in an Equilibrium Search model
01023
BIBARD Laurent
Gestion et Politique
01024
Technological Change, Acquisition of Skills and Wages in a search Economy
01025
Quality Uncertainty and Welfare in a search Economy
01026
MOTTIS N. , PONSARD J.P.,
L’impact des FIE sur le pilotage de l’entreprise
01027
TAPIERO Charles, VALOIS Pierre
The inverse Range Process in a Random Volatibility Random Walk
01028
ZARLOWSKI Ph., MOTTIS N.
Making Managers into Owners An Experimental Research on the impact of Incentive Schemes on
Shareolder Value Creation
Page 9
01029
Incertitude, bien-être et distribution des salaires dans un modèle de recherche d’emploi
Page 10

Physical Real Estate : Risk Factors and Investor Behaviour

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