1 Impact Evaluation of the “entreprenant status” in Benin Listing

Transcription

Investment Climate Impact Program
Impact Evaluation of the “entreprenant status” in Benin
Listing-baseline Survey Report1
September 2, 2014
Executive Summary
In March and April 2014, the impact evaluation team completed a listing-baseline survey of informal
businesses in Cotonou. This survey was conducted to select the businesses that would be part of the
impact evaluation of the “entreprenant status,” and to collect information on their characteristics before
the program launch.
The survey was conducted by IREEP and involved 40 surveyors, 8 controllers and 4 supervisors. The
impact evaluation team designed the survey instruments, while the survey monitoring was done jointly. In
the end, 19,246 businesses were listed during the survey. Among them, 9,938 businesses were randomly
selected to be surveyed, and 7,945 (about 80%) were successfully surveyed.
Using the information collected during the survey, the impact evaluation team selected 3,600 informal
businesses for the study. The selection was done in order to maximize statistical power of the study and to
keep good external validity.
The 3,600 businesses were then randomly allocated to one control group and three treatment groups.
Important variables such as gender of the owner, business sector of activity, location of the business,
access to banking services, amount of profits, sales and number of employees were used as stratification
variables to ensure that groups would be comparable, and to maximize statistical power. Results from
balance checks comparing business characteristics across control and treatment groups show that the
randomization was done properly and that the groups are well balanced.
Following the completion of this survey, the entreprenant program was officially launched on April 29,
2014. Next steps in the impact evaluation study are the monitoring of the program roll out, the collection
of information about the program, and the preparation of the follow up surveys.
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This note was prepared by Victor Pouliquen and Massimiliano Santini.
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Outline
1.
2.
3.
Overview .............................................................................................................................................. 4
1.1.
Introduction ................................................................................................................................. 4
1.2.
Project Background .................................................................................................................... 4
1.3.
Project components ..................................................................................................................... 5
1.4.
Objectives ..................................................................................................................................... 5
1.4.1.
General purpose .................................................................................................................. 5
1.4.2.
Aim of the impact evaluation.............................................................................................. 5
1.4.3.
Research questions .............................................................................................................. 6
1.4.4.
Policy perspective ................................................................................................................ 6
Methodology......................................................................................................................................... 7
2.1.
Randomization ............................................................................................................................. 7
2.2.
Study design ................................................................................................................................. 7
2.3.
Sample size and sampling strategy ............................................................................................ 8
2.3.1.
Power calculation ................................................................................................................ 8
2.3.2.
Sampling framework ........................................................................................................... 9
2.4.
Variables for data analysis ....................................................................................................... 10
2.5.
Data storage, management and access policy ......................................................................... 11
Objectives and organization of the listing-baseline survey............................................................ 11
3.1.
Objectives ................................................................................................................................... 11
3.2.
Field organization ...................................................................................................................... 11
3.3.
Survey completion rates ............................................................................................................ 12
3.4.
Monitoring done during the survey ......................................................................................... 13
3.4.1.
Monitoring done by the survey company ........................................................................ 13
3.4.2.
Monitoring done by the World Bank Group .................................................................. 13
3.4.3.
Data entry........................................................................................................................... 14
3.5.
4.
Reasons for success .................................................................................................................... 14
Results of the listing-baseline survey: sampling and randomization ............................................ 15
4.1.
Selection of the study population and external validity ......................................................... 15
4.2.
Randomization and balance check........................................................................................... 16
Annex 1: Descriptive statistics on final sample by location ................................................................... 18
Annex 2: Listing-baseline survey ............................................................................................................. 20
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Abbreviations and Acronyms
AFTFW: Finance & Private Sector Development, West & Central Africa Unit
CAFIC: PEP Africa - Investment Climate Business Line
CGA: Centres de Gestion Agrées
CIC: Investment Climate Department
DEC: Development Research Unit
GUFE: Guichet Unique de Formalisation des Entreprises
IE: Impact Evaluation
IREEP: Institut de Recherche Empirique en Economie Politique
OHADA: Organisation pour l'Harmonisation en Afrique du Droit des Affaires
WBG: World Bank Group
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1.
Overview
1.1.
Introduction
In Benin, the great part of the GDP comes from the informal sector, and the overwhelming majority of the
Beninese works in the informal economy. In 2008, the informal sector value added to the GDP was 70.3%
of the total (INSAE, 2009)2. Agricultural activity was almost exclusively informal, and the economic
activity in industry and services was largely informal (63% and 75%). Among the services, almost 90% of
constructions were in the informal sector.
By converse, Benin’s formal economy is dominated by cotton, which is the main source of income for
more than half of the farmers. Regional trade, in particular with Nigeria, is Benin’s main industry, but vast
volume of informal trade takes place between the two countries. Oil products, in particular, are almost
entirely smuggled from Nigeria. Transport, banking and insurance depend greatly on this informal crossborder trade.
According to a 2005 household survey, the informal sector accounts for about 95% of employment in
Benin,3 but the informal sector contributes to less than 3% of national fiscal revenues. However, evidence
of the impact of informal employment on poverty and the living standards is not univocal. For example,
about 80% of households employed in the informal sector use gas lamp to light their houses, whereas
about 64% of households in the formal sector use electricity. While informal jobs provide a safe valve for
the unemployed, they do not provide the same standard of living of formal jobs.
According to a small survey of informal businesses conducted by the WB in 2011, about 35% of
businesses worked in commerce.4 Another study, by Charmes (1993) finds that 80.7% of businesses in
Benin’s urban zones are street vendors.5 According to the first survey, about 60% of small informal
businesses complained about fiscal harassment: once they became known to the fiscal authorities, they
reported being subjected to repeated audits and bribes. The same survey confirmed a significant
productivity gap between formal and informal businesses, with the gap being smaller for the large
informal businesses.
Understanding the main determinants of informality in Benin, and introducing mechanisms to decrease the
size of the informal sector, are among the top priorities for the Government of Benin.
1.2.
Project Background
Following technical assistance provided by the WBG and other donors, OHADA member countries
(Organisation pour l'Harmonisation en Afrique du Droit des Affaires) have adopted a revised General
Commercial Law in December 2010, which came into force in May 2011. Among other provisions, the
new law introduced the legal framework for the entreprenant status, a simplified legal regime specifically
designed for small entrepreneurs, whose intended objective is to facilitate the migration of businesses
operating in the informal sector into the formal sector.
However, the law did not explicit how the entreprenant status would practically function, nor the specific
combination of incentives that it would include, allowing instead each country to fill in the vacuum
2
INSAE (Institut National de la Statistique et de l’Analyse Economique), 2009. Comptes nationaux. INSAE, Cotonou.
INSAE, 2005. “Questionnaire unifi é du bienêtre de base (QUIBB) 2005,” INSAE, Cotonou.
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N. Benjamin and A. A. Mbaye, “The Informal Sector in Francophone Africa. Firm Size, Productivity, and Institutions,” World
Bank, 2012.
5
Charmes, J. 1993. “Estimation and Survey Methods for the Informal Sector,” Centre of Economics and Ethics for Environment
and Development, University of Versailles-St. Quentin en Yvelines. Paper prepared for an ILO international seminar.
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through ad-hoc secondary legislation. Benin, a member of OHADA, is the first OHADA country to roll
out the entreprenant legal status, as part of the impact evaluation program, with support from the WBG.
The Investment Climate Department (CIC), in collaboration with DEC, AFTFW, and CAFIC, has
launched in October 2012 a rigorous impact evaluation of the entreprenant status to assess which package
of incentives targeted to informal businesses is more effective on formalization decisions. Once the
evaluation is completed, the Government will scale up the package of incentives that best incentivize the
businesses to formalize.
1.3.
Project components
This impact evaluation tests three packages of formalization incentives.6 Package A of incentives includes
the following components:
 Regulatory simplification: a streamlined business registration process, including a reduction in
number of steps, time and cost to register;
 Provision of information on the new registration system: information on the new system are given inperson to business owners;
 Provision of tax information: information and clarification on the existing tax regimes applicable to
the entreprenants.
Package B of incentives includes the following components:
 Services and training: services include support to entrepreneurs in the formalization process and, for
example, help in drafting financial statements and business plans; support in bookkeeping; training
include basic accounting and business management, initiation to legal and tax obligations;
 Support with bank services: creation of a bank account (checking or saving) with a commercial bank.
Package C of incentives includes the following components:
 Provision of tax returns certification and tax mediation/counseling services: support on preparing and
certifying the tax declarations; provision of safeguards against arbitrary practices from the tax
administration through mediation services between entreprenants and the tax authority.
The rationale of the interventions follows directly the discussions held with the Government and the
private sector (formal and informal). The Government is keen to assess whether simplifying entry
procedures, and providing access to services and financial services, has any effects on formalization rates.
1.4.
Objectives
1.4.1.
General purpose
The objective of the project is to understand the determinants of formality in Benin, where the majority of
businesses are informal and owned by individual entrepreneurs. The study will offer an important
contribution to both the academic and the policy literatures on informality. In addition, it will provide
rigorous evidence on the impacts of formalization in the African region, whereas now the evidence mainly
comes from studies in Latin America and Southeast Asia.
1.4.2.
Aim of the impact evaluation
The entreprenant status, as formulated by the OHADA law, is a legal status that can apply to a physical
person running a small business, who practices any type of activity (civil, commercial, artisan,
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See chapter 2.2 below for more details on the identification strategy.
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agricultural), with a limited turnover according to the economic activity, and who will incur in lower
registration cost and time. Once the small business adopts the entreprenant status, the threshold should not
be exceeded for more than two consecutive years. Otherwise, the business will lose entreprenant status
and adopt the individual entreprise status.
The entreprenant status can be considered as a package of incentives to formalization that the Government
offers to small business. The implementation of the entreprenant status in Benin offers the ideal
conditions to study the impact of different packages of incentives on formalization decisions, the legal
environment in which businesses operate, and how businesses interact with public authorities. Also, it can
show the impact of different businesses and entrepreneur characteristics as determinants of formalization,
and whether specific incentives carry any tangible benefits for the business and its growth prospects.
The extent to which businesses will actually perceive these benefits as real is unclear and it will be
verified through the impact evaluation. The packages of incentives offered to two groups of small
informal businesses will try to directly reduce the concerns that businesses may have about formalizing.
Specifically, the impact evaluation will analyze the impact that different packages of incentives have on
the formalization rate and various measurements of business performance (i.e., increased turnover,
increased profits, and increased investments). For the purposes of this project, a business formalizes when
it registers at the company register, i.e. the Registre du Commerce et du Crédit Mobilier, RCCM.
1.4.3.
Research questions
The main research questions that the team will address are:
 Do firms voluntarily move into the formal sector if the costs of formalization are highly reduced?
 To what extent the fear of tax administration is an important barrier to formalization?
 What is the effect of becoming formal on firm performance and access to credit?
Following much of the findings obtained by the literature on business regulations, the team hypothesizes
that the entreprenant regime will encourage formalization by making business registration and operations
simpler, cheaper, and fast. However, much of the literature has tested this effect only on medium and
larger firms, whereas there is less evidence on whether this incentive works for micro businesses.
Anecdotal evidence points to informal businesses worrying about the risks of harassment from inspectors,
and the uncertainty connected with unclear tax systems. The team hypothesizes that the availability of a
tax mediator to defend the interests of the newly formalized tax payers can significantly contribute to
formalization decisions.
Finally, the literature has proven inconclusive on whether bank financing is a major channel through
which formalization can improve firm performance. The team hypothesizes that newly formalized
businesses require more than just their formal certification in order to access bank financing: for example,
an easy access to banks, like opening a checking account.
1.4.4.
Policy perspective
Understanding the effect of different ways to implement the entreprenant status is a critical issue to
introduce the right policies for promoting formalization. There is the perception that becoming formal and
having a tax and registration identification number should improve the credit risk of the business and its
chances to obtain credit. At the same time, facilitating small enterprises’ compliance with tax obligations
should be considered by businesses as an advantage with respect to the current convoluted tax system. The
impact evaluation will test the effect of increasing the predictability of what newly formalized businesses
will pay, and offer them protection during inspectors visit.
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Eventually, after the completion of the impact evaluation, the package of incentive that will result as being
more successful in attracting informal businesses to the formal sector will be scaled up and adopted by the
Government as the official entreprenant status. The Government will also need to factor in the decision a
cost-effectiveness and/or a cost-benefit analysis of the scale up, in addition to the capacity needed by the
agencies in charge of each part of the interventions.
In addition, the entreprenant status was introduced concurrently by the new OHADA Commercial law in
17 West African states. Accordingly, it is likely that the lessons learnt by the Government of Benin as a
result of this impact evaluation will have broad policy relevance in other West African states, particularly
on interventions focused on the informal sector.
2.
Methodology
2.1.
Randomization
This impact evaluation is a randomized control trial, the experimental method chosen in our policy
because it will give yield maximal internal validity. Indeed, the random allocation of informal businesses
to treatment and control groups will ensure that businesses in the different groups have on average the
same characteristics prior to program implementation (and are expected to have equivalent trajectories
going forward). So the only difference between the control group and the three treatment groups is the
type of program received (or no program received for the control group). The outcomes observed after the
program implementation will therefore identify the effect of the program.
2.2.
Study design
The randomized control trial is conducted at the level of informal businesses and the assignment is
stratified by business characteristics (using data collected during the listing-baseline survey). The
packages of incentives target the specific segments of the informal sector that are most likely to benefit
from formalizing, like the high-growth segment of informal entrepreneurs.
An eligible population of 3,600 informal businesses was identified through a listing-baseline survey in
Cotonou. These businesses were randomly allocated (at the firm level) into three treatment groups and one
control group. The first group of informal businesses will receive package A of incentives (see below), the
second group packages A and B of incentives, and the third group packages A, B and C. The fourth group
will serve as a comparison group. See previous chapter 1.3 for additional details on the various
interventions, and table 1 below for the organizational chart of the interventions.
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Figure 1: Impact Evaluation Design
2.3.
Sample size and sampling strategy
2.3.1.
Power calculation
Since the random allocation of informal businesses ensures that all businesses have on average the same
characteristics prior to program implementation, the team will be able to identify precisely program
impacts after eight months (midline survey) and two years (endline survey) from the program launch. The
sample size of 3,600 businesses has been calculated to meet two goals:


High statistical power to detect small changes in formalization rates;
Sufficient statistical power to analyze the effect of being formal on firm performances, assuming that
the program has an effect on formalization (i.e., formal businesses increase at least by 25 percentage
point).
Assuming that at most 10% of the businesses in the control group formalize during the study period, a
sample size of 1,000 in each treatment group would return a power of 91.3% to detect a 5 percentage point
increase in the formalization rate. The target is a 25 percentage point increase in formalization, in order to
get sufficient take-up of formality and examine impacts of being formal on other firm outcomes.
The same sample size would also yield the same power to detect a 5 percentage point increase in the
proportion of businesses paying taxes or receiving a bank loan. To examine power for continuous
outcomes like number of tax payments, amount of tax paid, and business profitability, the team requires
further data.
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If the team assumes that the coefficient of variation for business profits is 1, so that the standard deviation
is equal to the mean, and that the autocorrelation is 0.5, then if the treatment leads to a 25 percentage point
increase in the formalization rate, with a baseline and two rounds of follow-up data, using ANCOVA, the
team will have 81.2% power to detect a 36% increase in business profits from formalizing. The team will
attempt to make the baseline sample as homogeneous as possible to reduce the coefficient of variation and
reduce this minimal detectable effect size, as well as maximize the formalization rate.
The above power calculations assume a 100% take up rate and no attrition, but these assumptions may be
unrealistic given the context. However, program take-up is likely to be very high because the organization
in charge of the program is likely to be able to get in touch with most of the informal businesses to deliver
the different treatments. If we expect to reach 95% of informal businesses with our intervention (the “take
up-rate”), then we would need a sample of 1,108 in order to detect a 5 percentage points increase in
formalization rates [1/(0.95)^2)*1000].
In addition, the team may “lose” part of the sample due to attrition (i.e. businesses that we cannot survey
during the follow-up surveys). We think that we will be able to keep the attrition rate below 10% (since
we are only targeting businesses with a fixed location it seems a realistic assumption).
With 10% attrition and a take-up rate of 95%, we get our sample size of 1,200 informal businesses in each
of the three groups, two treatment groups and one control (and one treatment group further split in two
sets of 300 and 900 businesses), for a total number of 3,600 informal businesses.
2.3.2.
Sampling framework
From the previous power calculations, the size needed is 3,600 businesses: 1,200 businesses in each of the
three groups.
The evaluation team has considered first the use of different available databases of entrepreneurs for the
sampling framework:
 Database from the Centre des Impôts des Petites Entreprises, CIPE (the decentralized tax authority
agencies);
 Database from the Projet d'Appui au Développement des Microentreprises, PADME (a microfinance
institution);
 Database from Institut National de Statistique et de l'Analyse Economique, INSAE (the national
statistics office);
Unfortunately, these databases were either too limited (focusing on very specific entrepreneurs) or too old
(the national firm census by INSAE was done in 2008). The team has therefore decided to roll out a
listing-baseline survey, which also provided very useful information on all the businesses in Cotonou, and
thus on the external validity of the study.
More importantly, the listing-baseline survey allowed the team to precisely define the eligibility criteria
for the program. Indeed, in order to maximize take-up of the program, we want to focus on high-end
informal businesses, with a fixed location, which are more likely to benefit the program. Following up
with the businesses will also be easier if we exclude street vendors from the sample.
In the listing-baseline survey, the team has included questions on whether the business is formal, the
entrepreneur’s level of education, age of the business, number of employees, whether the business has
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some form of accounting, access to banking, amount of sales and profit.7 We have precisely defined the
eligible population using this data and knowing that we needed in total 3,600 businesses.
In order to define the eligible population for the program and to target the high-end informal businesses,
the listing-baseline survey have collected information on approximately 9,000 businesses. See Chapter 4.1
for descriptive statistics on the survey.
For the listing survey, we have used two different sampling methods: one for Danktopa market and the
other for the rest of Cotonou. In fact, according to the 2008 census, more than 15% of informal businesses
in Cotonou are located in Danktopa market, and we needed a special sampling procedure for this area:

Sampling framework for Danktopa market: we used a precise map of the market made by SOGEMA
(Société de Gestion des Marchés Autonomes), the public company managing markets in Benin. This
map allowed us to divide geographically the market in small areas. We have then randomly selected
areas in the markets where we surveyed 50% of the businesses (with fixed location).

Sampling framework for other neighborhoods of Cotonou: We were able to get maps of each of the
144 neighborhoods in Cotonou. Those maps are very detailed and allow identifying easily the ilots
(blocks): the official administrative unit below the neighborhoods. We used this administrative unit as
a reference for the listing survey sampling. We then used information given by the tax administration
(and confirmed by the survey company) in order to characterize neighborhoods as high or low firm
density areas. We randomly sampled 38% of ilots in high density neighborhoods and 10% of the ilots
in low density neighborhoods. In each ilots 68% of businesses where surveyed in average.
2.4.
Variables for data analysis
Prior to program implementation, baseline data have been collected on important firm characteristics and
determinant to formalization. Descriptive statistics and results of baseline survey are detailed in Chapter
4.1, while the original survey is on Annex 2.
The key outcomes of interest are:
 Formalization rate
 Business performance (i.e. increased turnover, increased profits, increased investments).
 Intermediary outcomes include:
 Improved business skills
 Improved accounting systems
 increased level of trust
 Increased access to new markets
 Increased level of advertising
 Increased access to banking
 Increased number of tax payments
 Increased amount of tax paid
Long-term impact indicators are:
 Increased employment
 Better standards of living
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The team have paid particular attention on how to define informality to make sure entrepreneurs understand properly what
informality means.
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The survey instruments were designed to measure all these outcomes after the program implementation
and to understand the underlying mechanisms.
Administrative data on formalization are collected every month and matched to the baseline survey data.
These data will allow us to look at the impact on formalization every month.
Data will be also collected on program implementation to better understand the quality of the programs.
This will include detailed monitoring data from the CGA and qualitative survey to understand success
and/or failure in the various treatment groups.
Finally, in order to conduct a cost effectiveness analysis, data on program cost will also be collected.
2.5.
Data storage, management and access policy
All databases will be stored on computers protected with passwords, and a research manager is
responsible for data management. Once the impact evaluation will be completed, all databases (without
any personal identifiable information) will be made publicly available following World Bank Open data
policy.
3.
Objectives and organization of the listing-baseline survey
3.1.
Objectives
As detailed in section 2.3.2 on sampling, the main objective of the listing survey was to get a
representative sample of all businesses operating in Cotonou. From this sample, the eligible population for
the study was defined and from this sub-population the random allocation of informal businesses into
control and treatment groups was done.
Another important objective of this survey is to collect baseline information on important firm
characteristics and determinant of formalization. This will increase the statistical power of the study and
will allow us to perform sub-group analysis. Finally, the last goal of the survey is to collect detailed
contact information in order to limit attrition at future follow-ups and to allow us to match our data with
administrative data on firm formalization.
The listing-baseline questionnaire was designed in order to meet all these goals. To ensure good quality of
the instrument, it was piloted multiple times by the impact evaluation team and was reviewed by program
partners and by the survey company in charge of the survey implementation. The survey instrument is
available on Annex 2.
3.2.
Field organization
IREEP (Institut de Recherche Empirique en Economie Politique) was the survey company in charge of the
survey implementation. In addition to IREEP’s team, a research assistant and a research manager from the
Impact Evaluation Team were involved on a day to day basis in the survey organization and monitoring.
The surveyor training took place one week before the survey launch and lasted 5 days. The training was
conducted jointly by IREEP supervisors and by the World Bank Group research assistant and research
manager, and included theoretical and practical exercises and field tests. Surveyors where selected for the
training based on their working experience and educational level, with at minimum a degree in economics,
sociology, accounting or a related field and at least one previous experience doing survey. 58 surveyors
were invited for the training and at the end of the 5 days, 48 were selected for the field work.
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The team was composed by:
 40 surveyors;
 8 Controllers, each of them in charge of one team of 5 surveyors;
 4 supervisors: in charge of daily monitoring. Each of them in charge of 2 or 3 teams;
 The surveyors were divided into 8 teams: two teams working in Dantokpa market and 6 outside the
market.
3.3.
Survey completion rates
The survey took place on March 4-April 12, 2014.
On the 1,170 ilots (blocks) sampled for the study outside the market and 558 sidewalks sampled in the
market:
 1,164 ilots (99.5%) and 558 (100%) sidewalks were successfully visited by surveyors.
 1 ilots was excluded from the study because the businesses in that block were having a problem with
local administration and refused to answer surveyors’ questions.
 5 ilots were not found on the ground by the surveyors. These ilots do not exist anymore, and the maps
used for the sampling were not up to date.
Overall, 19,246 businesses were listed by surveyors. Among those businesses, 9,938 businesses were
randomly selected to be surveyed. The results were the following:
 7,945 (80%) businesses were successfully surveyed;
 1,000 (10%) businesses refused to be surveyed;
 995 (10%) businesses were dropped because the business owner was not available or not reached after
4 attempts.
Outside the market, 16,193 businesses were listed by surveyors. Among those, 8,266 businesses were
 6,644 (80%) businesses were surveyed successfully;
 741 (9%) businesses refused to be surveyed;
 881 (10%) businesses were dropped because the business owner was not available or not reached after
4 attempts.
Inside the market, 3,053 businesses were listed by surveyors. Among those, 1,672 businesses were
 1,299 (78%) businesses were surveyed successfully;
 259 (15%) businesses refused to be surveyed;
 114 (7%) businesses were dropped out because the business owner was not available or not reached
after 4 attempts.
The team considers these results, in terms of survey completion rates, very good. Indeed, sensitive
questions were asked in the survey, like on the amount of profit, sales and taxes paid: the refusal rate
could have been much higher.
The team also decided to survey only business owners or manager in charge of day to day decisions. The
reason for this is that the program will target only business owners, so we wanted to focus on businesses
which have owners who can easily be reached. This will help us to keep attrition at a minimum during
follow up surveys and to increase take up of the intervention (business owners not available for the
program will be excluded from the study sample). This decision explains why 10% of the businesses were
dropped out from the study sample.
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3.4.
Monitoring done during the survey
3.4.1.
Monitoring done by the survey company
In order to ensure good quality data collection, 6 different types of monitoring were done by IREEP
supervisors:
 Spot check for the sampling protocol: in order to verify that the sampling was done properly. This was
done for about 1000 surveys (13%).
 Accompanying surveyors during survey. This was done by a supervisor with around 500 surveys (6%)
(400 during the first 2 weeks of the survey). It was done by a controller for 13% of the surveys (more
than 1000 surveys).
 Back checks: calling back the respondent to administer him a short back checks survey. No important
issue was found with this type of monitoring. For one survey, there were some discrepancies between
the actual and the back checked surveys. A supervisor visited the firm to clarify the reason and it
turned out that it was due to the respondent been inconsistent. 123 surveys (1.5%) where back checked
by the supervisor.
 Reviewing and editing surveys: both by controllers and supervisors. Controllers reviewed 100% of the
surveys, and supervisors 59% of the surveys. The main mistakes identified with this type of
monitoring were missing answers and inconsistencies between two different answers. When they were
found, surveyors went back to the respondent to correct the questionnaire. For each survey, the
process was reiterated until no mistake was found.
 For all cases of refusal and when the survey was not done because the business owner was still not
available after several attempts, a controller or a supervisor double-checked the problem.
 Surveyors with more difficulties or with survey rates too low or too high were received additional in
person monitoring.
In addition to these processes, a monitoring file was filled out every two days by the survey company in
order to record, for each surveyor, the number of surveys completed, refused or dropped out. This file
allowed the team to follow in real time the survey progress, and to target efficiently field visits for the
supervision team on surveyors with unusual results.
Before sending surveys to the data entry team, another monitoring file was filled out. This file allowed
checking that each survey sent to data entry was actually entered.
3.4.2.
Monitoring done by the World Bank Group
A research assistant and a research manager were sent by the World Bank Group to work in close
collaboration with IREEP, and to report on a regular basis to the impact evaluation team.
The research assistant worked on a day to day basis with IREEP during all the length of the survey. The
research manager was present during the surveyor training and during the first 3 days of the survey.
Besides all the coordination work with IREEP to discuss and solve all problems that happened daily
during the survey, two main types of monitoring where done by the research assistant and the research
manager themselves:
 Accompanying surveyors during surveys and supervising the sampling protocol: 130 survey where
controlled with this method, including 20 during the first 2 days of fieldwork.
 Reviewing and editing surveys: the first 200 surveys done at the beginning of the fieldwork where
reviewed by the research manager or the research assistant. The research assistant also reviewed the
first 300 surveys sent to the data entry team and in average 15 surveys by day on the field. In total
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around 10% (760) of all the surveys were reviewed with this method. The main mistakes identified
with this type of monitoring were missing answers and inconsistencies between two different answers.
When mistakes were found, surveyors were sent back to the respondents to make corrections. The
team determined an upper bound of the error rate for this type of monitoring as 0.8 mistakes per
survey (corresponding to about 5% of the answers provided). This was considered an upper bound
because most surveys were reviewed at the very beginning of the fieldwork, while the error rate was
likely to be better on the whole dataset. Also, the upper bound corresponded to the number of
mistakes found before sending surveyors back to the businesses to make the corrections.
3.4.3.
Data entry
Data entry was conducted by IREEP, following a rigorous protocol defined in coordination with the
Impact Evaluation team.
In order to minimize data entry errors, a data entry interface was specially developed with the software
CSPro. All data entry operators were trained on this software during 3 days before starting to enter
surveys. Each survey was entered twice by two different data entry operators. Discrepancies between the
two entries were reconciled with the questionnaire and corrected.
Once IREEP sent the final database to the Impact Evaluation team, different types of controls where done:
 The Impact Evaluation team first checked that the number of surveys entered corresponds to the
number of surveys completed according to the monitoring files. Discrepancies where double-checked
by IREEP.
 The Impact Evaluation team randomly selected 60 ilots outside the market and 30 sidewalks in the
market and asked IREEP to re-enter all the surveys in those areas. Once these surveys were entered,
the Impact Evaluation team compared these data with those from the final database. Out of more than
40,000 fields not empty, only 11 discrepancies were found. This gives us an error rate less than
0.02%, which is extremely low.8
 The research manager checked all variables to ensure that the database is of good quality, that there
are no impossible values, that the number of missing values and outliers are low enough.
3.5. Reasons for success
The success of the listing survey was a combination of several complementary factors. The following
appear to be the most relevant:
 World Bank Group staff was deeply involved in the day-to-day management decisions and
monitoring. In particular, he survey was jointly managed by the survey company and the World
Bank Group’s Research Assistant and Research Coordinator.
 Considerable effort was place in selecting the appropriate human resources:
o Both the survey company and the Word Bank Group survey management teams had
experienced staff which performed up to their task.
o The required qualification for the surveyors and supervisors was very high (at least a
degree in economics or in a related field and at least one work experience doing survey).
Most of the selected surveyors and controllers already had experience working with
IREEP.
 Survey TORs were very specific on the survey methodology. Indeed, the World Bank Group
research team prepared in advance the sampling strategy, the survey instrument and all the
monitoring tools. This probably contributed to the fact that the survey company had enough time
to focus successfully on survey logistics and management.
8
Usually best practices for good quality data entry recommend and error rates below 1% or 0.5%
14




TORs were very specific on expected results and on how to achieve them. In particular, providing
concrete numbers for each type of error rate was useful for the survey company.
Having a lot of different monitoring tools done by different staff and targeting different types of
bad behaviors.
The fact that the monitoring tools allowed to check the quality of the data collected in real time.
This allowed for improvement in quality between the beginning and the end of the survey.
It was important to only start data entry when the data entry interface was ready and had been
tested by several persons (including someone working with the World Bank Group).
4.
Results of the listing-baseline survey: sampling and randomization
4.1.
Selection of the study population and external validity
As detailed in chapter 3.3, the listing-baseline survey was a success in term of number of survey
completed. Among the 7,945 surveys successfully completed, the team sampled 3,600 businesses for the
study based on different criteria with different goals:
 Exclude businesses already formal;
 Remove businesses that will probably not cooperate in the future or that will be probably difficult to
find;
 Trim the database from (a) businesses very close to formalization who would have formalize anyway,
and (b) businesses very far from formalization which would not be interested by the program;
 Remove businesses that will most probably not been interested (in particular business which already
have access to loan from commercial banks);
 Reduce the standard deviation of the main outcomes (profit and sales) by excluding businesses with
very high or very low levels of profit or sales;
 Keep a good external validity of the study.
Table 1 below provides descriptive statics on business characteristics for the whole population of informal
businesses surveyed, for businesses selected into the study population, and for businesses already formal.
From the table, we observe that the sample is composed by relatively small businesses with 1.2 employees
on average. 55% of businesses are doing trade, 26% work in services and 16% are craftsmen. 63% of
businesses sampled for the study are owned by women. This number is driven up by the high share of
female owners in Dantokpa market (See below tables A1 and A2 for descriptive statistics by location).
Around 30% of businesses owners never went to school and less than 20% of the businesses are doing
some type of accounting.
Formal businesses have on average 3 employees against 1 employee for informal businesses, and their
average monthly profits is around FCFA 220,000 against FCFA 47,000 for informal businesses. Formal
businesses also have more access to the banking system: 80% of their owners owns a bank account,
whereas the same figure is only 20% for informal businesses.
In terms of external validity, the study sample is highly representative of the overall population of
informal businesses of Cotonou. In fact, the sample selected for the study and the overall sample of
informal businesses are very similar. For example, the share of female owners, the age of the owners, the
amount of monthly profits and the average number of employees are almost exactly the same in both
samples.
The standard deviations of profits and sales are much lower in the study population than in the whole
population of informal businesses. This is due to the fact that businesses with extremely high level of
15
profits or sales were removed from the sample. As a result, standard deviations of profits and sales are
equal to their mean. This is an important point to note since this show that our assumption, taken for the
study power calculation, is respected for these two important variables (see section 2.3.1.).
Table 1: Descriptive statistics on final sample
All informal firms
Mean [SD]
N
0.629
7215
SELECTED Sample
Mean [SD]
N
0.629
3600
Already formal
Mean [SD]
N
0.419
608
Firm owner characteristics
Female owner
[0.483]
Age of the owner
39.444
[0.483]
7072
[11.148]
Firm owner has at least some formal
education
Firm characteristics
Trade
0.705
7206
0.276
7216
0.169
7216
0.183
7216
18.577
7215
0.398
7203
1.05
7205
0.161
7215
83 190.87
7211
47 476.38
6736
0.2
3600
18.72
0.377
1.176
0.179
60 553.35
6438
46 671.9
3594
7010
0.222
0.26
608
0.09
608
0.137
606
52.479
606
[106.493]
3597
0.35
608
[0.477]
3600
2.961
608
[4.59]
3598
0.642
604
[0.48]
3600
542 166.8
528
[4434990]
3600
[46558.47]
[0.4]
608
[0.344]
[56492.2]
[145536.8]
Firm owner owns a bank account
0.144
0.584
[0.287]
[0.383]
[297730.5]
Amount of profit in the last month
3600
[1.687]
[0.367]
Total amount of sales in an average week
0.16
606
[0.439]
[0.485]
[1.626]
The firm does any form of accounting
3600
[43.479]
[0.49]
Number of employee
0.262
0.884
[0.493]
[0.351]
[51.451]
Firm owner owns the firm place
3600
[0.367]
[0.387]
Firm area in m²
0.549
589
[0.32]
[0.44]
[0.375]
Business created less than one year ago
3595
[0.498]
[0.447]
Craft
0.712
43.637
[10.525]
[0.453]
[0.5]
Services
3561
[10.386]
[0.456]
0.519
39.454
[0.494]
223 041.2
490
[726068.4]
3517
[0.416]
0.789
582
[0.409]
Taxes
Firm pays taxes
0.47
7109
[0.499]
Amount of taxes paid in the previous year
36 903.52
3133
[36610.46]
Thinks that it's difficult or very difficult to
know in advance how much taxes he/she will
have to pay
4.2.
0.765
[0.424]
0.547
3564
[0.498]
34 883.34
1873
[28646.3]
5001
0.744
[0.436]
0.836
597
[0.371]
387 970.6
435
[2863888]
2669
0.725
[0.447]
520
Randomization and balance check
In order to ensure good balancing of the sample on important business characteristics and to maximize
statistical power, the impact evaluation team decided to stratify the randomization.
The randomization was done in several steps:
- We first created 16 strata using dummy variables for “Dantokpa market”, “business owner is a
woman,” “sector of activity is trade,” and “business owner owns a bank account”;
- Inside each stratum, we calculated a z-score for each business equal to the average of standardized
profits, sales and number of employee;
16
-
Based on their z-score, we ordered businesses inside each stratum and we made triplets;
businesses were then randomly allocated into three groups: control group, “group 1-or-2” and group 3;
Then, the “group 1-or-2” was randomly divided into group 1 and group 2.
Table 2 presents business characteristics in the control group, balance checks with the treatment groups,
and the P-values of joint tests on the hypothesis that all differences between any group and the control
group are equal to zero. We see from that very few coefficients are statistically different from zero. As a
result, we assume that the randomization was properly done and that treatment and control groups are well
balanced.
Table 2: Descriptive statistics and balance check
Mean [SD]
in Control
Group
group 3
N
P-values of joint
test
group1=group2=
group3=0
3600
0.63
3561
0.11
3595
0.163
3600
0.315
3600
0.937
3600
0.884
3600
0.596
3600
0.86
3598
0.678
-1048.507 3600
0.751
Difference between […]
and Control group
group 1
group 2
Female owner
Age of the owner
education
Trade
Services
Craft
Number of employee
0.629
0.001
0
-0.002
[0.483]
(0.003)
(0.002)
(0.002)
39.237
1.14
0.58
-0.188
[10.743]
(0.73)
(0.454)
(0.404)
0.707
-0.034
-0.002
0.026
[0.456]
(0.032)
(0.02)
(0.018)
0.55
-0.007*
0
0
[0.498]
(0.004)
(0.002)
(0.002)
0.259
0.007
-0.001
0.007
[0.438]
(0.023)
(0.014)
(0.013)
0.166
-0.007
-0.01
-0.008
[0.372]
(0.023)
(0.014)
(0.013)
0.137
-0.008
0.009
0.017
[0.344]
(0.025)
(0.016)
(0.014)
1.18
-0.044
-0.021
0.016
[1.681]
(0.092)
(0.057)
(0.051)
0.173
0.013
-0.001
0.015
[0.378]
(0.027)
(0.017)
(0.015)
60822.03
74.833
[57009.83]
(2254.68)
46195.02
[44824.93]
141.754
297.79
(1401.761) (1253.075)
309.459
1161.15
3600
0.788
3564
0.668
1873
0.032**
(2133.701) (1326.547) (1185.839)
Taxes
Firm pays taxes
0.561
-0.014
-0.016
-0.022
[0.496]
(0.033)
(0.021)
(0.018)
-7008.588*** 564.924
808.602
35305
[29625.5] (2639.708) (1680.84) (1476.014)
Notes: Column 1: Standard deviations presented in brackets. Columns 2-4: coefficients and standard errors (in
parentheses) from an OLS regression of the firm owner/firm characteristic on treatment dummies, controlling for strata
dummies (dummies for each triplet). ***, **, * indicate statistical significance at 1, 5 and 10%.
17
Annex 1: Descriptive statistics on final sample by location
Table A1: Descriptive statistics on the final sample Outside Dantokpa Market
Outside Dantokpa Market
All informal firms SELECTED Sample
Already formal
Mean [SD]
N
Mean [SD]
N
0.589
6012
0.327
507
Mean [SD]
N
0.577
2818
Female owner
[0.492]
Age of the owner
38.775
[0.494]
5909
[11.094]
education
Trade
0.72
0.325
6013
0.198
6013
0.212
20.798
6012
1.11
6001
0.157
56130.47
6009
37663.07
0.203
1.321
0.185
5597 50442.31
2818
2812
[0.402]
0.241
0.312
507
0.108
507
0.162
505
61.234
505
[114.66]
2818
3.323
507
[4.923]
2817
0.652
503
[0.477]
2818
559062.5 433
[4875532]
2818
[44961.8]
5835
507
[0.369]
[44295.88]
5302 45525.47
[76589.99]
22.014
0.501
[0.311]
[0.388]
[242788.6]
0.172
505
[0.464]
2818
[1.816]
[0.364]
2818
[48.608]
6012
[1.721]
0.197
0.893
[0.5]
[0.378]
[56.067]
Number of employee
2818
[0.398]
[0.409]
Firm area in m²
0.324
492
[0.309]
[0.468]
6013
[0.398]
0.445
42.817
[10.228]
2813
[0.497]
[0.468]
Craft
0.737
[0.44]
[0.496]
Services
2796
[10.097]
6003
[0.449]
0.437
38.768
[0.47]
233726
398
[787680.9]
2751
[0.428]
0.813
482
[0.39]
Taxes
Firm pays taxes
0.384
5909
[0.486]
46406.85
0.719
[0.45]
18
2783
[0.498]
2104 45792.59
[40484.29]
have to pay
0.452
0.676
[0.468]
496
[0.395]
1202
[29740.37]
3910
0.806
486102.6 341
[3228705]
1965
0.682
[0.466]
424
Table A2: Descriptive statistics on the final sample in Dantokpa Market
Dantokpa Market
All informal firms SELECTED Sample Already formal
Mean [SD]
N
0.827
1203
Mean [SD]
N
0.817
782
Mean [SD]
N
0.881
101
Female owner
[0.378]
Age of the owner
42.846
[0.387]
1163
[10.802]
education
Trade
0.629
1203
0.032
1203
0.028
0.041
1203
7.486
0.751
1202
0.181
216164.6
1202
93277.62
0.187
0.656
0.157
782
0.01
[0.39]
0.155
101
101
101
[0]
101
[0.1]
782
8.703
101
[5.392]
782
1.139
101
[1.105]
781
0.594
782
465157.9
101
[0.494]
95
[1010340]
782
[51727.23]
1175
0
0
[77013.46]
1136 50803.17
1
782
[0.364]
[300297.1]
6.876
1139 96989.32
[462011.9]
0.041
101
[0]
[0.939]
[0.385]
0.027
0.842
[0]
782
[3.657]
1203
[0.975]
0.037
[0.198]
[4.695]
Number of employee
782
[0.162]
1203
[0.198]
Firm area in m²
0.926
97
[0.367]
[0.189]
[0.166]
782
[0.262]
1203
[0.177]
Craft
0.62
47.794
[11.072]
[0.486]
[0.255]
Services
765
[11.028]
[0.483]
0.93
41.962
[0.325]
176817.9
92
[351317.1]
766
[0.362]
0.67
100
[0.473]
Taxes
Firm pays taxes
0.892
1200
[0.31]
17472.02
1029
[12956.72]
have to pay
0.93
[0.255]
19
0.887
781
[0.316]
15341
671
[10552.01]
1091
0.935
[0.247]
0.98
101
[0.14]
31980.85
94
[26929.89]
704
0.917
[0.278]
96
Annex 2: Listing-baseline survey
Questionnaire entreprises Cotonou
(Version 25 - 27/02/2014)
ID saisie : |__|__|__|__|__|__|
TOUJOURS ECRIRE CLAIREMENT EN MAJUSCULE
Code réponses manquantes : Ne sait pas = 9 ; Ne veut pas répondre= 7 ; Pas applicable= 8
A.
Identification
A.1
Date enquête (1ère visite)
(jour/mois/année)
A.2
Heure début
|__|__| h |__|__| min
A.3
Nom, prénom et code enquêteur
Code : |__|__|
A.4
Où est située l’enquête ?
A.5
|__|__|
A.6
Numéro arrondissement
Nom et code du quartier
A.7
Numéro lot
|__|__|__|__|
A.8
Lettre parcelle (voir carte)
A.9
Numéro d’ordre de l’entreprise sur
la carte du lot
Quel est le nom du secteur dans le
marché ?
Quel est le numéro de la rangée de
cette entreprise ? (ex : h1_10b)
Numéro d’ordre sur la carte du
marché faite par le contrôleur
Quel est le numéro SOGEMA de
l’Entreprise (noté sur le mur ou la
porte de l’entreprise)
Identifiant questionnaire :
A.10
A.11
A.12
A.13
A.14
B.
|__|__| /|__|__| /2014
1. [ ] Marché Dantokpa -----> Allez en A.10
2. [ ] En dehors du Marché
Code : |__|__|__|
|__|__|__| -----> Allez en A.14
|__|__|__|
|__|__|__|__|__|__|__|__|__|
B |__|__|__|+__________________ + |__|__|__|
Dantokpa :
100 + Numéro rangée + Numéro d’ordre (A.12)
Hors Dantokpa : Code quartier +Numéro Lot +Numéro d’ordre (A.9)
Adresse et description de l’entreprise (avant de rentrer dans l’entreprise)
B.1
Numéro ou nom de la rue
B.2
Nom de l’entreprise ou inscription _________________________________________________
visible de l’extérieur
_________________________________________________
Type d’activité probable de
1. [ ] Artisanat/production de biens
l’entreprise vue de l’extérieur ?
2. [ ] Services
3. [ ] Commerce
4. [ ] Autre -----------------> Précisez en B.3.a
9. [ ] Ne sait pas
Si autre type d’activité précisez
Point de repère N°1 à côté de
_________________________________________________
l’entreprise [notez entre
parenthèse la distance à ce point] _________________________________________________
B.3
B.3.a
B.4
20
B.5
B.6
B.7
B.8
B.9
parenthèse la distance à ce point]
parenthèse la distance à ce point]
Y a-t-il une enseigne à l’extérieur
de l’entreprise annonçant
l’entreprise?
Quelle est la couleur de la porte de
l’entreprise ?
Coordonnées GPS de l’entreprise :
_________________________________________________
[Uniquement hors du marché
Dantokpa]
Point numéro (mark point #) :
_________________________________________________
_________________________________________________
_________________________________________________
1. [ ] Oui
2. [ ] Non
GPS ID : |__|__|
GPS latitude : |__|__|°|__|__|.|__|__|__|’ Nord
GPS longitude : |__|__|__|°|__|__|.|__|__|__|’ Est
B.10
L’entreprise est-elle ouverte ?
Y a-t-il quelqu’un qui peut vous
renseigner sur la prochaine
ouverture de l’entreprise ?
B.12 Quand l’entreprise va-t-elle
ouvrir ?
B.11
1. [ ] Oui -----------> Allez en C
2. [ ] Non
1. [ ] Oui
2. [ ] Non -----------> Allez en B.13
_________________________________________________
_________________________________________________
B.13  Rangez le questionnaire dans le dossier « entreprises à revisiter » et repassez plus tard dans la
journée ou si cela n’est pas possible votre contrôleur planifiera une autre visite plus tard.
B.14
Date seconde visite
B.15
Heure seconde visite
B.16
L’entreprise est-elle ouverte ?
C.
(jour/mois/année)
|__|__| /|__|__| /2014
|__|__| h |__|__| min
1. [ ] Oui -----------> Allez en C
2. [ ] Non ---> Allez en F.2 (4) et expliquez dans les commentaires
Sélection du répondant à l’enquête :
[Demandez à parler au propriétaire. Si celui-ci est absent, demandez à parler à l’employé qui connait le mieux
l’entreprise]. Expliquez clairement le but de votre visite :
L’IREEP organise une enquête sur les petites et moyennes entreprises de Cotonou. Il s’agit d’un projet de
recherche mené par l’institut de recherche indépendant « IREEP » dans le but de mieux comprendre les
conditions dans lesquelles elles opèrent ainsi que les difficultés et contraintes auxquelles elles font face. Les
résultats de cette enquête permettront de proposer des politiques publiques. Le fait de répondre au
questionnaire et la nature des réponses n’apportent aucun bénéfice direct à l’entreprise. Mais indirectement,
toutes les petites entreprises de Cotonou bénéficieront des résultats de l’enquête, notamment par le biais des
futures politiques mises en œuvre.
*
C.1
Le propriétaire est-il présent ?
1. [ ] Oui --------> Commencez l’enquête en D
2. [ ] Non
C.2
Est-ce qu’un
responsable/gérant/employé
prenant les décisions quotidiennes
2. [ ] Non
21
pour l’entreprise est présent ?
[cet employé doit connaitre très
bien l’entreprise et être d’accord
pour répondre à toutes les
questions (montant des ventes,
impôts…)]
Expliquez que vous devez faire l’enquête avec le propriétaire de l’entreprise.
C.3 Est-il possible d’appeler le
1. [ ] Oui
propriétaire pour prendre un
rendez-vous avec lui pour faire
2. [ ] Non --------> Allez en F.2 et expliquez dans les commentaires
l’enquête ?
Pouvez-vous me donner le nom et le numéro de téléphone du propriétaire ?
C.4 Nom du propriétaire
C.5
C.6
C.7
Numéro du propriétaire
|__|__|__|__|__|__|__|__|
-----> Appelez le propriétaire et expliquez-lui le but de l’enquête ; essayez d’obtenir un rendez-vous le jour
même ou le plus tôt possible.
Le propriétaire accepte-il un
1. [ ] Oui
rendez-vous pour faire l’enquête ?
2. [ ] Non --------> Allez en F.2 et expliquer dans les commentaires
Quand est-ce que le propriétaire
est-il disponible pour faire
l’enquête ?
_________________________________________________
_________________________________________________
_________________________________________________
C.8
 Rangez le questionnaire dans le dossier « entreprises à revisiter » et repassez plus tard dans la journée
si vous avez pu fixer un rendez-vous le jour même. Si cela n’est pas possible votre contrôleur planifiera
une autre visite plus tard.
Date seconde visite
(jour/mois/année)
|__|__| /|__|__| /2014
C.9
Heure seconde visite
C.10
Le propriétaire est-il disponible
pour faire l’enquête ?
D.
Est-ce que le répondant accepte de
participer à l’enquête ?
D.2
Quel est le nom exact de
l’entreprise ?
D.4
D.5
2. [ ] Non ---> Allez en F.2 (4) et expliquez dans les commentaires
Entretien avec le propriétaire (ou un responsable)
D.1
D.3
|__|__| h |__|__| min
1. [ ] Oui
2. [ ] Non -----> Allez en F.2 et expliquez dans les commentaires
_________________________________________________
_________________________________________________
Quel est le nom du propriétaire de
l’entreprise ? [Si plusieurs
propriétaires, prendre celui qui
travaille le plus dans l’entreprise]
Quel est le prénom du propriétaire de
l’entreprise ?
Quel est le surnom du propriétaire ?
22
D.6
Quel est le sexe du propriétaire de
l’entreprise ?
D.7
Quel est l’âge du propriétaire ?
[Si nécessaire faire une approximation]
D.8
Quel est le poste de la personne
enquêtée ?
D.8.a
Si autre poste, précisez
D.9
Nom de la personne enquêtée
D.10
Prénom de la personne enquêtée
D.11
Quel est le sexe de la personne
enquêtée ?
D.12
Numéro de téléphone de l’enquêté ?
Pouvez-vous me donner le numéro de
téléphone du propriétaire ?
D.14 Second numéro
D.13
D.15
Troisième numéro
Pouvez-vous donner un autre contact
à appeler au cas où les autres
numéros ne fonctionneraient pas ?
D.17 Nom et prénom de cette personne
D.16
D.18
Numéro de téléphone
D.19
Second numéro
E.
1. [ ] Masculin
2. [ ] Féminin
|__|__|
1.
2.
3.
4.
[
[
[
[
] Propriétaire principal -----------> Allez en D.13
] Copropriétaire
] Employé permanent
] Autre --------> Précisez en D.8.a
1. [ ] Masculin
2. [ ] Féminin
|__|__|__|__|__|__|__|__|
|__|__|__|__|__|__|__|__|
|__|__|__|__|__|__|__|__|
|__|__|__|__|__|__|__|__|
1. [ ] Oui
2. [ ] Non -----------> Allez en E
|__|__|__|__|__|__|__|__|
|__|__|__|__|__|__|__|__|
Entretien avec le propriétaire (ou un responsable) sur l’entreprise
[Je vais maintenant vous poser quelques questions sur votre entreprise/l’entreprise où vous travaillez.]
Assurer au répondant que les informations collectées sont confidentielles et ne serviront qu’à l’équipe de
recherche. Précisez aussi que les réponses données ne déterminent en rien l’éligibilité pour aucun programme.
E.1
Quelle est l’activité exacte de
_________________________________________________
l’entreprise ? (activité principale)
_________________________________________________
E.2
Code de l’activité (voir codebook)
|__|__|__|__|
E.3
Pouvez-vous me dire quel est le
mode de propriété de l’entreprise ?
Lire les réponses
E.3.a
Si autre mode de propriété, précisez
1.
2.
3.
4.
5.
6.
7.
[
[
[
[
[
[
[
] Un seul propriétaire --------> Allez en E.5
] Plusieurs propriétaires/propriété familiale
] Société privé à responsabilité limité ------>FIN DE L’ÊNQUETE
] Entreprise Publique --------> FIN DE L’ÊNQUETE
] Coopérative de production --------> FIN DE L’ÊNQUETE
] Club ou Association --------> FIN DE L’ÊNQUETE
] Autre --------> Précisez en E.3.a
-------->FIN DE L’ÊNQUETE
23
E.4
Combien y-a-t-il de copropriétaires
de l’entreprise ?
E.5
L’entreprise a-t-elle d’autres annexes ou
boutiques ou centres de production ?
|__|__|
1. [ ] Oui
2. [ ] Non -----------------> Allez en E.7
9. [ ] Ne sait pas
S’agit-t-il de l’unité principale (siège de
1. [ ] Unité principale
l’entreprise) ou d’une unité secondaire ?
2. [ ] Unité secondaire --------> FIN DE L’ÊNQUETE
[Si le répondant ne sait pas, considérer
3. [ ] Lieu de stockage --------> FIN DE L’ÊNQUETE
l’unité la plus grosse comme la
9. [ ] Ne sait pas --------> FIN DE L’ÊNQUETE
principale]
E.7 Pouvez-vous me dire quand cette
1. [ ] Il y a moins de 1 an
entreprise a-t-elle été créée ?
2. [ ] Entre 1 an et 2 ans
[Si nécessaire faire une approximation]
3. [ ] Entre 2 ans et 5 ans
4. [ ] Plus de 5 ans
9. [ ] Ne sait pas
E.8 En plus de cette entreprise, le
1. [ ] Oui
propriétaire possède-t-il une ou
2. [ ] Non
plusieurs autres entreprises ?
9. [ ] Ne sait pas
E.9 Est-ce que l’entreprise a un toit en
1. [ ] Oui
durs (Béton, tuiles, …)?
2. [ ] Non
E.10 Est-ce que l’entreprise a un sol en durs ? 1. [ ] Oui
(carrelage, dalle de béton…)
2. [ ] Non
E.11 Quelle est la superficie (en m²)
|__|__|__|__| m²
approximative de l’entreprise ?
E.12 Est-ce que le propriétaire de l’entreprise 1. [ ] Oui
possède le local de l’entreprise ?
2. [ ] Non
E.13.a L’entreprise est-elle connectée au
1. [ ] Oui
réseau d’électricité ?
2. [ ] Non
E.13.b L’entreprise possède-t-elle au moins un
1. [ ] Oui
générateur électrique?
2. [ ] Non
E.14 Quel est le plus haut niveau d’éducation
1. [ ] Niveau école primaire (classe CI au CM2)
atteint par le propriétaire?
2. [ ] Niveau collège jusqu’au BEPC (classe 6ème à 3ème)
3. [ ] Niveau collège après le BEPC (2nd à Terminale), ou le CAP
4. [ ] Niveau Supérieur (après le Bac ou DTI, Université)
5. [ ] Jamais été à l’école
6. [ ] Autre précisez ------------------> Précisez en E.14.a
9. [ ] Ne sait pas
E.14.a Si autre niveau précisez
E.6
E.15
Le propriétaire a-t-il fait un
apprentissage ?
E.16
En plus de l’éducation que le
propriétaire a pu recevoir à l’école,
collège, lycée ou dans l’éducation
supérieure, est-ce que le propriétaire a
1. [ ] Oui
2. [ ] Non
9. [ ] Ne sait pas
1. [ ] Oui
2. [ ] Non
9. [ ] Ne sait pas
24
déjà participé à une formation visant à
améliorer ses compétences en affaires
ou gestion ?
[Ne pas inclure l’apprentissage]
Pour les types de travailleurs suivants, dites-moi combien travaillent actuellement dans votre entreprise?
Et combien de femmes parmi vos travailleurs. (Pour E.17 à E.21, ne pas inclure le ou les propriétaires)
E.17 Employés permanents [Employé
dont |__|__| femmes
pour une longue durée (> 3mois)] |__|__|
E.18 Employés temporaires [Employé
|__|__|
dont |__|__| femmes
pour une courte durée (< 3mois)]
E.19 Apprentis
|__|__|
dont |__|__| femmes
E.20.a
Stagiaires
E.20.b Aides
familiaux non-salariés
|__|__|
|__|__|
dont |__|__| femmes
dont |__|__| femmes
Au total combien de travailleurs de
tout type sont présents dans
|__|__|
dont |__|__| femmes
l’entreprise actuellement ?
E.22 Votre entreprise est-elle
1. [ ] Oui
enregistrée au Registre du
2. [ ] Non --------------> Allez en E.24
Commerce (ou RCCM ou guichet
9. [ ] Ne sait pas --------------> Allez en E.24
unique ou GUFE) ?
E.23 Pouvez-vous me montrer l’extrait
1. [ ] Oui
de registre du commerce?
2. [ ] Non
E.24 Est-ce que le propriétaire possède
1. [ ] Oui
une « Carte de Commerçant » pour 2. [ ] Non
l’entreprise enquêtée ?
9. [ ] Ne sait pas
1. [ ] Oui
une attestation « provisoire de
2. [ ] Non
commerçant » pour l’entreprise
9. [ ] Ne sait pas
enquêtée ?
1. [ ] Oui
une « Carte d’Artisan » pour
2. [ ] Non
l’entreprise enquêtée ?
9. [ ] Ne sait pas
1. [ ] Oui
un numéro IFU (Identifiant Fiscal
2. [ ] Non
Unique) ?
9. [ ] Ne sait pas
E.28 Est-ce que l’entreprise enregistre
1. [ ] Oui
sur des cahiers ou registres des
2. [ ] Non aucune forme de comptabilité -----> Allez en E.31
informations comme les ventes, les
9. [ ] Ne sait pas
achats ou la trésorerie ?
E.29 De quel type de comptabilité
1. [ ] Comptabilité analytique -----> Allez en E.31
s’agit-il ? [Lire les réponses
2. [ ] Des notes sur les ventes, les stocks ou la production…
possibles]
9. [ ] Ne sait pas
E.21
25
E.30
Quel(s) type(s) d’informations
enregistrez-vous sur ces notes ou
registres ?
a.
b.
c.
d.
e.
f.
g.
Sur les ventes de l’entreprise
Sur les achats de l’entreprise
Sur les coûts à payer par l’entreprise
Sur la trésorerie
Sur vos stocks
Sur vos crédits ou créances
Autre ------> Précisez en E.30.az
Oui
1. [
1. [
1. [
1. [
1. [
1. [
1. [
]
]
]
]
]
]
]
Non
2. [ ]
2. [ ]
2. [ ]
2. [ ]
2. [ ]
2. [ ]
2. [ ]
NSP
9. [
9. [
9. [
9. [
9. [
9. [
9. [
]
]
]
]
]
]
]
E.30.z Si
autre précisez
E.31 Au cours des 6 derniers mois, avez1. [ ] Oui
vous fait de la publicité pour votre
2. [ ] Non
entreprise sous quelque forme que
9. [ ] Ne sait pas
ce soit ?
E.32 Au cours du dernier mois, est-ce
1. [ ] Oui
qu’un de vos clients a demandé à
2. [ ] Non
recevoir un reçu ou une facture
9. [ ] Ne sait pas
après un achat ?
E.33 Quel est le montant total de vos
ventes et gains au cours d’une
|__|__|__|.|__|__|__|.|__|__|__| FCFA
semaine normale ? [Si besoin, aidez Pour une semaine normale
le répondant à faire le calcul]
Au cours du dernier mois, quel a
été le profit généré par votre
entreprise ?
Cela correspond à la différence
|__|__|__|.|__|__|__|.|__|__|__| FCFA
entre tous les revenus/recettes de Pour le dernier mois
votre entreprise et toutes les
dépenses (salaires des employés,
matériaux, taxes…).
E.35 Est-ce que le propriétaire a un
1. [ ] Oui
compte en banque ?
2. [ ] Non
9. [ ] Ne sait pas
E.36 Est-ce que le propriétaire est déjà
1. [ ] Oui
allé voir une banque comme par
2. [ ] Non --------------> Allez en E.38
exemple BOA ou Eco Bank pour
demander un crédit ?
E.37 A-t-il déjà obtenu un crédit auprès
1. [ ] Oui
d’une institution de ce type ?
2. [ ] Non
9. [ ] Ne sait pas
E.38 Est-ce que le propriétaire est déjà
1. [ ] Oui
allé voir une institution de
2. [ ] Non --------------> Allez en E.40
microfinance comme par exemple
9.
[ ] Ne sait pas --------------> Allez en E.40
PADME pour demander un crédit ?
E.39 A-t-il déjà obtenu un crédit auprès
1. [ ] Oui
d’une institution de ce type ?
2. [ ] Non
9. [ ] Ne sait pas
E.40 Est-ce que l’entreprise paye des
1. [ ] Oui
taxes, impôts ou patentes ?
2. [ ] Non --------------> Allez en E.44
E.34
26
E.41
Quel(s) type(s) de
taxe/impôt/patente votre
entreprise paye-t-elle ?
[Ne pas inclure la redevance
payée à la SOGEMA]
E.41.z Si
a.
b.
c.
d.
Patente foraine
Patente (hors Marchés SOGEMA)
TPU
Taxe pour l’utilisation du domaine public
(payée à la mairie)
e. Autre taxe pour la mairie
f. Autre --------------> Précisez en E.41.az
Oui
1. [
1. [
1. [
1. [
]
]
]
]
1. [ ]
1. [ ]
Non
2. [ ]
2. [ ]
2. [ ]
2. [ ]
NSP
9. [
9. [
9. [
9. [
]
]
]
]
2. [ ] 9. [ ]
2. [ ] 9. [ ]
autre précisez
Quel est le montant total des
impôts et taxes de l’entreprise au
|__|__|__|.|__|__|__|.|__|__|__| FCFA
cours de l’année précédente ?
[aidez le répondant à calculer]
E.43 Avez-vous le sentiment que vous
1. [ ] Oui
avez payé plus de taxes que ce que 2. [ ] Non
la loi vous obligerait normalement? 9. [ ] Ne sait pas
E.44 Au cours de l’année 2013, combien 1. [ ] Jamais, pas de visite l’année dernière ---------> Allez en E.46
de fois avez-vous reçu la visite d’un 2. [ ] Une seule fois
inspecteur des impôts ou de
3. [ ] Deux fois
quelqu’un demandant à votre
4. [ ] De 3 à 5 fois
entreprise de payer des taxes ? [Ne
pas inclure la redevance SOGEMA] 5. [ ] Plus de 5 visites
E.45 Pensez-vous que les agents des
1. [ ] Oui
impôts/mairie abusent et vous
2. [ ] Non
demandent de payer trop de
9. [ ] Ne sait pas
taxes ?
E.46 Pensez-vous qu’il est facile de
1. [ ] C’est très facilement prévisible
savoir à l’avance le montant des
2. [ ] C’est plutôt facilement prévisible
impôts que vous allez payer
3. [ ] C’est plutôt difficilement prévisible
chaque année ?
4. [ ] C’est très difficilement prévisible
9. [ ] Ne sait pas
E.42
F.
Résultat de l’enquête
F.1
Heure de fin de l’enquête
F.2
Résultat de l’enquête
F.2.a
Expliquez
F.3
Avez-vous des commentaires relatifs _________________________________________________
au déroulement de l’enquête ?
_________________________________________________
|__|__| h |__|__| min
1.
2.
3.
4.
[
[
[
[
] Enquête achevée
] Enquête incomplète --------------> Expliquez en F.2.a
] L’enquêté a refusé de répondre -----------> Expliquez en F.2.a
] Autre --------------> Expliquez en F.2.a
_________________________________________________
_________________________________________________
_________________________________________________
27
_________________________________________________
F.4
G.
G.1
G.2
G.3
Avez-vous vérifié que le questionnaire 1. [ ] Oui
est rempli correctement en entier ?
Contrôle qualité de l’enquête (réservé au contrôleur)
Nom, prénom et code contrôleur
|__|__|
Etiez-vous présent lors de 1. [ ] Oui
l’entretien ?
2. [ ] Non
Combien d’erreurs avez-vous
|__|__|
trouvé dans le questionnaire ?
28

1 Impact Evaluation of the “entreprenant status” in Benin Listing

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