Impact Evaluation of the “entreprenant status” in Beninpubdocs.worldbank.org/.../COMPEL-Benin-baselinereport.pdf · Investment Climate Impact Program 1 Impact Evaluation of the

Investment Climate Impact Program

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Impact Evaluation of the “entreprenant status” in Benin

Listing-baseline Survey Report

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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.

1 This note was prepared by Victor Pouliquen and Massimiliano Santini.


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Outline

1. 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

2. 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

3. 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. Reasons for success .................................................................................................................... 14

4. 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 cross-

border 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. 3 INSAE, 2005. “Questionnaire unifi é du bienêtre de base (QUIBB) 2005,” INSAE, Cotonou. 4 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 in-

person 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,

6 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

7 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%


15

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


16

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.).

4.2. 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;

Table 1: Descriptive statistics on final sample

Mean [SD] N Mean [SD] N Mean [SD] N

Firm owner characteristics

Female owner 0.629 7215 0.629 3600 0.419 608

[0.483] [0.483] [0.494]

Age of the owner 39.444 7072 39.454 3561 43.637 589

[11.148] [10.386] [10.525]

0.705 7206 0.712 3595 0.884 606

[0.456] [0.453] [0.32]

Firm characteristics

Trade 0.519 7216 0.549 3600 0.584 608

[0.5] [0.498] [0.493]

Services 0.276 7216 0.262 3600 0.26 608

[0.447] [0.44] [0.439]

Craft 0.169 7216 0.16 3600 0.09 608

[0.375] [0.367] [0.287]

Business created less than one year ago 0.183 7215 0.144 3600 0.137 606

[0.387] [0.351] [0.344]

Firm area in m² 18.577 7203 18.72 3594 52.479 606

[51.451] [43.479] [106.493]

Firm owner owns the firm place 0.398 7205 0.377 3597 0.35 608

[0.49] [0.485] [0.477]

Number of employee 1.05 7215 1.176 3600 2.961 608

[1.626] [1.687] [4.59]

The firm does any form of accounting 0.161 7211 0.179 3598 0.642 604

[0.367] [0.383] [0.48]

Total amount of sales in an average week 83 190.87 6736 60 553.35 3600 542 166.8 528

[297730.5] [56492.2] [4434990]

Amount of profit in the last month 47 476.38 6438 46 671.9 3600 223 041.2 490

[145536.8] [46558.47] [726068.4]

Firm owner owns a bank account 0.2 7010 0.222 3517 0.789 582

[0.4] [0.416] [0.409]

Taxes

Firm pays taxes 0.47 7109 0.547 3564 0.836 597

[0.499] [0.498] [0.371]

Amount of taxes paid in the previous year 36 903.52 3133 34 883.34 1873 387 970.6 435

[36610.46] [28646.3] [2863888]

0.765 5001 0.744 2669 0.725 520

[0.424] [0.436] [0.447]

Thinks that it's difficult or very difficult to

know in advance how much taxes he/she will

have to pay

Firm owner has at least some formal

education

All informal firms SELECTED Sample Already formal


17

- 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

group 1 group 2 group 3


Female owner 0.629 0.001 0 -0.002 3600 0.63

[0.483] (0.003) (0.002) (0.002)

Age of the owner 39.237 1.14 0.58 -0.188 3561 0.11

[10.743] (0.73) (0.454) (0.404)


education 0.707 -0.034 -0.002 0.026 3595 0.163

[0.456] (0.032) (0.02) (0.018)


Trade 0.55 -0.007* 0 0 3600 0.315

[0.498] (0.004) (0.002) (0.002)

Services 0.259 0.007 -0.001 0.007 3600 0.937

[0.438] (0.023) (0.014) (0.013)

Craft 0.166 -0.007 -0.01 -0.008 3600 0.884

[0.372] (0.023) (0.014) (0.013)

Business created less than one year ago 0.137 -0.008 0.009 0.017 3600 0.596

[0.344] (0.025) (0.016) (0.014)

Number of employee 1.18 -0.044 -0.021 0.016 3600 0.86

[1.681] (0.092) (0.057) (0.051)

The firm does any form of accounting 0.173 0.013 -0.001 0.015 3598 0.678

[0.378] (0.027) (0.017) (0.015)

Total amount of sales in an average week 60822.03 74.833 297.79 -1048.507 3600 0.751

[57009.83] (2254.68) (1401.761) (1253.075)

Amount of profit in the last month 46195.02 141.754 309.459 1161.15 3600 0.788

[44824.93] (2133.701) (1326.547) (1185.839)

Taxes

Firm pays taxes 0.561 -0.014 -0.016 -0.022 3564 0.668

[0.496] (0.033) (0.021) (0.018)

Amount of taxes paid in the previous year 35305 -7008.588*** 564.924 808.602 1873 0.032**

[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%.

Mean [SD]

in Control

Group

Difference between […]

and Control group

N

P-values of joint

test

group1=group2=

group3=0


18

Annex 1: Descriptive statistics on final sample by location

Table A1: Descriptive statistics on the final sample Outside Dantokpa Market



Female owner 0.589 6012 0.577 2818 0.327 507

[0.492] [0.494] [0.47]

Age of the owner 38.775 5909 38.768 2796 42.817 492

[11.094] [10.097] [10.228]

0.72 6003 0.737 2813 0.893 505

[0.449] [0.44] [0.309]


Trade 0.437 6013 0.445 2818 0.501 507

[0.496] [0.497] [0.5]

Services 0.325 6013 0.324 2818 0.312 507

[0.468] [0.468] [0.464]

Craft 0.198 6013 0.197 2818 0.108 507

[0.398] [0.398] [0.311]


[0.409] [0.378] [0.369]

Firm area in m² 20.798 6001 22.014 2812 61.234 505

[56.067] [48.608] [114.66]


[1.721] [1.816] [4.923]


[0.364] [0.388] [0.477]

Total amount of sales in an average week 56130.47 5597 50442.31 2818 559062.5 433

[242788.6] [44295.88] [4875532]

Amount of profit in the last month 37663.07 5302 45525.47 2818 233726 398

[76589.99] [44961.8] [787680.9]


[0.402] [0.428] [0.39]

Taxes

Firm pays taxes 0.384 5909 0.452 2783 0.806 496

[0.486] [0.498] [0.395]

Amount of taxes paid in the previous year 46406.85 2104 45792.59 1202 486102.6 341

[40484.29] [29740.37] [3228705]

0.719 3910 0.676 1965 0.682 424

[0.45] [0.468] [0.466]



have to pay


education

Already formal

Outside Dantokpa Market

All informal firms SELECTED Sample


19

Table A2: Descriptive statistics on the final sample in Dantokpa Market



Female owner 0.827 1203 0.817 782 0.881 101

[0.378] [0.387] [0.325]

Age of the owner 42.846 1163 41.962 765 47.794 97

[10.802] [11.028] [11.072]

0.629 1203 0.62 782 0.842 101

[0.483] [0.486] [0.367]


Trade 0.93 1203 0.926 782 1 101

[0.255] [0.262] [0]

Services 0.032 1203 0.037 782 0 101

[0.177] [0.189] [0]

Craft 0.028 1203 0.027 782 0 101

[0.166] [0.162] [0]


[0.198] [0.198] [0.1]

Firm area in m² 7.486 1202 6.876 782 8.703 101

[4.695] [3.657] [5.392]


[0.975] [0.939] [1.105]


[0.385] [0.364] [0.494]

Total amount of sales in an average week 216164.6 1139 96989.32 782 465157.9 95

[462011.9] [77013.46] [1010340]

Amount of profit in the last month 93277.62 1136 50803.17 782 176817.9 92

[300297.1] [51727.23] [351317.1]


[0.39] [0.362] [0.473]

Taxes

Firm pays taxes 0.892 1200 0.887 781 0.98 101

[0.31] [0.316] [0.14]

Amount of taxes paid in the previous year 17472.02 1029 15341 671 31980.85 94

[12956.72] [10552.01] [26929.89]

0.93 1091 0.935 704 0.917 96

[0.255] [0.247] [0.278]



have to pay


education

All informal firms SELECTED Sample Already formal

Dantokpa Market


20

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) |__|__| /|__|__| /2014

A.2 Heure début |__|__| h |__|__| min

A.3 Nom, prénom et code enquêteur Code : |__|__|

A.4 Où est située l’enquête ? 1. [ ] Marché Dantokpa -----> Allez en A.10

2. [ ] En dehors du Marché

A.5 Numéro arrondissement |__|__|

A.6 Nom et code du quartier

Code : |__|__|__|

A.7 Numéro lot

|__|__|__|__|

A.8 Lettre parcelle (voir carte)

A.9 Numéro d’ordre de l’entreprise sur la carte du lot

|__|__|__| -----> Allez en A.14

A.10 Quel est le nom du secteur dans le marché ?

A.11 Quel est le numéro de la rangée de cette entreprise ? (ex : h1_10b)

A.12 Numéro d’ordre sur la carte du marché faite par le contrôleur

|__|__|__|

A.13 Quel est le numéro SOGEMA de l’Entreprise (noté sur le mur ou la porte de l’entreprise)

|__|__|__|__|__|__|__|__|__|

A.14 Identifiant questionnaire :

B |__|__|__|+__________________ + |__|__|__| Dantokpa : 100 + Numéro rangée + Numéro d’ordre (A.12) Hors Dantokpa : Code quartier +Numéro Lot +Numéro d’ordre (A.9)

B. 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

_________________________________________________ _________________________________________________

B.3 Type d’activité probable de l’entreprise vue de l’extérieur ?

1. [ ] Artisanat/production de biens

2. [ ] Services

3. [ ] Commerce

4. [ ] Autre -----------------> Précisez en B.3.a

9. [ ] Ne sait pas

B.3.a Si autre type d’activité précisez

B.4 Point de repère N°1 à côté de l’entreprise [notez entre parenthèse la distance à ce point]

_________________________________________________

_________________________________________________


21


_________________________________________________

_________________________________________________


_________________________________________________ _________________________________________________

B.7 Y a-t-il une enseigne à l’extérieur de l’entreprise annonçant l’entreprise?

1. [ ] Oui

2. [ ] Non

B.8 Quelle est la couleur de la porte de l’entreprise ?

B.9 Coordonnées GPS de l’entreprise : [Uniquement hors du marché Dantokpa]

GPS ID : |__|__|

Point numéro (mark point #) :

GPS latitude : |__|__|°|__|__|.|__|__|__|’ Nord

GPS longitude : |__|__|__|°|__|__|.|__|__|__|’ Est

B.10 L’entreprise est-elle ouverte ? 1. [ ] Oui -----------> Allez en C

2. [ ] Non

B.11 Y a-t-il quelqu’un qui peut vous renseigner sur la prochaine ouverture de l’entreprise ?

1. [ ] Oui

2. [ ] Non -----------> Allez en B.13

B.12 Quand l’entreprise va-t-elle ouvrir ?

_________________________________________________ _________________________________________________

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 (jour/mois/année) |__|__| /|__|__| /2014

B.15 Heure seconde visite |__|__| h |__|__| min

B.16 L’entreprise est-elle ouverte ? 1. [ ] Oui -----------> Allez en C

2. [ ] Non ---> Allez en F.2 (4) et expliquez dans les commentaires

C. 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

1. [ ] Oui --------> Commencez l’enquête en D

2. [ ] Non


22

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 propriétaire pour prendre un rendez-vous avec lui pour faire l’enquête ?

1. [ ] Oui

2. [ ] Non --------> Allez en F.2 et expliquez dans les commentaires

Pouvez-vous me donner le nom et le numéro de téléphone du propriétaire ?

C.4 Nom du propriétaire

C.5 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.

C.6 Le propriétaire accepte-il un rendez-vous pour faire l’enquête ?

1. [ ] Oui

2. [ ] Non --------> Allez en F.2 et expliquer dans les commentaires

C.7 Quand est-ce que le propriétaire est-il disponible pour faire l’enquête ?

_________________________________________________

_________________________________________________

_________________________________________________

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.

C.8 Date seconde visite (jour/mois/année) |__|__| /|__|__| /2014

C.9 Heure seconde visite |__|__| h |__|__| min

C.10 Le propriétaire est-il disponible pour faire l’enquête ?

1. [ ] Oui --------> Commencez l’enquête en D

2. [ ] Non ---> Allez en F.2 (4) et expliquez dans les commentaires

D. Entretien avec le propriétaire (ou un responsable)

D.1 Est-ce que le répondant accepte de participer à l’enquête ?

1. [ ] Oui

2. [ ] Non -----> Allez en F.2 et expliquez dans les commentaires

D.2 Quel est le nom exact de l’entreprise ?

_________________________________________________

_________________________________________________

D.3 Quel est le nom du propriétaire de l’entreprise ? [Si plusieurs propriétaires, prendre celui qui travaille le plus dans l’entreprise]

D.4 Quel est le prénom du propriétaire de l’entreprise ?

D.5 Quel est le surnom du propriétaire ?


23

D.6 Quel est le sexe du propriétaire de l’entreprise ?

1. [ ] Masculin

2. [ ] Féminin

D.7 Quel est l’âge du propriétaire ? [Si nécessaire faire une approximation]

|__|__|

D.8 Quel est le poste de la personne enquêtée ?

1. [ ] Propriétaire principal -----------> Allez en D.13

2. [ ] Copropriétaire

3. [ ] Employé permanent

4. [ ] Autre --------> Précisez en D.8.a

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 ?

1. [ ] Masculin

2. [ ] Féminin

D.12 Numéro de téléphone de l’enquêté ? |__|__|__|__|__|__|__|__|

D.13 Pouvez-vous me donner le numéro de téléphone du propriétaire ?

|__|__|__|__|__|__|__|__|

D.14 Second numéro |__|__|__|__|__|__|__|__|

D.15 Troisième numéro |__|__|__|__|__|__|__|__|

D.16 Pouvez-vous donner un autre contact à appeler au cas où les autres numéros ne fonctionneraient pas ?

1. [ ] Oui

2. [ ] Non -----------> Allez en E

D.17 Nom et prénom de cette personne

D.18 Numéro de téléphone |__|__|__|__|__|__|__|__|

D.19 Second numéro |__|__|__|__|__|__|__|__|

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

1. [ ] Un seul propriétaire --------> Allez en E.5

2. [ ] Plusieurs propriétaires/propriété familiale

3. [ ] Société privé à responsabilité limité ------>FIN DE L’ÊNQUETE

4. [ ] Entreprise Publique --------> FIN DE L’ÊNQUETE

5. [ ] Coopérative de production --------> FIN DE L’ÊNQUETE

6. [ ] Club ou Association --------> FIN DE L’ÊNQUETE

7. [ ] Autre --------> Précisez en E.3.a

E.3.a Si autre mode de propriété, précisez -------->FIN DE L’ÊNQUETE


24

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

E.6 S’agit-t-il de l’unité principale (siège de l’entreprise) ou d’une unité secondaire ? [Si le répondant ne sait pas, considérer l’unité la plus grosse comme la principale]

1. [ ] Unité principale

2. [ ] Unité secondaire --------> FIN DE L’ÊNQUETE

3. [ ] Lieu de stockage --------> FIN DE L’ÊNQUETE

9. [ ] Ne sait pas --------> FIN DE L’ÊNQUETE

E.7 Pouvez-vous me dire quand cette entreprise a-t-elle été créée ? [Si nécessaire faire une approximation]

1. [ ] Il y a moins de 1 an

2. [ ] Entre 1 an et 2 ans

3. [ ] Entre 2 ans et 5 ans

4. [ ] Plus de 5 ans

9. [ ] Ne sait pas

E.8 En plus de cette entreprise, le propriétaire possède-t-il une ou plusieurs autres entreprises ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.9 Est-ce que l’entreprise a un toit en durs (Béton, tuiles, …)?

1. [ ] Oui

2. [ ] Non

E.10 Est-ce que l’entreprise a un sol en durs ? (carrelage, dalle de béton…)

1. [ ] Oui

2. [ ] Non

E.11 Quelle est la superficie (en m²) approximative de l’entreprise ?

|__|__|__|__| m²

E.12 Est-ce que le propriétaire de l’entreprise possède le local de l’entreprise ?

1. [ ] Oui

2. [ ] Non

E.13.a L’entreprise est-elle connectée au réseau d’électricité ?

1. [ ] Oui

2. [ ] Non

E.13.b L’entreprise possède-t-elle au moins un générateur électrique?

1. [ ] Oui

2. [ ] Non

E.14 Quel est le plus haut niveau d’éducation atteint par le propriétaire?

1. [ ] Niveau école primaire (classe CI au CM2)

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.15 Le propriétaire a-t-il fait un apprentissage ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

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


25

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 pour une longue durée (> 3mois)]

|__|__| dont |__|__| femmes

E.18 Employés temporaires [Employé pour une courte durée (< 3mois)]

|__|__| dont |__|__| femmes

E.19 Apprentis |__|__| dont |__|__| femmes E.20.a Stagiaires |__|__| dont |__|__| femmes E.20.b Aides familiaux non-salariés |__|__| dont |__|__| femmes E.21 Au total combien de travailleurs de

tout type sont présents dans l’entreprise actuellement ?

|__|__| dont |__|__| femmes

E.22 Votre entreprise est-elle enregistrée au Registre du Commerce (ou RCCM ou guichet unique ou GUFE) ?

1. [ ] Oui

2. [ ] Non --------------> Allez en E.24

9. [ ] Ne sait pas --------------> Allez en E.24

E.23 Pouvez-vous me montrer l’extrait de registre du commerce?

1. [ ] Oui

2. [ ] Non

E.24 Est-ce que le propriétaire possède une « Carte de Commerçant » pour l’entreprise enquêtée ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.25 Est-ce que le propriétaire possède une attestation « provisoire de commerçant » pour l’entreprise enquêtée ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.26 Est-ce que le propriétaire possède une « Carte d’Artisan » pour l’entreprise enquêtée ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.27 Est-ce que le propriétaire possède un numéro IFU (Identifiant Fiscal Unique) ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.28 Est-ce que l’entreprise enregistre sur des cahiers ou registres des informations comme les ventes, les achats ou la trésorerie ?

1. [ ] Oui

2. [ ] Non aucune forme de comptabilité -----> Allez en E.31

9. [ ] Ne sait pas

E.29 De quel type de comptabilité s’agit-il ? [Lire les réponses possibles]

1. [ ] Comptabilité analytique -----> Allez en E.31

2. [ ] Des notes sur les ventes, les stocks ou la production… 9. [ ] Ne sait pas


26

E.30 Quel(s) type(s) d’informations enregistrez-vous sur ces notes ou registres ?

a. Sur les ventes de l’entreprise

b. Sur les achats de l’entreprise

c. Sur les coûts à payer par l’entreprise

d. Sur la trésorerie

e. Sur vos stocks

f. Sur vos crédits ou créances

g. 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, avez-vous fait de la publicité pour votre entreprise sous quelque forme que ce soit ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.32 Au cours du dernier mois, est-ce qu’un de vos clients a demandé à recevoir un reçu ou une facture après un achat ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.33 Quel est le montant total de vos ventes et gains au cours d’une semaine normale ? [Si besoin, aidez

le répondant à faire le calcul]

|__|__|__|.|__|__|__|.|__|__|__| FCFA Pour une semaine normale

E.34 Au cours du dernier mois, quel a été le profit généré par votre entreprise ? Cela correspond à la différence entre tous les revenus/recettes de votre entreprise et toutes les dépenses (salaires des employés, matériaux, taxes…).

|__|__|__|.|__|__|__|.|__|__|__| FCFA

Pour le dernier mois

E.35 Est-ce que le propriétaire a un compte en banque ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.36 Est-ce que le propriétaire est déjà allé voir une banque comme par exemple BOA ou Eco Bank pour demander un crédit ?

1. [ ] Oui

2. [ ] Non --------------> Allez en E.38


E.37 A-t-il déjà obtenu un crédit auprès d’une institution de ce type ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.38 Est-ce que le propriétaire est déjà allé voir une institution de microfinance comme par exemple PADME pour demander un crédit ?

1. [ ] Oui

2. [ ] Non --------------> Allez en E.40


E.39 A-t-il déjà obtenu un crédit auprès d’une institution de ce type ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.40 Est-ce que l’entreprise paye des taxes, impôts ou patentes ?

1. [ ] Oui

2. [ ] Non --------------> Allez en E.44


27


E.41 Quel(s) type(s) de taxe/impôt/patente votre entreprise paye-t-elle ? [Ne pas inclure la redevance payée à la SOGEMA]

a. Patente foraine

b. Patente (hors Marchés SOGEMA)

c. TPU

d. 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. [ ] 2. [ ] 2. [ ]

NSP 9. [ ] 9. [ ] 9. [ ] 9. [ ] 9. [ ] 9. [ ]

E.41.z Si autre précisez

E.42 Quel est le montant total des impôts et taxes de l’entreprise au cours de l’année précédente ? [aidez le répondant à calculer]

|__|__|__|.|__|__|__|.|__|__|__| FCFA

E.43 Avez-vous le sentiment que vous avez payé plus de taxes que ce que la loi vous obligerait normalement?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.44 Au cours de l’année 2013, combien de fois avez-vous reçu la visite d’un inspecteur des impôts ou de quelqu’un demandant à votre entreprise de payer des taxes ? [Ne pas inclure la redevance SOGEMA]

1. [ ] Jamais, pas de visite l’année dernière ---------> Allez en E.46

2. [ ] Une seule fois

3. [ ] Deux fois

4. [ ] De 3 à 5 fois

5. [ ] Plus de 5 visites


E.45 Pensez-vous que les agents des impôts/mairie abusent et vous demandent de payer trop de taxes ?

1. [ ] Oui

2. [ ] Non

9. [ ] Ne sait pas

E.46 Pensez-vous qu’il est facile de savoir à l’avance le montant des impôts que vous allez payer chaque année ?

1. [ ] C’est très facilement prévisible

2. [ ] C’est plutôt facilement prévisible

3. [ ] C’est plutôt difficilement prévisible

4. [ ] C’est très difficilement prévisible

9. [ ] Ne sait pas

F. Résultat de l’enquête F.1 Heure de fin de l’enquête |__|__| h |__|__| min

F.2 Résultat de l’enquête

1. [ ] Enquête achevée

2. [ ] Enquête incomplète --------------> Expliquez en F.2.a

3. [ ] L’enquêté a refusé de répondre -----------> Expliquez en F.2.a

4. [ ] Autre --------------> Expliquez en F.2.a

F.2.a Expliquez

_________________________________________________ _________________________________________________ _________________________________________________

F.3 Avez-vous des commentaires relatifs au déroulement de l’enquête ?

_________________________________________________ _________________________________________________


28

_________________________________________________

F.4 Avez-vous vérifié que le questionnaire est rempli correctement en entier ?

1. [ ] Oui

G. Contrôle qualité de l’enquête (réservé au contrôleur) G.1 Nom, prénom et code contrôleur |__|__|

G.2 Etiez-vous présent lors de l’entretien ?

1. [ ] Oui

2. [ ] Non

G.3 Combien d’erreurs avez-vous trouvé dans le questionnaire ?

|__|__|

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