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Impact Evaluation of the Entreprenant Status in Cotonou
Last registered on April 12, 2018


Trial Information
General Information
Impact Evaluation of the Entreprenant Status in Cotonou
Initial registration date
October 07, 2014
Last updated
April 12, 2018 9:11 AM EDT
Primary Investigator
World Bank
Other Primary Investigator(s)
PI Affiliation
World Bank
PI Affiliation
World Bank
PI Affiliation
World Bank
Additional Trial Information
Start date
End date
Secondary IDs
In developing countries a large majority of small and medium firms operate in the informal sector. In Benin, this is particularly the case and the national statistics agency estimated that the informal sector represented in 2009 up to 70% of the GDP and 95% of employment. This evaluation takes advantage of the creation of a new legal status for small firms by the Government of Benin to study the impact of three different packages of formalization incentives on formalization rate and firm performances. 3,600 informal businesses operating in Cotonou have been randomly allocated into three treatment and one control groups. A first treatment group will only receive information about the new status and the fact that direct and indirect costs of formalization have been highly reduced. A second group of businesses will receive the same information plus access to business training and bank services (access to a bank account) as further incentives to formalize. On a top of that, a last treatment group will have access to tax mediation services. The evaluation goal is to answer the following research questions (i) Do firms voluntarily move into the formal sector if costs of formalization are highly reduced? (ii) What is the optimal package of incentives to increase formalization? (iii) To what extent the fear of tax administration is an important barrier to formalization? (iv) What is the effect of becoming formal on firm performance and access to credit?
External Link(s)
Registration Citation
Benhassine, Najy et al. 2018. "Impact Evaluation of the Entreprenant Status in Cotonou." AEA RCT Registry. April 12. https://doi.org/10.1257/rct.515-4.0.
Former Citation
Benhassine, Najy et al. 2018. "Impact Evaluation of the Entreprenant Status in Cotonou." AEA RCT Registry. April 12. http://www.socialscienceregistry.org/trials/515/history/28126.
Experimental Details
The Entreprenant status is a new Legal status for small firms offers by the Governement of Benin. Direct and indirect cost are much lower with this new status than with the existing ones. This project is studying different packages of incentives to formalization accompanying this new status.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
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

These outcomes will be measured through in-person interviews with firm owners. One survey was conducted in early 2014 prior to program implementation. A first follow up survey will be done after one year and an endline survey will measure medium term impact 2 years after program implementation. The survey instruments will be designed to measure all of these outcomes and to understand the underlying mechanisms.
Administrative data on formalization from the GUFE are also 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 surveys to understand success and/or failure in the various treatment groups.
Finally, in order to conduct a cost effectiveness analysis, data on program costs will also be collected.

Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The experimental design will adress the following research questions:
• Do firms voluntarily move into the formal sector if the costs of formalization are highly reduced?
• What is the optimal package of incentives to increase formalization?
• 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?

To do so, the evaluation will use a randomized control trial (RCT) methodology with a firm level randomization.
Experimental Design Details
1- Selection of the study population: In order to select the study population, a listing survey was conducted in Cotonou. This survey was designed in order to get a representative sample of all business operating in Cotonou including Dantokpa market (the largest market in Benin and one of the largest in West Africa). All firms with fixed location excepting international and nationwide companies were targeted. 7,945 businesses were successfully surveyed. A population of 3,600 businesses was then selected to participate to the study based on the following goals: • Drop firms already formal. • Drop firms that will probably not cooperate in the future or which will be probably difficult to find. • Try to trim the database from (a) firms very close to formalization who would have formalize anyway and (b) firms very far from formalization which would not be interested by the program. • Remove firms that will most probably not been interested. • Reduce the standard deviation of the main outcomes (profit and sales). The 3,600 firms selected for the study have very similar characteristics to the other informal firm not selected. It means that even with these selection criteria, the study kept a good external validity. 2- Evaluation design The 3,600 informal businesses were then randomly allocated into 3 treatment groups and one control group. Data collected during the listing survey on important firm characteristics were used for the stratification (see below for more details). In Group 1, firms will only receive package A of incentives. That is only the information on the new status, on how to formalize and on tax system applicable to the new status. In Group 2, firms will receive package A and package B of incentives. Thus these firms will receive package A and additional incentives to formalization like access to business trainings and services and support to open a bank account in a commercial bank. In Group 3, firms will receive package A, package B and package C of incentives. So in addition to what will receive firms in group 2, they will also receive tax mediation services. In Group 0, firms will not receive any information or incentives. This group will serve as a control group.
Randomization Method
The randomization was done in office using STATA.
The following methodology was used for stratification:
16 strata were created using the variables: Firm owner gender, firm operating in Dantokpa market, trader and firm owner a bank account.
Then inside each stratum a Z-score was created as the average of standardized profit, sale and number of employee. Based on this Z-score, triplets of firms were created and inside each triplet, firms were randomly allocated to 3 groups: group 0, group "1&2", and group3. Each group included 1,200 firms.
Finally, the 1,200 firms in group "1&2" were randomly allocated into group 1 with 300 firms and group 2 with 900 firms.

Randomization Unit
Randomization at the firm level.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
No Cluster (Firm level randomization)
Sample size: planned number of observations
3,600 businesses operating in Cotonou
Sample size (or number of clusters) by treatment arms
Group 1 (only package A) : 300 businesses
Group 2 (packages A+B): 900 businesses
Group 3 (packages A+B+C): 900 businesses
Control group: 1200 businesses
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The sample size of 3,600 firms 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 give us a power of 91.3% to detect a 5 percentage point increase in the formalization rate. Our 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. It would also yield the same power to detect a 5 percentage point increase in the proportion of firms paying taxes or receiving a bank loan. To examine power for continuous outcomes like firm profitability, or amount of sales, we use the data collected during the listing/baseline survey. In this data, standard deviations of both profits and sales are equal to the mean. It means that 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, we will have 81.2% power to detect a 36% increase in firm profits from formalizing. 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, we 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.
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents
Pre-Analysis Plan Entreprenant Status March 2015

MD5: 6af4b1a05664b4b4a8d2450f99406b22

SHA1: 0ee672ce3781bd55805d5c068bce37ee463b8850

Uploaded At: March 24, 2015

Post Trial Information
Study Withdrawal
Is the intervention completed?
Intervention Completion Date
February 15, 2015, 12:00 AM +00:00
Is data collection complete?
Data Collection Completion Date
July 01, 2016, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
3,596 business owners at baseline, Two follow-up surveys were conducted in April–June 2015, and in
May–June 2016. Attrition rates at first and second follow-up surveys
were 11.8% and 15.9 respectively and were not correlated with treatment
Final Sample Size (or Number of Clusters) by Treatment Arms
Group 0 (control): 1,197 business owners. Group 1: 301. Group 2: 899. Group 3: 1,199.
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
Efforts to bring informal firms into the formal sector are often based on a view that this will bring benefits to the firms themselves, or at least benefit governments through increasing the tax base. A randomized experiment based around the introduction of the entreprenant legal status in Benin is used to test these assumptions, along with supplementary efforts to enhance the presumed benefits of formalizing to firms. Few firms register when just given information about the new regime, but our full package of supplementary efforts boosts formalization by 16.3 percentage points. However, this formalization does not bring firms higher sales or profits, and the cost of formalizing these firms exceeds the added taxation they will pay over the next decade. We show how better targeting of these policies towards firms that look more like formal firms to begin with can increase the formalization rate and improve cost-effectiveness.
Benhassine, N., McKenzie, D., Pouliquen, V., and Santini, M. "Does Inducing Informal Firms to Formalize Make Sense? Experimental Evidence from Benin”. Journal of Public Economics, 157, 1-14, January 2018.