While there are rigorous studies from Bolivia (McKenzie and Sakho, 2007) and Brazil (Fajnzylber et al, 2009) which suggest that registering to pay taxes does improve the profitability of enterprises, to our knowledge, there are no experimental studies that measure the value of business registration for firms, and in particular there is no knowledge on the benefits for firms in Africa in becoming formal. Moreover, we are also unaware of the extent of heterogeneity that the causal formality-performance relationship could display, in particular if certain types of entrepreneurs – such as female entrepreneurs or entrepreneurs in a particular sector – are better placed to gain than others.
Although there are clear benefits for the state when entrepreneurs and firms register their businesses, including increased tax compliance and the opportunity to better serve the business community with customized programs, it is still unclear how beneficial becoming formal is from the perspective of small businesses in Malawi and in the African context more generally. As Malawi’s Department of the Registrar General (DRG) is streamlining its registration process to increase the registration rate, it is considering outreach campaigns to promote the potential benefits of business registration. Therefore, the DRG is supporting an evaluation to experimentally assess the value of becoming formal for small to medium enterprises and hence the relative importance of this constraint. The DRG will use the results to create incentives for registration in the future (if positive) or to identify other bottlenecks that constrain enterprise performance (if negative).
Furthermore, we will use the experimental design of this study to isolate the relevance of a second constraint often identified as complementary to informality and faced especially by women-entrepreneurs – limited access to formal financial services. We will examine through this study the importance of bank accounts in the name of the business as a means of helping separate household from business money by studying an intervention to incentivize financial inclusion.
[Results are from baseline survey, evaluation is still ongoing]
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Enterprises and households
Variables related to Name, Phone Number, Address, GPS, Email were anonymized.
Lilongwe Urban and Blantyre Urban
Unit of Analysis
Enterprises and households
Producers and sponsors
Authoring entity/Primary investigators
Tigist Assefa Ketema
Innovations for Poverty Action
From the list of all enumeration areas (EAs) in Lilongwe Urban and Blantyre Urban, as defined by the Malawi National Statistics Office (NSO) , 10 were sampled - 5 from Lilongwe Urban and 5 from Blantyre Urban. In addition to those, IPA conducted a market/business area listing exercise to collect information about business areas in the two cities. Three teams of enumerators per urban location will walk through assigned geographical sections of the cities and list any contiguous areas that contain businesses, abstracting from the nature and size of those businesses. From the universe of Business Areas listed, 20 were randomly selected in Lilongwe and 20 in Blantyre for inclusion in BRIE.
After this mapping of business /market areas in Lilongwe and Blantyre, we identified 130 isolated markets or business areas in Lilongwe and 138 in Blantyre. In Lilongwe, the number of markets or shopping centers in each area varies across the areas, with some of them having 21 markets ( area 25) and other areas with just one market.
From this initial list of markets and business areas, for the purpose of this study, we identified 39 business centers. Accordingly with the sampling design, each business center needs to be large enough to include a minimum number of businesses. This would guarantee to find at least 65 non registered businesses within those business centers. Therefore in some cases, whenever the isolated market or shopping center appeared to be too small, other adjacent markets have been added in order to meet the target.
Following these assumptions, some of our business centers appear to be a combination of markets within the same enumeration area (i.e. the one in Area 4) while other ones are the result of merging small markets into a larger one.
The criteria we used to select business centers for our sample were:
? the size of the market ( approximately 120-180 vendors). Some Business Centers include more than 180 vendors as these are mostly big businesses and very likely to be registered.
? the proximity with another market in the same enumeration area or in a close area
For the purpose of this impact evaluation, a Business Center is defined as an area where a market or a number of shops are located. Thus, an area where business activities take place, even if it is not a market itself, it is considered a "Business Center."
In order to select enterprises that would be eligible for the business registration data collection and subsequent implementation, the following criteria were considered:
1. The enterprise must not be registered.
2. The enterprise must be large enough (it must have at least one employee, excluding the owner)
3. The enterprise must operate from a fixed location.(This can be a permanent structure as a shop or house, but also semi-permanent structures as huts/ grass stalls)
In addition to the abovementioned criteria, (monthly) turnover was also considered to screen out very small and marginal businesses which, accordingly with the design of study, would not benefit from the intervention.
The final sample size was 3,002 businesses, 40 percent of which are female-owned (the goal was to reach a rate of 50 percent). 71 percent of the businesses are retail firms, the average monthly sales amount to $ 1,000, an average of two people work in a business and 30 percent of the entrepreneurs have at least secondary education.
After baseline data collection the sample was then split into three treatment groups and one control group:
- Treatment 1: Costless Registration and information sessions + business bank account (1,200)
- Treatment 2: Costless registration (750)
- Treatment 3: Costless Registration + Taxpayer identification number (300)
- Control group: No treatment (750)
Dates of Data Collection (YYYY/MM/DD)
Basline data collection
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download.
Francisco Campos, World Bank. Business Registration Impact Evaluation (BRIE) 2011-2012, Baseline Survey. Ref. MWI_2011_BRIE-BL_v01_M. Dataset downloaded from [url] on [date].