Formalization Experiment Data 2008-2011
Sri Lanka, 2008 - 2011
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Reference ID
LKA_2008_SLFED_v01_M
Producer(s)
David McKenzie, Suresh de Mel, Christopher Woodruff
Collection(s)
Created on
Oct 23, 2012
Last modified
Sep 26, 2013
Page views
73630
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7066
Identification
Survey ID Number
LKA_2008_SLFED_v01_M
Title
Formalization Experiment Data 2008-2011
Country/Economy
| Name | Country code |
|---|---|
| Sri Lanka | LKA |
Study type
Enterprise Survey [en/oth]
Abstract
The majority of firms in most developing countries are informal. In Sri Lanka only one-fifth of firms operating without paid workers are registered with any government agency. Even among firms employing paid workers, the majority are unregistered with one or more pertinent agencies.
Researchers from the World Bank, Sri Lanka's University of Peradeniya and United Kingdom's University of Warwick designed a field experiment to measure the latent demand for formalization, and the consequences that formalizing has on informal firms. The experiment provided informal firms incentives to formalize. A sample of informal firms with one to 14 paid employees in two largest Sri Lanka cities were divided into four treatment groups and a control group. The first treatment group was given information about the costs and benefits of, and procedures for, registering their firm for tax purposes, and offered reimbursement for the cost of registering, about 1000 Sri Lankan Rupees (LKR). The second, third, and fourth treatment groups were provided the same information and also offered a payment of 10,000 LKR, 20,000 LKR and 40,000 LKR (approximately US$88, $175 and $350 respectively) to register.
Baseline survey was conducted in December 2008 with the sample of 520 businesses. Three follow-up surveys of these same firms were carried out in August 2010, March 2011 and December 2011 to examine whether and how the firms benefited from formalization.
Researchers from the World Bank, Sri Lanka's University of Peradeniya and United Kingdom's University of Warwick designed a field experiment to measure the latent demand for formalization, and the consequences that formalizing has on informal firms. The experiment provided informal firms incentives to formalize. A sample of informal firms with one to 14 paid employees in two largest Sri Lanka cities were divided into four treatment groups and a control group. The first treatment group was given information about the costs and benefits of, and procedures for, registering their firm for tax purposes, and offered reimbursement for the cost of registering, about 1000 Sri Lankan Rupees (LKR). The second, third, and fourth treatment groups were provided the same information and also offered a payment of 10,000 LKR, 20,000 LKR and 40,000 LKR (approximately US$88, $175 and $350 respectively) to register.
Baseline survey was conducted in December 2008 with the sample of 520 businesses. Three follow-up surveys of these same firms were carried out in August 2010, March 2011 and December 2011 to examine whether and how the firms benefited from formalization.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Businesses with one to 14 employees not registered with the Divisional Secretariat (DS) at the time of the baseline survey.
Version
Version Description
v01: Edited, anonymous datasets for public distribution.
Scope
Notes
The scope of the study includes:
- informality,
- small enterprises,
- entrepreneurship,
- personal and business information,
- education and employment background,
- childhood and family background,
- finance and loans,
- assets, income, expenses and profit,
- innovation,
- competitive environment,
- business skills and practices,
- expectations, trust,
- risk attitudes and recall abilities.
- informality,
- small enterprises,
- entrepreneurship,
- personal and business information,
- education and employment background,
- childhood and family background,
- finance and loans,
- assets, income, expenses and profit,
- innovation,
- competitive environment,
- business skills and practices,
- expectations, trust,
- risk attitudes and recall abilities.
Coverage
Geographic Coverage
Two largest cities in Sri Lanka - Colombo and Kandy
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| David McKenzie | World Bank |
| Suresh de Mel | University of Peradeniya, Sri Lanka |
| Christopher Woodruff | University of Warwick, United Kingdom |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| World Bank | |
| Knowledge for Change Program Trust Fund | |
| Department for International Development | DFID |
| Ewing Marion Kauffman Foundation |
Sampling
Sampling Procedure
Researchers randomly selected five Divisional Secretariat Divisions (DS) in each Colombo and Kandy. In December 2008, research assistants went door-to-door in these areas to screen firms, with the goal of surveying approximately 50 unregistered firms in each selected DS. Firms were selected for the baseline survey if they were not registered with the DS, were not in seasonal agriculture or fisheries, had 1 to 14 paid employees, and had an owner aged 20 to 55 who worked at least 20 hours in the enterprise each week. A sixth DS Division was added in Kandy due to difficulty finding enough informal firms which satisfied these criteria. The resulting baseline sample consisted of 520 firms, evenly split between Colombo and Kandy.
The sample size of 520 was randomly assigned by computer into four treatment groups and a control group as follows. Firms were first stratified by province (Colombo or Kandy), industry (retail, manufacturing, or services), whether or not they had more than two paid employees, and whether or not in the baseline survey they had said they would register if someone were to pay the costs, and had also said they perceived some benefit to registration. Then within each of these 24 strata researchers sorted firms according to their sales rank, and formed matched quintuplets. Where the number of firms in a strata was not perfectly divisible by five, the additional firms were randomly assigned within strata to one of the five treatment groups with equal probability. There were 102-105 firms in each treatment group. The stratification variables were chosen on the basis that local regulations make the process of registration slightly different in Colombo and Kandy, while the incentives to register were a priori believed to possibly differ by industry, firm size, and self-professed desire to register.
The sample size of 520 was randomly assigned by computer into four treatment groups and a control group as follows. Firms were first stratified by province (Colombo or Kandy), industry (retail, manufacturing, or services), whether or not they had more than two paid employees, and whether or not in the baseline survey they had said they would register if someone were to pay the costs, and had also said they perceived some benefit to registration. Then within each of these 24 strata researchers sorted firms according to their sales rank, and formed matched quintuplets. Where the number of firms in a strata was not perfectly divisible by five, the additional firms were randomly assigned within strata to one of the five treatment groups with equal probability. There were 102-105 firms in each treatment group. The stratification variables were chosen on the basis that local regulations make the process of registration slightly different in Colombo and Kandy, while the incentives to register were a priori believed to possibly differ by industry, firm size, and self-professed desire to register.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2008-12 | 2011-12 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
- In total, 152 out of the 415 firms which were assigned to one of the four treatment groups did not receive the registration offer. The majority of time (106 cases) this was because the firm was already-registered or quasi-registered at the time of the baseline survey. In 14 cases, the business had closed since the baseline survey, in 18 cases, the owner could not be found in the follow-up, and in 14 cases the business had registered on its own between the baseline survey and the intervention. Five of the owners rejected the offer outright; researchers count these cases as having received the offer. Follow-up visits with the control group revealed 30 firms which were already registered, and a further 12 had closed or moved or couldn't be located.
- The first follow-up was conducted in August 2010, corresponding to a period of between 12 and 18 months after firms were induced to register. Researchers were able to re-interview 465 of the original 520 firms (89%), with such reasons for attrition as not being able to find the owner (20 out of the 55 cases), the owner being abroad (9 out of 55 cases), and firm owners refusing to be re-interviewed (9 out of 55 cases). Researchers cannot reject the null hypothesis that attrition is unrelated to treatment status at conventional significance levels (p=0.17).
- The second follow-up survey was conducted in March 2011, at period averaging 22 months after the start of the intervention. Researchers reached 445 firms in this round, with attrition again unrelated to treatment status (p=0.35).
- The final follow-up survey was conducted in December 2011, an average of 31 months after the treatment. In this last survey 424 firms were interviewed with attrition again unrelated to treatment status (p=0.40). In addition, proxy reports were used to determine whether the business was still open for a further 59 firms. The remaining 37 firm owners were unable to be located, largely due to their having moved out of the study areas.
- The first follow-up was conducted in August 2010, corresponding to a period of between 12 and 18 months after firms were induced to register. Researchers were able to re-interview 465 of the original 520 firms (89%), with such reasons for attrition as not being able to find the owner (20 out of the 55 cases), the owner being abroad (9 out of 55 cases), and firm owners refusing to be re-interviewed (9 out of 55 cases). Researchers cannot reject the null hypothesis that attrition is unrelated to treatment status at conventional significance levels (p=0.17).
- The second follow-up survey was conducted in March 2011, at period averaging 22 months after the start of the intervention. Researchers reached 445 firms in this round, with attrition again unrelated to treatment status (p=0.35).
- The final follow-up survey was conducted in December 2011, an average of 31 months after the treatment. In this last survey 424 firms were interviewed with attrition again unrelated to treatment status (p=0.40). In addition, proxy reports were used to determine whether the business was still open for a further 59 firms. The remaining 37 firm owners were unable to be located, largely due to their having moved out of the study areas.
Data Collectors
| Name |
|---|
| Kandy Consulting Group |
Questionnaires
Questionnaires
Four survey questionnaires were administered during the impact evaluation study.
Note that the December 2011 fourth round survey was originally schedule for September 2011, and so some dates in the English version of the questionnaire still refer to September 2011. The dates were changed to correspond to a December 2011 timeline in the Sinhala version.
Note that the December 2011 fourth round survey was originally schedule for September 2011, and so some dates in the English version of the questionnaire still refer to September 2011. The dates were changed to correspond to a December 2011 timeline in the Sinhala version.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| David McKenzie | World Bank | dmckenzie@worldbank.org |
Citation requirements
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.
David McKenzie, World Bank; Suresh de Mel, University of Peradeniya; Christopher Woodruff, University of Warwick. Sri Lanka Formalization Experiment Data (SLFED) 2008-2011, Ref. LKA_2008_SLFED_v01_M. Dataset downloaded from [URL] on [date].
- 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.
David McKenzie, World Bank; Suresh de Mel, University of Peradeniya; Christopher Woodruff, University of Warwick. Sri Lanka Formalization Experiment Data (SLFED) 2008-2011, Ref. LKA_2008_SLFED_v01_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
DDI Document ID
DDI_LKA_2008_SLFED_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Generation of DDI documentation |
Date of Metadata Production
2012-10-11
DDI Document version
Version 01