Informal Sector Business Survey 2019
Lao PDR, 2019
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Reference ID
LAO_2019_ISBS_v01_M
Producer(s)
World Bank Group (WBG)
Collection(s)
Metadata
Created on
Jan 09, 2020
Last modified
Jan 09, 2020
Page views
12455
Downloads
582
Identification
Survey ID Number
LAO_2019_ISBS_v01_M
Title
Informal Sector Business Survey 2019
Country/Economy
| Name | Country code |
|---|---|
| Lao PDR | LAO |
Study type
Informal Sector Survey [hh/iss]
Abstract
The 2019 Lao PDR Informal Sector Business Survey (ISBS) data was collected by the World Bank Group - Enterprise Analysis Unit. The survey covers two cities: Vientiane and Pakse.
The primary objectives of the survey are: i) to understand the business demographics of the sector in the two cities, and ii) to describe the environment within which these businesses operate. A secondary objective of the survey is to provide an estimate of the number of informal businesses operating in these cities.
The primary objectives of the survey are: i) to understand the business demographics of the sector in the two cities, and ii) to describe the environment within which these businesses operate. A secondary objective of the survey is to provide an estimate of the number of informal businesses operating in these cities.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Unit of analysis is informal business, where informality is defined based on whether or not a business is formally registered with the government.
Version
Version Description
Version 01. Edited, anonymous dataset for public distribution.
Scope
Notes
The 2019 Lao PDR Informal Sector Business Survey covered the following topics:
- General information
- Location and infrastructure
- Crime
- Sales and supplies
- Business practices
- Finance
- Labor
- Registration
- Assets
- General information
- Location and infrastructure
- Crime
- Sales and supplies
- Business practices
- Finance
- Labor
- Registration
- Assets
Coverage
Geographic Coverage
The survey covers two cities: Vientiane and Pakse.
Universe
The universe includes informal businesses, where informality is defined based on whether or not a business is formally registered with the government.
Producers and sponsors
Primary investigators
| Name |
|---|
| World Bank Group (WBG) |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| World Bank Group | WBG |
Sampling
Sampling Procedure
The 2019 Lao PDR ISBS uses an innovative technique to survey informal businesses. The survey follows an area-based sampling methodology with geographic area rather than an establishment or a business unit as a primary sampling unit. To account for potential clustering of informal business, the survey uses an area-based sampling called (stratified) Adaptive Cluster Sampling (ACS), whereby one selects a sample of starting squares and adaptively samples surrounding squares based on the number of informal firms discovered in the enumerated squares. All informal business in selected squares are enumerated using a 2 to 3-minutes questionnaire, referred to in this document as the short-form questionnaire. The short form questionnaire is a listing questionnaire where basic information about the business is collected. A randomly selected subset of the enumerated businesses is given a 20-minutes questionnaire, referred to in this document as the long-form questionnaire. This is the main questionnaire of the survey and the basis of the database posted on the ES portal.
The survey is adaptive in the sense that if the number of informal units in a square exceeds a predefined threshold, all the squares surrounding the starting square are surveyed, following the same approach of enumeration and randomly conducting the main interview. If one of the surrounding squares exceed the threshold, then the squares surrounding that square in turn are also surveyed. This process continues until either the network is exhausted, or an arbitrary cut-off point is defined.
The first step in the sampling approach is the construction of a spatial grid as the Primary Sampling Units (PSU) frame. The grid covered the total of municipal areas and each cell had a size of 150 by 150 meters. This produced a total of about 17,400 squares between the two cities, excluding squares that are considered inaccessible. The second step was to stratify each grid, with in each city, based on likely concentration of informal business units. The grids were categorized into four strata: three strata of low, medium, and high concentration of informal sector activity, and a market center. The stratification was based on local knowledge of the survey implementing contractor with approval from the World Bank Group task team leader. The third step in the sampling process was to select a pre-defined number of starting squares from each stratum for enumeration and main data.
The survey is adaptive in the sense that if the number of informal units in a square exceeds a predefined threshold, all the squares surrounding the starting square are surveyed, following the same approach of enumeration and randomly conducting the main interview. If one of the surrounding squares exceed the threshold, then the squares surrounding that square in turn are also surveyed. This process continues until either the network is exhausted, or an arbitrary cut-off point is defined.
The first step in the sampling approach is the construction of a spatial grid as the Primary Sampling Units (PSU) frame. The grid covered the total of municipal areas and each cell had a size of 150 by 150 meters. This produced a total of about 17,400 squares between the two cities, excluding squares that are considered inaccessible. The second step was to stratify each grid, with in each city, based on likely concentration of informal business units. The grids were categorized into four strata: three strata of low, medium, and high concentration of informal sector activity, and a market center. The stratification was based on local knowledge of the survey implementing contractor with approval from the World Bank Group task team leader. The third step in the sampling process was to select a pre-defined number of starting squares from each stratum for enumeration and main data.
Weighting
To estimate population parameters, weights are applied to survey samples. In surveys design following standard random sampling, selection probability of all units is known before the actual data collection. Hence, weights can be derived as the inverse of selection probability.
Computation of sampling weights is a bit involved for Adaptive Cluster Sampling (ACS) since final sample size is not known a priori. In ACS, selection probabilities are not known a priori since sampling squares are adaptively added to the sample depending on the number of informal businesses found in a square. In adaptive sampling, one instead talks about empirically derived inclusion probabilities.
Note: Refer to Sampling Weight section in "The 2019 Lao PDR Informal Sector Business Survey Dataset" document for further details on sampling weight.
Computation of sampling weights is a bit involved for Adaptive Cluster Sampling (ACS) since final sample size is not known a priori. In ACS, selection probabilities are not known a priori since sampling squares are adaptively added to the sample depending on the number of informal businesses found in a square. In adaptive sampling, one instead talks about empirically derived inclusion probabilities.
Note: Refer to Sampling Weight section in "The 2019 Lao PDR Informal Sector Business Survey Dataset" document for further details on sampling weight.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2019-01 | 2019-02 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
Enumerators were assigned to starting squares, enumerating all informal business units in selected squares and administering the main questionnaire to a randomly selected subset of the enumerated businesses. This survey was fully implemented using the World Banks' Survey Solutions CAPI system. The selection for long-form (main) questionnaire was conducted in real time (i.e., concurrently with the listing process) using the CAPI system with a random decaying probability of selection; these minimizes issues stemming from the transitory nature of many informal activities. An important feature of the implementation is that enumerators did not have control over who gets selected for an interview with the long-form (main) questionnaire since the CAPI does so randomly. All respondents that were not selected for the long-form were given a short-form questionnaire, which captured information on the type of activity, physical location, and the number of workers. Outright refusals were also recorded, using enumerator observation of the activity, workers observed, and whether the business had any sign and permits on display.
Overall, the enumeration started with a total of 269 starting squares in the two cities combined, and a total of 1,322 squares were enumerated in the end. Out of a total of 7,172 business enumerated, about 361 were randomly selected and responded the main questionnaire (i.e., the long-form), which is the main data file.
Implementation of the actual fieldwork can be daunting given the complicated nature of the sampling methodology. An intensive and extended training and piloting sessions were conducted before the launch of the fieldwork. A three-day intensive training of enumerators and field management team took place followed by two days of piloting in each of the two cities. Based on feedback from this trainings and piloting, necessary changes were made to the questionnaire and CAPI script.
A detailed monitoring protocol was put in place during the data collection phase to ensure the integrity of the fieldwork and methodology. In addition to supervision through assigned supervisors, every enumerator records his/her path using a tracking software (Oruxmaps) installed on to all the CAPI tablets. Enumerators submit captured paths to a centralized server at the end of enumeration of every square. This tracking path is checked to ensure that enumerators have fully covered the square assigned to them. This quality check was done daily, and for cases where the tracking path indicated below acceptable level of effort in listing informal business, the enumerator was asked to re-survey the square.
Overall, the enumeration started with a total of 269 starting squares in the two cities combined, and a total of 1,322 squares were enumerated in the end. Out of a total of 7,172 business enumerated, about 361 were randomly selected and responded the main questionnaire (i.e., the long-form), which is the main data file.
Implementation of the actual fieldwork can be daunting given the complicated nature of the sampling methodology. An intensive and extended training and piloting sessions were conducted before the launch of the fieldwork. A three-day intensive training of enumerators and field management team took place followed by two days of piloting in each of the two cities. Based on feedback from this trainings and piloting, necessary changes were made to the questionnaire and CAPI script.
A detailed monitoring protocol was put in place during the data collection phase to ensure the integrity of the fieldwork and methodology. In addition to supervision through assigned supervisors, every enumerator records his/her path using a tracking software (Oruxmaps) installed on to all the CAPI tablets. Enumerators submit captured paths to a centralized server at the end of enumeration of every square. This tracking path is checked to ensure that enumerators have fully covered the square assigned to them. This quality check was done daily, and for cases where the tracking path indicated below acceptable level of effort in listing informal business, the enumerator was asked to re-survey the square.
Questionnaires
Questionnaires
The survey data was collected using a standardized questionnaire, i.e., the long-form questionnaire. The questionnaire was developed building on previous modules used by the Enterprise Analysis Unit of the World Bank to survey informal businesses.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Enterprise Analysis Unit | World Bank Group | enterprisesurveys@worldbank.org |
Confidentiality
Confidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.
Citation requirements
The use of this dataset must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online).
Example:
The World Bank. Lao PDR - Informal Sector Business Survey 2019, Ref. LAO_2019_ISBS_v01_M. Dataset downloaded from https://www.enterprisesurveys.org/portal/login.aspx on [date].
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online).
Example:
The World Bank. Lao PDR - Informal Sector Business Survey 2019, Ref. LAO_2019_ISBS_v01_M. Dataset downloaded from https://www.enterprisesurveys.org/portal/login.aspx on [date].
Archive where study is originally stored
Enterprise Surveys
https://www.enterprisesurveys.org/Portal/
Cost: None
https://www.enterprisesurveys.org/Portal/
Cost: None
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_LAO_2019_ISBS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2019-12-31
DDI Document version
Version 01 (December 2019)