Abstract

As part of the efforts of the World Bank Group to understand the impact of COVID-19 on the private sector, the Enterprise Analysis unit is conducting follow-up surveys on recently completed Enterprise Surveys (ES) in several countries. These short surveys follow the baseline ES and are designed to provide quick information on the impact and adjustments that COVID-19 has brought about in the private sector.

The Zimbabwe Informal Businesses COVID-19 Impact Survey is different from the standard follow-up survey conducted by the unit in other countries, the major difference veing that this is not a follow-up survey.

Geographic coverage

National

Analysis unit

Enterprise

Universe

The universe of inference is all registered establishments with five or more employees that are engaged in one of the following activities defined using ISIC Rev. 3.1: manufacturing (groupd D), construction (group F), services sector (groups G and H), transport, storage, and communcations sector (group I) and information technology (division 72 of group K)

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the survey was selected using stratified random sampling, broadly following similar methodology explained in the ES Sampling Note. However, unlike ES that uses three levels of stratification (size, location, and sector), this survey uses two levels of stratification, namely location/region of the informal busines and the gender of the main business owner.

Stratifies random sampling was preferred over simple random sampling for several reasons: a. To obtain unbiased estimates for different subdivisions of the population with some known level of precision b. To obtain unbiased estimates for the whole population. The whole population, or universe of the study, is informal sector businesses operating in Zimbabwe. Informality is defined as any business that doesn't have registration from Zimbabwe Registrar of Companies. c. To make sure that the final total sample includes establishments from different regions and from businesses owned by male and femal. d. To exploit the benefits of stratifies sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e. lower standard errors, other things being equal.) e. Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous. f. The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.

Total sample target: 1020

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire contains the following modules: - Control information and introduction - General information - Sales and operations - Production - Labor force - Finance - Policies and prospects - Registration - Information on permanently closed establishments - Interview protocol

Response rate

98.4%

Explore gender statistics data focusing on academic staff, employment, fertility rates, GDP, poverty, and more in the GCC region. Access comprehensive information on key indicators for Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.

academic staff, Access to anti-retroviral drugs, Adjusted net enrollment rate, Administration and Law programmes, Age at first marriage, Age dependency ratio, Cause of death, Children out of school, Completeness of birth registration, consumer prices, Cost of business start-up procedures, Employers, Employment in agriculture, Employment in industry, Employment in services, employment or training, Engineering and Mathematics programmes, Female headed households, Female migrants, Fertility planning status: mistimed pregnancy, Fertility planning status: planned pregnancy, Fertility rate, Firms with female participation in ownership, Fisheries and Veterinary programmes, Forestry, GDP, GDP growth, GDP per capita, gender parity index, Gini index, GNI, GNI per capita, Government expenditure on education, Government expenditure per student, Gross graduation ratio, Households with water on the premises, Inflation, Informal employment, Labor force, Labor force with advanced education, Labor force with basic education, Labor force with intermediate education, Learning poverty, Length of paid maternity leave, Life expectancy at birth, Mandatory retirement age, Manufacturing and Construction programmes, Mathematics and Statistics programmes, Number of under-five deaths, Part time employment, Population, Poverty headcount ratio at national poverty lines, PPP, Primary completion rate, Retirement age with full benefits, Retirement age with partial benefits, Rural population, Sex ratio at birth, Unemployment, Unemployment with advanced education, Urban population

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

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Vietnam VN: Informal Employment: Female: % of Total Non-Agricultural Employment data was reported at 52.480 % in 2016. This records a decrease from the previous number of 53.430 % for 2015. Vietnam VN: Informal Employment: Female: % of Total Non-Agricultural Employment data is updated yearly, averaging 61.810 % from Dec 2007 (Median) to 2016, with 8 observations. The data reached an all-time high of 96.650 % in 2011 and a record low of 52.480 % in 2016. Vietnam VN: Informal Employment: Female: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

Abstract

This research is a survey of unregistered businesses conducted in Côte d'Ivoire between October 2008 and February 2009, simultaneously with Côte d'Ivoire 2009 Enterprise Survey. 129 informal establishments were interviewed.

The objective of World Bank firm-level surveys is to obtain feedback from enterprises in client countries on the state of the private sector, assess the constraints to private sector growth and create statistically significant business environment indicators that are comparable across countries.

Informal survey questionnaires are a shorter, tailored to unregistered businesses, version of Enterprise Survey questionnaires. The topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. Business owners or managers are interviewed face-to-face.

Geographic coverage

National

Analysis unit

The primary sampling unit of Informal Surveys is an unregistered establishment. In Côte d'Ivoire, registration with the Chambre du Commerce et de l'Industrie for firms with more than ten employees or with the Chambre des Metiers et de l'Artisanat for firms with less than ten employees differentiated formal and informal businesses.

Universe

The whole population, or the universe, covered in the survey is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the informal sector, there were no sample lists of firms. The sampling procedure was to survey an unregistered establishment in a certain geographic region and sector, similar to a registered business with one to four employees, interviewed for the Enterprise Survey that was conducted in conjunction with the Informal Survey.

Because a formal sample frame was not used, it is not possible to calculate response rates, universe estimates, or sampling weights for the informal sector sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Abstract

A specialized survey was designed to collect data needed for the Dimensions of Informality in Bangladesh report. The survey was conducted between March and May 2010 by Data International Ltd., and covered 1724 enterprises. The sample frame for these enterprises was the EGI Census of 55,817 firms in the randomly selected areas in urban parts of the 19 old districts. The sample was stratified by firm size (in terms of full-time employment) and broad industry (manufacturing, trade or services), and was chosen to be representative of firms with 3 to 99 full-time workers in these areas. Oversampling of firms with 10-99 full-time workers was done to ensure sufficient sample sizes of these firms, which are less prevalent than firms with fewer workers. In practice 20 percent of the final sample were actually of size 1 or 2 workers, and 2 percent had more than 100 workers – this likely reflects changes in firm size from the time of listing to the time of surveying, as well as seasonality in employment.

Geographic coverage

The sample frame for the selection of business concentrations in the ‘old’ 19 district headquarters is a subset of the list of all mahallas/paras within and adjacent to the urban areas of that district headquarter. These lists of all mahallas/paras were collected from the BBS Population Census 2001 database and updated using secondary information.

Analysis unit

Firm

Kind of data

Sample survey data [ssd]

Sampling procedure

Detailed sampling procedure document attached: The sample frame for these enterprises was the EGI Census of 55,817 firms in the randomly selected areas in urban parts of the 19 old districts. The sample was stratified by firm size (in terms of full-time employment) and broad industry (manufacturing, trade or services), and was chosen to be representative of firms with 3 to 99 full-time workers in these areas. Oversampling of firms with 10-99 full-time workers was done to ensure sufficient sample sizes of these firms, which are less prevalent than firms with fewer workers. In practice 20 percent of the final sample were actually of size 1 or 2 workers, and 2 percent had more than 100 workers – this likely reflects changes in firm size from the time of listing to the time of surveying, as well as seasonality in employment.

Mode of data collection

Face-to-face [f2f]

Research instrument

An English version of the questionnaire is provided as an external resource.

Response rate

Refusal rate was 20%

State of Palestine (West Bank and Gaza) PS: Informal Employment: % of Total Non-Agricultural Employment data was reported at 51.960 % in 2017. This records an increase from the previous number of 51.290 % for 2016. State of Palestine (West Bank and Gaza) PS: Informal Employment: % of Total Non-Agricultural Employment data is updated yearly, averaging 51.455 % from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 52.490 % in 2015 and a record low of 50.420 % in 2011. State of Palestine (West Bank and Gaza) PS: Informal Employment: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2018.; ; Harmonized series

Peru PE: Informal Employment: Male: % of Total Non-Agricultural Employment data was reported at 52.060 % in 2016. This records a decrease from the previous number of 53.980 % for 2015. Peru PE: Informal Employment: Male: % of Total Non-Agricultural Employment data is updated yearly, averaging 62.390 % from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 83.770 % in 2004 and a record low of 52.060 % in 2016. Peru PE: Informal Employment: Male: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

Abstract

This research is a survey of unregistered businesses conducted in Peru from June 10 to July 20, 2010. Data from 480 enterprises were analyzed.

Questionnaire topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. The mode of data collection is face-to-face interviews.

The Informal Surveys aim to accomplish the following objectives: 1) To provide information about the state of the private sector for informal businesses in client countries; 2) To generate information about the reasons of said informality; 3) To collect useful data for the research agenda on informality; 4) To provide information on the level of activity in the informal sector of selected urban centers in each country.

Geographic coverage

National

Analysis unit

The primary sampling unit of the Informal Surveys is an unregistered establishment. For Peru, informal firms were defined as those not registered with the Superintendencia Nacional de Administración Tributaria (SUNAT).

Universe

The whole population, or the universe, covered in the survey is the non-agricultural informal economy.

At the beginning of each survey, a screening procedure is conducted in order to identify eligible interviewees. At this point, a full description of all the activities of the business owner or manager is taken; based on its principal activity, a business is then classified in the manufacturing or services stratum using a list of activities developed from previous iterations of the survey. Certain activities are excluded such as strictly illegal activities (e.g., prostitution or drug trafficking) as well as individual activities that are forms of selling labor like domestic servants or windshield washers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Informal Surveys are conducted in selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined.

In Peru, the urban centers identified were Lima and Arequipa. The target sample for both urban centers was 240 interviews.

Sampling in the Informal Surveys is conducted within clearly delineated sampling zones, which are geographically determined divisions within each urban center. Sampling zones are defined at the beginning of fieldwork, and are delineated according to the concentration and geographical dispersion of informal business activity.

The number of sampling areas, and the geographical area they contain, is determined with the goal that each sector will yield four effective interviews.

In Peru, each sampling area was designed to contain a physical area, on average, of no less than the equivalent of eight city blocks. These sampling areas may or may not correspond to the administrative districts of the urban center.

In both Lima and Arequipa, for a total of 240 interviews in each city, 60 sampling areas were identified (240/4 = 60 sampling areas), respectively.

In order to provide information on diverse aspects of the informal economy, the sample is designed to have equal proportions of services and manufacturing (50:50). These sectors are defined by responses provided by each informal business to a question on the business's main activity included in the screener portion of the questionnaire.

As a general rule, services must constitute an ongoing business enterprise and so exclude the sale of manual labor Manufacturing activity in the informal sector includes business activity requiring inputs and/or intermediate goods. Thus, for example, the processing of coffee, sugar, oil, dried fruit, or other processed foods is considered manufacturing, while the simple selling of these goods falls under services. If an informal business conducts a mixture of these activities, the business is considered under the manufacturing stratum.

Each sampling zone was designed with the goal of obtaining two interviews in services and two interviews in manufacturing. In order to ensure a degree of geographical dispersion within each sampling zone, two starting points were identified.

Each starting point was designed to correspond to five city blocks, which were numbered sequentially. The first starting point was identified as Starting Point A and the second as Starting Point B.

Proceeding from each starting point, interviewers were instructed to begin on block 1, defining the starting block and corner. Each interviewer was instructed to attempt to achieve two interviews from each starting point, ideally one interview in manufacturing and one in services.

Interviewers were instructed to proceed clockwise around block 1 from Starting Point A; if the target interviews were not achieved, interviewers proceeded to block 2, Starting Point A, and so forth until completing a circuit of block 5. After achieving two interviews from Starting Point A, interviewers were instructed to cease work in the blocks assigned to that given Starting Point and repeat the sameprocedure from Starting Point B, beginning with block 1.

Using local knowledge, within each block all houses and shops were checked for unregistered businesses, following the pre-fixed route described above, until the allotted quota of interviews for each starting point was reached. Often interviewers used referrals by neighbors and locals in order to identify informal businesses. When a referral was obtained, the pre-determined route was followed until reaching the address of the referral. It should be noted that when referrals were obtained, interviewers were instructed to maintain the sampling procedure noted above; i.e., in the case that an interviewer encountered an informal business in the process of following a referral, an attempt was made to interview the former business first.

Each sampling zone, including its two starting points, were marked using Google maps, with the GPS coordinates of the starting points being systematically recorded.

Additionally, when obtaining a complete interview, the exact address of the informal business (or where the interview took place) was registered by the interviewer. Once in the office, this address was searched in Google maps, and its GPS coordinates were registered in a fieldwork report.

If no address was immediately available, using local knowledge, the GPS coordinates were determined using imaging via Google maps. In order to preserve confidentiality, the exact coordinates of businesses are not published.

Due to issues of non-response, in the process of fieldwork, the implementing contractor was unable to obtain the targeted four interviews in each of the originally delineated sampling areas.

As a result, replacement sampling areas were delineated, ex post. In sum, there were 70 sampling areas (60 original, 10 replacement) in Arequipa and 72 zones in Lima (60 original, 12 replacement).

Complete information regarding the sampling methodology as well as maps of starting points can be found in "Description of Peru Informal Survey Implementation" and "Mapping of starting points for sampling in Peru Informal Survey 2010" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

The overall survey response rate among contacted, eligible businesses for the Peru Informal Survey 2010 was estimated at 25%.

Abstract

This research is a survey of unregistered businesses conducted in Burkina Faso between May and October 2009, simultaneously with Burkina Faso 2009 Enterprise Survey. 120 informal businesses were interviewed.

The objective of World Bank firm-level surveys is to obtain feedback from enterprises in client countries on the state of the private sector, assess the constraints to private sector growth and create statistically significant business environment indicators that are comparable across countries.

Informal survey questionnaires are a shorter, tailored to unregistered businesses, version of Enterprise Survey questionnaires. The topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. Business owners or managers are interviewed face-to-face.

Geographic coverage

National

Analysis unit

The primary sampling unit of Informal Surveys is an unregistered establishment. In Burkina Faso, registration with the Chambre de Commerce, d’Industrie et d’Artisanat du Burkina Faso differentiated formal and informal businesses.

Universe

The whole population, or the universe, covered in the survey is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the informal sector, there were no sample lists of firms. The sampling procedure was to survey an unregistered establishment in a certain geographic region and sector, similar to a registered business with one to four employees, interviewed for the Enterprise Survey that was conducted in conjunction with the Informal Survey.

Because a formal sample frame was not used, it is not possible to calculate response rates, universe estimates, or sampling weights for the informal sector sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available:

• Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Abstract

This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.

The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.

The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.

Geographic coverage

National coverage.

There are six statistical regions known as Division's in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'pai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks. The sample for the 2018 Labour Force Survey (LFS) was designed to cover at least 2500 employed population aged 10 years and over from all the regions. This was made mainly to have sufficient cases to provide information on the employed population.

Analysis unit

• Households (for food insecurity module questionnaire)
• Individuals.

Universe

Population living in private households in Tonga. The labour force questionnaire is directed to the population aged 10 and above. Disability short set of questions is directed to all individuals age 2 and above and the food insecurity experience scale is directed to the head of household.

Kind of data

Sample survey data [ssd]

Sampling procedure

2018 Tonga Labour force survey aimed at estimating all the main ILO indicators at the island group level (geographical stratas). The sampling strategy is based on a two stages stratified random survey.

1. Computation of the survey parameters: Total sample size per strata, number of households to interview in each Primary Sampling Unit (PSU = census block) and number of PSUs to select The stratification of the survey is the geographical breakdown by island group (6 stratas Tongatapu urban, Tongatapu rural, Vava'u, Ha'apai, 'Eua, Niuas)
2. The selection strategy is a 2 stages random survey where: Random selection of census blocks within each
3. Census blocks are randomly selected in first place, using probability proportional to size

4. 15 households per block are randomly selected using uniform probability

5. The sampling frame used to select PSUs (census blocks) and household is the 2016 Tonga population census.

The computation of sample size required the use of: - Tonga 2015 HIES dataset (labour force section) - Tonga 2016 population census (distribution of households across the stratas) The resource variable used to compute the sample size is the labour force participation rate from the 2015 HIES. The use of the 2015 labour force section of the Tonga HIES allows the computation of the design effect of the labour force participation rate within each strata. The design effect and sampling errors of the labour force participation rate estimated from the 2015 HIES in combination with the 2016 household population distribution allow to predict the minimum sample size required (per strata) to get a robust estimate from the 2018 LFS.

Total sample size: 2685 households Geographical stratification: 6 island groups Selection process: 2 stages random survey where census blocks are selected using Probability Proportional to Size (Primary Sampling Unit) in the first place and households are randomly selected within each selected blocks (15 households per block) Non response: a 10% increase of the sample happened in all stratas to account for non-response Sampling frame: the household listing from the 2016 population census was used as a sampling frame and the 2015 labour force section of the HIES was used to compute the sample size (using labour force participation rate.

Sampling deviation

No major deviation from the original sample has taken place.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2018 Tonga Labour Force Survey questionnaire included 15 sections:

IDENTIFICATION SECTION B: INDIVIDUAL CHARACTERISTICS SECTION C: EDUCATION (AGE 3+) SECTIONS B & C: EMPLOYMENT IDENTIFICATION AND TEMPORARY ABSENCE (AGE 10+) SECTION D: AGRICULTURE WORK AND MARKET DESTINATION SECTION E1: MAIN EMPLOYMENT CHARACTERISTICS SECTION E2: SECOND PAID JOB/ BUSINESS ACTIVITY CHARACTERISTICS SECTION F: INCOME FROM EMPLOYMENT SECTION G: WORKING TIME SECTION H: JOB SEARCH SECTION I: PREVIOUS WORK EXPERIENCE SECTION J: MAIN ACTIVITY SECTION K: OWN USE PRODUCTION WORK FOOD INSECURITY EXPERIENCES GPS + PHOTO

The questionniares were developed and administered in English and were translated into Tongan language. The questionnaire is provided as external resources.

The draft questionnaire was pre-tested during the supervisors training and during the enumerators training and it was finally tested during the pilot test. The pilot testing was undertaken on the 27th of May to the 1st of June 2018 in Tongatapu Urban and Rural areas. The questionnaire was revised rigorously in accordance to the feedback received from each test. At the same time, a field operations manual for supervisors and enumerators was prepared and modified accordingly for field operators to use as a reference during the field work.

Cleaning operations

The World Bank Survey Solutions software was used for Data Processing, STATA software was used for data cleaning, tabulation tabulation and analysis.

Editing and tabulation of the data will be undertaken in February/March 2019 in collaboration with SPC and ILO.

Response rate

A total, 2,685 households were selected for the sample. Of these existing households, 2,584 were successfully interviewed, giving a household response rate of 96.2%.

Response rates were higher in urban areas than in the rural area of Tongatapu.

-1 Tongatapu urban: 97.30%
-2 Tongatapu rural: 93.00%
-3 Vava'u: 100.00% -4 Ha'pai: 100.00% -5 Eua: 95.20% -6 Niuas: 80.00% -Total: 96.20%.

Sampling error estimates

Sampling errors were computed and are presented in the final report.

The sampling error were computed using the survey set package in Stata. The Finite Population Correction was included in the sample design (optional in svy set Stata command) as follow: - Fpc 1: total number of census blocks within the strata (variable toteas) - Fpc 2: Here is a list of some LF indicators presented with sampling error

-RSE: Labour force population: 2.2% Employment - population in employment: 2.2% Labour force participation rate (%): 1.7% Unemployment rate (%): 13.5% Composite rate of labour underutilization (%): 7.3% Youth unemployment rate (%): 18.2% Informal employment rate (%): 2.7% Average monthly wages - employees (TOP): 12%.

-95% Interval: Labour force population: 28,203 => 30,804 Employment - population in employment: 27,341 => 29,855 Labour force participation rate (%): 45.2% => 48.2% Unemployment rate (%): 2.2% => 3.9% Composite rate of labour underutilization (%): 16% => 21.4% Youth unemployment rate (%): 5.7% => 12.1% Informal employment rate (%): 44.3% => 49.4% Average monthly wages - employees (TOP): 1,174 => 1,904.

Ivory Coast CI: Informal Employment: % of Total Non-Agricultural Employment data was reported at 87.700 % in 2016. This records a decrease from the previous number of 96.210 % for 2013. Ivory Coast CI: Informal Employment: % of Total Non-Agricultural Employment data is updated yearly, averaging 92.150 % from Dec 2012 (Median) to 2016, with 3 observations. The data reached an all-time high of 96.210 % in 2013 and a record low of 87.700 % in 2016. Ivory Coast CI: Informal Employment: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

Sudan SD: Informal Employment: % of Total Non-Agricultural Employment: Female data was reported at 60.190 % in 2011. Sudan SD: Informal Employment: % of Total Non-Agricultural Employment: Female data is updated yearly, averaging 60.190 % from Dec 2011 (Median) to 2011, with 1 observations. Sudan SD: Informal Employment: % of Total Non-Agricultural Employment: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sudan – Table SD.World Bank.WDI: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in April 2019.; ; Harmonized series

Abstract

At the onset of the 2008-2009 global economic crisis, the Open Society Institute-Sofia and the World Bank partnered to implement Crisis Monitoring Survey (CMS). The CMS is a multi-topic household survey that followed three nationally representative cross-sections of about 2,400 households, including a panel of about 1,700 Bulgarian households, during February 2010, October 2010 and February 2011. The survey included a detailed income module, but no consumption module. It tracked the incidence of income shocks, the coping strategies used by affected households to mitigate the income losses, and the impact of public polices - social protection in particular - in alleviating the effects of the crisis. In particular, the survey investigated in some depth how households used the labor market to mitigate the impact of the crisis, whether formal social protection programs protected households against sliding into poverty, and the effectiveness of informal safety nets.

Given the special need to study the more vulnerable ethnic minority Roma population, an independent "booster sample" of about 300 households was selected in settlements and neighborhoods identified as predominantly Roma.

The first round of Crisis Monitoring Survey was conducted in February 2010. The data from this round is documented here.

Geographic coverage

National

Analysis unit

• households,
• individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Two samples were used in Crisis Monitoring Survey: main sample and booster sample.

The main sample was created in two stages.

First, the population was stratified by district (NUTS 3) and type of settlement. In Bulgaria, there are 28 administrative districts. For the type of settlement three categories were defined - rural, urban (with population under 50,000) and metropolitan (with population over 50,000). Bulgaria's capital, Sofia, is include in the metropolitan category. In this way 28 x 3=84 categories (strata) were defined and proportional allocation was made. The method of selecting settlements from each stratum is simple random sampling with replacement, weighted by the number of households in the settlement.

In the second stage, voting stations were chosen in each settlement. Voting stations were used as a type of cluster. Voting stations were selected with probability proportional to the number of voters in each station. In each cluster, (voting station), 20 household addresses were randomly selected from the list of all addresses in the station. The first 10 addresses, which had to be visited mandatorily, formed the main list. If there was a refusal in a household of the main list, this household had to be replaced with an address from the list of reserves (the last 10 addresses).

For the Roma booster sample, an expert database was used. It contained basic information for all segregated neighborhoods in the country like locality (district, municipality and settlement), an experts' approximation for the number of population, number of households, number of houses and other characteristics. The planned booster size sample was 300 households. Simple random sampling without replacement was used in segregated neighborhoods, weighted by their population. In this way, 30 segregated neighborhoods in 20 districts were selected. In each district, 10 randomly sampled households had to be interviewed. GPS sampling was used to identify households in each cluster.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey collected information about household demographics (roster), labor market participation and earnings, housing, durables, access to and receipts of social protection programs, informal safety nets and remittances, other income, credit, self-reported impact of the crisis, coping and mitigation mechanisms.

The Bulgaria Crisis Monitoring Survey combines modules that have been used in crisis surveys in a number of countries (including crisis-specific labor, credit, and coping strategies modules) with uniquely detailed modules on income and social assistance.

Response rate

The planned size of the main sample in the first round was 2,400 households, 2,384 households were interviewed. The planned size of the Roma booster sample was 300 households, 296 households were interviewed.

For each cluster, there was a list of 10 addresses that had to be visited by the interviewer and an additional 10 addresses in reserve. If any of the first 10 addresses did not exist, dwellings were locked for a long time or the people refused to be interviewed, the additional ones were used. According to instructions, the interviewer had to visit each address in the main list three times, unless the building (or apartment) was obviously uninhabited. The interviewer had to write down what happened at each visit to each address on the list. At addresses where the interview did not take place, the interviewer noted the reason. Once an interview was done, the questionnaire got an ID that showed whether the address was on the original list or not.

Abstract

This research is a survey of unregistered businesses conducted in Mali between May and November 2010, at the same time with Mali 2010 Enterprise Survey. Data from 120 enterprises were analyzed.

Questionnaire topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. The mode of data collection is face-to-face interviews.

The Informal Surveys aim to accomplish the following objectives: 1) To provide information about the state of the private sector for informal businesses in client countries; 2) To generate information about the reasons of said informality; 3) To collect useful data for the research agenda on informality; 4) To provide information on the level of activity in the informal sector of selected urban centers in each country.

Geographic coverage

National

Analysis unit

The primary sampling unit of the Informal Surveys is an unregistered establishment. For Mali, informal firms were defined as those not registered as determined by a list of firms supplied by the World Bank.

Universe

The whole population, or the universe, covered in the survey is the non-agricultural informal economy.

At the beginning of each survey, a screening procedure is conducted in order to identify eligible interviewees. At this point, a full description of all the activities of the business owner or manager is taken; based on its principal activity, a business is then classified in the manufacturing or services stratum using a list of activities developed from previous iterations of the survey. Certain activities are excluded such as strictly illegal activities (e.g., prostitution or drug trafficking) as well as individual activities that are forms of selling labor like domestic servants or windshield washers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Informal Surveys are conducted in selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined.

In Mali, Bamako, Mopti, Segou, and Sikasso were identified as urban centers of interest. The sample was confined to the major cities covered and the survey was run in parallel with the enterprise surveys of the formal economy. The target number of interviews will reflect, as far as practical, the individuals' population distribution but with no more than 60% sample from a single city and no city with fewer than 20 interviews in total.

Sampling in the Informal Surveys is conducted within clearly delineated sampling zones, which are geographically determined divisions within each urban center. Sampling zones are defined at the beginning of fieldwork, and are delineated according to the concentration and geographical dispersion of informal business activity. After the sampling sizes are defined for each location every city is divided into several zones that may or may not correspond to the administrative districts.

In Mali, using Google maps or local city maps, the target areas within each city were identified. With input from the local agency applying local knowledge, the starting points were defined. The number of zones was determined by the target sample size for each city divided by the cluster size (4 interviews).

In Bamako, 60 interviews were completed in 15 sampling zones. In Mopti, Segou, and Sikasso, 20 interviews were completed in 5 sample zones in each city.

In order to provide information on diverse aspects of the informal economy, the sample is designed to have equal proportions of services and manufacturing (50:50). These sectors are defined by responses provided by each informal business to a question on the business's main activity included in the screener portion of the questionnaire.

As a general rule, services must constitute an ongoing business enterprise and so exclude the sale of manual labor. Manufacturing activity in the informal sector includes business activity requiring inputs and/or intermediate goods. Thus, for example, the processing of coffee, sugar, oil, dried fruit, or other processed foods is considered manufacturing, while the simple selling of these goods falls under services. If an informal business conducts a mixture of these activities, the business is considered under the manufacturing stratum.

Each sampling zone was designed with the goal of obtaining two interviews in services and two interviews in manufacturing. In order to ensure a degree of geographical dispersion within each sampling zone, two starting points were identified.

Each sampling zone, including its two starting points, were marked using Google maps, with the GPS coordinates of the starting points being systematically recorded.

Additionally, when obtaining a complete interview, the exact address of the informal business (or where the interview took place) was registered by the interviewer. Once in the office, this address was searched in Google maps, and its GPS coordinates were registered in a fieldwork report.

If no address was immediately available, using local knowledge, the GPS coordinates were determined using imaging via Google maps. In order to preserve confidentiality, the exact coordinates of businesses are not published.

Due to issues of non-response, in the process of fieldwork, the implementing contractor was unable to obtain the targeted four interviews in each of the originally delineated sectors.

As a result, replacement sectors were delineated, ex post. Additionally, the implementing contractor noted that in various interviews there were notable shortfalls in response rates to certain questions. For these reasons, additional interviews were authorized. These were distributed according to the discretion of the implementing contractor in Mali, with authorization from the World Bank.

In sum, there were 30 zones in Mali; 15 zones in Bamako, 5 zones each in Mopti, Segou, and Sikasso.

Complete information regarding the sampling methodology can be found in "Description of Mali Informal Survey Implementation" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Timor-Leste TL: Informal Employment: Female: % of Total Non-Agricultural Employment data was reported at 57.170 % in 2013. This records a decrease from the previous number of 69.820 % for 2010. Timor-Leste TL: Informal Employment: Female: % of Total Non-Agricultural Employment data is updated yearly, averaging 63.495 % from Dec 2010 (Median) to 2013, with 2 observations. The data reached an all-time high of 69.820 % in 2010 and a record low of 57.170 % in 2013. Timor-Leste TL: Informal Employment: Female: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Timor-Leste – Table TL.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

Employment in agriculture, female (% of female employment) (modeled ILO estimate) in Mozambique was reported at 79.17 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mozambique - Employees, agriculture, female (% of female employment) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

Abstract

This research is a survey of unregistered businesses conducted in Cape Verde between June and November 2009, simultaneously with Cape Verde 2009 Enterprise Survey. 129 informal businesses were interviewed.

The objective of World Bank firm-level surveys is to obtain feedback from enterprises in client countries on the state of the private sector, assess the constraints to private sector growth and create statistically significant business environment indicators that are comparable across countries.

Informal survey questionnaires are a shorter, tailored to unregistered businesses, version of Enterprise Survey questionnaires. The topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. Business owners or managers are interviewed face-to-face.

Geographic coverage

National

Analysis unit

The primary sampling unit of Informal Surveys is an unregistered establishment. In Cape Verde, registration with the Registry of Commerce or posession of a Municipal License differentiated formal and informal businesses.

Universe

The whole population, or the universe, covered in the survey is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the informal sector, there were no sample lists of firms. The sampling procedure was to survey an unregistered establishment in a certain geographic region and sector, similar to a registered business with one to four employees, interviewed for the Enterprise Survey that was conducted in conjunction with the Informal Survey.

Because a formal sample frame was not used, it is not possible to calculate response rates, universe estimates, or sampling weights for the informal sector sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available:

• Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Benin BJ: Informal Employment: % of Total Non-Agricultural Employment data was reported at 94.540 % in 2011. Benin BJ: Informal Employment: % of Total Non-Agricultural Employment data is updated yearly, averaging 94.540 % from Dec 2011 (Median) to 2011, with 1 observations. The data reached an all-time high of 94.540 % in 2011 and a record low of 94.540 % in 2011. Benin BJ: Informal Employment: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Benin – Table BJ.World Bank.WDI: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 20, 2020.; ; Harmonized series

Abstract

This research is a survey of unregistered businesses conducted in Argentina from June 11, 2010, to Aug. 13, 2010. Data from 384 enterprises were analyzed.

Questionnaire topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. The mode of data collection is face-to-face interviews.

The Informal Surveys aim to accomplish the following objectives: 1) To provide information about the state of the private sector for informal businesses in client countries; 2) To generate information about the reasons of said informality; 3) To collect useful data for the research agenda on informality; 4) To provide information on the level of activity in the informal sector of selected urban centers in each country.

Geographic coverage

National

Analysis unit

The primary sampling unit of the Informal Surveys is an unregistered establishment. For Argentina, informal firms were defined as those not registered with the Administración Federal de Ingresos Públicos (AFIP).

Universe

The whole population, or the universe, covered in the survey is the non-agricultural informal economy.

At the beginning of each survey, a screening procedure is conducted in order to identify eligible interviewees. At this point, a full description of all the activities of the business owner or manager is taken; based on its principal activity, a business is then classified in the manufacturing or services stratum using a list of activities developed from previous iterations of the survey. Certain activities are excluded such as strictly illegal activities (e.g., prostitution or drug trafficking) as well as individual activities that are forms of selling labor like domestic servants or windshield washers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Informal Surveys are conducted in selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined.

In Argentina, the urban centers identified were Buenos Aires and Resistencia in the province of Chaco. At the outset, the target sample for Buenos Aires was 240 interviews; the sample target for Chaco was 80 interviews.

Sampling in the Informal Surveys is conducted within clearly delineated sampling zones, which are geographically determined divisions within each urban center. Sampling zones are defined at the beginning of fieldwork, and are delineated according to the concentration and geographical dispersion of informal business activity.

The number of sampling areas, and the geographical area they contain, is determined with the goal that each sector will yield four effective interviews.

In Argentina, each sampling area was designed to contain a physical area, on average, of no less than the equivalent of ten city blocks. These sampling areas may or may not correspond to the administrative districts of the urban center.

In Buenos Aires, for a total of 240 interviews, 60 sampling areas were initially identified (240/4 = 60 sampling areas). In Chaco, a total of 80 interviews yielded 20 sampling areas (80/4 = 20 sampling areas).

In order to provide information on diverse aspects of the informal economy, the sample is designed to have equal proportions of services and manufacturing (50:50). These sectors are defined by responses provided by each informal business to a question on the business's main activity included in the screener portion of the questionnaire.

As a general rule, services must constitute an ongoing business enterprise and so exclude the sale of manual labor Manufacturing activity in the informal sector includes business activity requiring inputs and/or intermediate goods. Thus, for example, the processing of coffee, sugar, oil, dried fruit, or other processed foods is considered manufacturing, while the simple selling of these goods falls under services. If an informal business conducts a mixture of these activities, the business is considered under the manufacturing stratum.

Each sampling zone was designed with the goal of obtaining two interviews in services and two interviews in manufacturing. In order to ensure a degree of geographical dispersion within each sampling zone, two starting points were identified.

Each starting point was designed to correspond to five city blocks, which were numbered sequentially. The first starting point was identified as Starting Point A and the second as Starting Point B.

Proceeding from each starting point, interviewers were instructed to begin on block 1, defining the starting block and corner. Each interviewer was instructed to attempt to achieve two interviews from each starting point, ideally one interview in manufacturing and one in services.

Interviewers were instructed to proceed clockwise around block 1 from Starting Point A; if the target interviews were not achieved, interviewers proceeded to block 2, Starting Point A, and so forth until completing a circuit of block 5. After achieving two interviews from Starting Point A, interviewers were instructed to cease work in the blocks assigned to that given Starting Point and repeat the sameprocedure from Starting Point B, beginning with block 1.

Using local knowledge, within each block all houses and shops were checked for unregistered businesses, following the pre-fixed route described above, until the allotted quota of interviews for each starting point was reached. Often interviewers used referrals by neighbors and locals in order to identify informal businesses. When a referral was obtained, the pre-determined route was followed until reaching the address of the referral. It should be noted that when referrals were obtained, interviewers were instructed to maintain the sampling procedure noted above; i.e., in the case that an interviewer encountered an informal business in the process of following a referral, an attempt was made to interview the former business first.

Each sampling zone, including its two starting points, were marked using Google maps, with the GPS coordinates of the starting points being systematically recorded.

Additionally, when obtaining a complete interview, the exact address of the informal business (or where the interview took place) was registered by the interviewer. Once in the office, this address was searched in Google maps, and its GPS coordinates were registered in a fieldwork report.

If no address was immediately available, using local knowledge, the GPS coordinates were determined using imaging via Google maps. In order to preserve confidentiality, the exact coordinates of businesses are not published.

Due to issues of non-response, in the process of fieldwork, the implementing contractor was unable to obtain the targeted four interviews in each of the originally delineated sectors.

As a result, replacement sectors were delineated, ex post. Additionally, the implementing contractor noted that in various interviews there were notable shortfalls in response rates to certain questions. For these reasons, additional interviews were authorized. These were distributed according to the discretion of the implementing contractor in Argentina, with authorization from the World Bank.

Continuing with the sample target of four interviews per sector, as a result of the replacement procedure, more than the original target of interviews per urban center were realized, 100 in Chaco (target 80) and 284 in Buenos Aires (target 240).

In sum, there were 64 zones (60 original, 4 replacement) in Buenos Aires and 27 zones in Chaco (20 original, 7 replacement).

Complete information regarding the sampling methodology as well as maps of starting points can be found in "Description of Argentina Informal Survey Implementation" and "Mapping of starting points for sampling in Argentina Informal Survey 2010" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

The overall survey response rate among contacted, eligible businesses for the Argentina Informal Survey 2010 was estimated at 20%.

Abstract

This research is a survey of unregistered businesses conducted in Angola between June and November 2010, at the same time with Angola 2010 Enterprise Survey. Data from 119 enterprises were analyzed.

Questionnaire topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. The mode of data collection is face-to-face interviews.

The Informal Surveys aim to accomplish the following objectives: 1) To provide information about the state of the private sector for informal businesses in client countries; 2) To generate information about the reasons of said informality; 3) To collect useful data for the research agenda on informality; 4) To provide information on the level of activity in the informal sector of selected urban centers in each country.

Geographic coverage

National

Analysis unit

The primary sampling unit of the Informal Surveys is an unregistered establishment. For Angola, informal firms were defined as those not registered as determined by a registry supplied by Dun & Bradstreet.

Universe

The whole population, or the universe, covered in the survey is the non-agricultural informal economy.

At the beginning of each survey, a screening procedure is conducted in order to identify eligible interviewees. At this point, a full description of all the activities of the business owner or manager is taken; based on its principal activity, a business is then classified in the manufacturing or services stratum using a list of activities developed from previous iterations of the survey. Certain activities are excluded such as strictly illegal activities (e.g., prostitution or drug trafficking) as well as individual activities that are forms of selling labor like domestic servants or windshield washers.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Informal Surveys are conducted in selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined.

In Angola, the urban centers identified were Luanda, Huambo and Benguela. At the outset, the target sample in Luanda was 60 interviews, in Huambo was 30 interviews, and in Benguela 30 interviews. The sample will be confined to the major cities covered in the running in parallel enterprise survey of the formal economy. The target number of interviews will reflect, as far as practical, the individuals' population distribution but with no more than 60% sample from a single city and no city with fewer than 20 interviews in total.

Sampling in the Informal Surveys is conducted within clearly delineated sampling zones, which are geographically determined divisions within each urban center. Sampling zones are defined at the beginning of fieldwork, and are delineated according to the concentration and geographical dispersion of informal business activity. After the sampling sizes are defined for each location every city is divided into several zones that may or may not correspond to the administrative districts.

In Angola, using Google maps or local city maps, the target areas within each city were identified. With input from the local agency applying local knowledge, the starting points were defined. The number of zones was determined by the target sample size for each city divided by the cluster size (4 interviews).

In Luanda, for a total of 60 interviews, 15 sampling zones were initially identified (60/4=15 zones). In Huambo, a total of 30 interviews were completed in 7 sampling zones. In Benguela, a total of 29 interviews were conducted in 8 sampling zones. As described above, the criteria used in choosing these sample sectors was a combination of territorial dispersion and the presence of informal businesses.

In order to provide information on diverse aspects of the informal economy, the sample is designed to have equal proportions of services and manufacturing (50:50). These sectors are defined by responses provided by each informal business to a question on the business's main activity included in the screener portion of the questionnaire.

As a general rule, services must constitute an ongoing business enterprise and so exclude the sale of manual labor Manufacturing activity in the informal sector includes business activity requiring inputs and/or intermediate goods. Thus, for example, the processing of coffee, sugar, oil, dried fruit, or other processed foods is considered manufacturing, while the simple selling of these goods falls under services. If an informal business conducts a mixture of these activities, the business is considered under the manufacturing stratum.

Each sampling zone was designed with the goal of obtaining two interviews in services and two interviews in manufacturing. In order to ensure a degree of geographical dispersion within each sampling zone, two starting points were identified.

Each sampling zone, including its two starting points, were marked using Google maps, with the GPS coordinates of the starting points being systematically recorded.

Additionally, when obtaining a complete interview, the exact address of the informal business (or where the interview took place) was registered by the interviewer. Once in the office, this address was searched in Google maps, and its GPS coordinates were registered in a fieldwork report.

If no address was immediately available, using local knowledge, the GPS coordinates were determined using imaging via Google maps. In order to preserve confidentiality, the exact coordinates of businesses are not published.

Due to issues of non-response, in the process of fieldwork, the implementing contractor was unable to obtain the targeted four interviews in each of the originally delineated sectors.

As a result, replacement sectors were delineated, ex post. Additionally, the implementing contractor noted that in various interviews there were notable shortfalls in response rates to certain questions. For these reasons, additional interviews were authorized. These were distributed according to the discretion of the implementing contractor in Angola, with authorization from the World Bank.

In sum, there were 30 zones in Angola; Luanda (15 zones), Huambo (7 zones), and Benguela (8 zones).

Complete information regarding the sampling methodology can be found in "Description of Angola Informal Survey Implementation" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Informal Questionnaire.

The survey topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.