Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely designed modules in the Employer Survey aim to assess the structure of the labor force; the skills (cognitive skills, behavior and personality traits, and job-relevant skills) currently being used; the skills that employers look for when hiring new workers; the propensity of firms to provide training (including satisfaction with education, training, and levels of specific skills) and the link between skills and compensation and promotion. The survey also captures background characteristics (size, legal form, industry, full time vs. non-standard employment and occupational breakdown), performance (revenues, wages and other costs, profits and scope of market), key labor market challenges and their ranking relative to other challenges, and job skill requirements of the firms being interviewed.

The questionnaire can be adapted to address a sample of firms in both informal and formal sectors, with varying sizes and industry classifications.

Geographic coverage

Capital Nairobi and other urban areas.

Analysis unit

The units of analysis are establishments or workplaces - a single location at which one or more employees work. The larger legal entity may include multiple establishments. The firms on the list will have been randomly chosen, with probability proportional to the number of employees in the firm.

Universe

The universe of the study are non-government businesses registered with the Kenya National Bureau of Statistics (KNBS), from 2016. Firms with at least five employees were selected from the following sectors: Manufacturing, Trade and Other Services.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling objective of the survey was to obtain interviews from 500 non-government enterprise workplaces in the capital and urban regions of Kenya. Firms with less than five employees were excluded from the target population.

Two-stage stratified random sampling was used in the survey. A list of businesses registered with the Kenya National Bureau of Statistics (KNBS) from 2016, served as the sampling frame.

Detailed information about sampling is available in the Kenya Employer Survey Design Planning Report and Kenya Employer Survey Weighting Procedure, provided as Related Material.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The Questionnaire for the STEP Employer Survey consists of five modules:

Section 1 - Work Force Section 2 - Skills Used Section 3 - Hiring Practices Section 4 - Training and Compensation Section 5 - Background

In the case of Kenya, the questionnaire was adapted to the Kenya context and published in English and Swahili. It has been provided as Related Material.

Cleaning operations

STEP Data Management Process:

1) Raw data is sent by the survey firm

2) The World Bank (WB) STEP team runs data checks on the Questionnaire data. Comments and questions are sent back to the survey firm.

3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data.

4) The WB STEP team again check to make sure the data files are clean. This might require additional iterations with the survey firm.

5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies.

Response rate

An overall response rate of 72% was achieved in Kenya STEP Survey. Detailed distribution of responses by stratum can be found in the document Kenya Employer Survey Weighting Procedure, available as Related Material.

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely designed modules in the Employer Survey aim to assess the structure of the labor force; the skills (cognitive skills, behavior and personality traits, and job-relevant skills) currently being used; the skills that employers look for when hiring new workers; the propensity of firms to provide training (including satisfaction with education, training, and levels of specific skills) and the link between skills and compensation and promotion. The survey also captures background characteristics (size, legal form, industry, full time vs. non-standard employment and occupational breakdown), performance (revenues, wages and other costs, profits and scope of market), key labor market challenges and their ranking relative to other challenges, and job skill requirements of the firms being interviewed.

The questionnaire can be adapted to address a sample of firms in both informal and formal sectors, with varying sizes and industry classifications.

Geographic coverage

Capital Yerevan and other urban areas

Analysis unit

The units of analysis are establishments and workplaces – a single location at which one or more employees work. The larger legal entity may include multiple establishments.

Universe

The universe of the study are non-government businesses registered with Armenia Social Security State Agency from 2012, with at least five employees in the following sectors: food processing, fishing, mining, manufacturing, electricity, gas and waterworks, construction, wholesale, retail trade, repair of motor vehicles, motorcycle and household goods, hotels and restaurants, transportation, financial services, real estate.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling objective of the survey was to obtain interviews from 400 non-government enterprise workplaces in the capital and urban regions of Armenia. Firms with less than five employees were excluded from the target population.

Two-stage stratified random sampling was used in the survey. A list of businesses registered with Armenia Social Security State Agency from 2012 served as the sampling frame.

Detailed information about sampling is available in Armenia Employer Survey Design Planning Report and Armenia Employer Survey Weighting Procedure, provided as external resources.

Mode of data collection

Face-to-face [f2f]

Research instrument

STEP Employer Survey Questionnaire has five sections: Section 1 - Work Force Section 2 - Skills Used Section 3 - Hiring Practices Section 4 -Training and Compensation Section 5 - Background

In Armenia, the questionnaire was adapted to the Armenian context and published in English and Armenian.

Cleaning operations

STEP Data Management Process:

1) Raw data is sent by the survey firm.

2) The World Bank (WB) STEP team runs data checks on the Questionnaire data. Comments and questions are sent back to the survey firm.

3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data.

4) The WB STEP team again check to make sure the data files are clean. This might require additional iterations with the survey firm.

5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies.

Response rate

An overall response rate of 36% was achieved in Armenia STEP Survey. Detailed distribution of responses by stratum can be found in Armenia Employer Survey Weighting Procedure (Table 4), available as an external resource.

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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Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely designed modules in the Employer Survey aim to assess the structure of the labor force; the skills (cognitive skills, behavior and personality traits, and job-relevant skills) currently being used; the skills that employers look for when hiring new workers; the propensity of firms to provide training (including satisfaction with education, training, and levels of specific skills) and the link between skills and compensation and promotion. The survey also captures background characteristics (size, legal form, industry, full time vs. non-standard employment and occupational breakdown), performance (revenues, wages and other costs, profits and scope of market), key labor market challenges and their ranking relative to other challenges, and job skill requirements of the firms being interviewed.

The questionnaire can be adapted to address a sample of firms in both informal and formal sectors, with varying sizes and industry classifications.

Geographic coverage

Capital Belgrade and other urban areas.

Analysis unit

The units of analysis are establishments or workplaces - a single location at which one or more employees work. The larger legal entity may include multiple establishments. The firms on the list will have been randomly chosen, with probability proportional to the number of employees in the firm.

Universe

The universe of the study are non-government businesses registered with Serbian Business Register Agency from 2013, with at least five employees from the following sectors: Manufacturing, Trade and Other Services.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling objective of the survey was to obtain interviews from 1000 non-government enterprise workplaces in the capital and urban regions of Serbia. Firms with less than five employees were excluded from the target population.

Two-stage stratified random sampling was used in the survey. A list of businesses registered with Serbian Business Register Agency from 2013 served as the sampling frame.

Detailed information about sampling is available in the Serbia Employer Survey Design Planning Report and Serbia Employer Survey Weighting Procedure, provided as Related Material.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire for the STEP Employer Survey consists of five modules:

Section 1 - Work Force Section 2 - Skills Used Section 3 - Hiring Practices Section 4 - Training and Compensation Section 5 - Background

In the case of Serbia, the questionnaire was adapted to the Serbian context and published in English and Serbian. It has been provided as Related Material.

Cleaning operations

STEP Data Management Process:

1) Raw data is sent by the survey firm

2) The World Bank (WB) STEP team runs data checks on the Questionnaire data. Comments and questions are sent back to the survey firm.

3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data.

4) The WB STEP team again check to make sure the data files are clean. This might require additional iterations with the survey firm.

5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies.

Response rate

An overall response rate of 48% was achieved in Serbia STEP Survey. Detailed distribution of responses by stratum can be found in the document Serbia Employer Survey Weighting Procedure, available as Related Material.

Abstract

Many small firms lack the finance and marketing skills needed for growth. A standard approach is to train the entrepreneur in these skills. However, rather than requiring entrepreneurs to learn everything, an alternative is to move beyond the boundary of the entrepreneur and link firms to these skills in a marketplace through insourcing workers, or outsourcing tasks to professionals. We conducted a randomized experiment in Nigeria to test the relative effectiveness of these different approaches to improving business practices. Insourcing and outsourcing both dominate business training; and do at least as well as business consulting at one-half of the cost. Replication data for this project are provided.

Geographic coverage

Firms in Abuja and Lagos

Analysis unit

Firm

Universe

Firms that applied and were selected for the government Growth and Employment (GEM) program

Kind of data

Sample survey data [ssd]

Sampling procedure

Firms applied to the Growth and Employment (GEM) Program. To qualify for the programs in our experiment, firms needed to pass a second screening step demonstrating they: (i) were not already insourcing or outsourcing both their marketing function and finance function; (ii) had between 2 and 15 workers; and (iii) received a score of 5.0 to 8.0 (out of 10) in terms of their baseline business practices5. This resulted in an experimental sample of 753 firms.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The following questionnaires were used for data collection and they are provided as supporting documentation: - BaselineQuestionnaire.pdf - the baseline training manual and questionnaire - Codebook_Baseline_Survey.xls - a codebook for the baseline questionnaire - GEM First Follow-Up Survey.pdf - the first follow-up survey - GEM Follow-p Survey_Round2.pdf - the second follow-up survey - GEM consultant and trainer questionnaire.pdf - questionnaire on background of Trainers and Consultants - SocialMediaScoring.xlsx - scoring questions for the 50 measures of social media quality - GEMServiceProviderSurvey.xls - questionnaire given to business service providers * InformationExperimentBaselineSurvey.pdf - baseline for the information experiment * InformationExperimentFollowupSurvey.pdf - follow-up survey for the information experiment

Response rate

The first follow-up survey had a response rate of 88.6%, and the second follow-up survey had a response rate of 86.1%. 93% of firms completed at least one of the follow-up surveys

Abstract

There is a widespread policy view that a lack of job opportunities at home is a key reason for migration, accompanied by suggestions of the need to spend more on creating these opportunities so as to reduce migration. Self-employment is widespread in poor countries, and faced with a lack of existing jobs, providing more opportunities for people to start businesses is a key policy option. But empirical evidence to support this idea is slight, and economic theory offers several reasons why the self-employed may in fact be more likely to migrate.

The "Self-employment and Migration", World Development study conducted two sets of analysis: 1) It put together panel surveys from 8 countries to look descriptively at the relationship between self-employment and migration; 2) It re-analyzed 7 randomized experiments that increased self-employment to look at their impacts on migration.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

Derived data, see paper and readme document found under 'Documentation' for sources

This map is adapted from the outstanding work of Dr. Joseph Kerski at ESRI. A map of political, social, and economic indicators for 2010. Created at the Data Analysis and Social Inquiry Lab at Grinnell College by Megan Schlabaugh, April Chen, and Adam Lauretig.Data from Freedom House, the Center for Systemic Peace, and the World Bank.Shapefile:Weidmann, Nils B., Doreen Kuse, and Kristian Skrede Gleditsch. 2010. The Geography of the International System: The CShapes Dataset. International Interactions 36 (1).Field Descriptions:

Variable Name Variable Description Years Available Further Description Source

TotPop Total Population 2011 Population of the country/region World Bank

GDPpcap GDP per capita (current USD) 2011 A measure of the total output of a country that takes the gross domestic product (GDP) and divides it by the number of people in the country. The per capita GDP is especially useful when comparing one country to another because it shows the relative performance of the countries. World Bank

GDPpcapPPP GDP per capita based on purchasing power parity (PPP) 2011

World Bank

HDI Human Development Index (HDI) 2011 A tool developed by the United Nations to measure and rank countries' levels of social and economic development based on four criteria: Life expectancy at birth, mean years of schooling, expected years of schooling and gross national income per capita. The HDI makes it possible to track changes in development levels over time and to compare development levels in different countries. World Bank

LifeExpct Life expectancy at birth 2011 The probable number of years a person will live after a given age, as determined by mortality in a specific geographic area. World Bank

MyrSchool Mean years of schooling 2011 Years that a 25-year-old person or older has spent in schools World Bank

ExpctSch Expected years of schooling 2011 Number of years of schooling that a child of school entrance age can expect to receive if prevailing patterns of age-specific enrolment rates persist throughout the child’s life. World Bank

GNIpcap Gross National Income (GNI) per capita 2011 Gross national income (GNI) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI per capita is gross national income divided by mid-year population. World Bank

GNIpcapHDI GNI per capita rank minus HDI rank 2011

World Bank

NaIncHDI Nonincome HDI
2011

World Bank

15+LitRate Adult (15+) literacy rate (%). Total 2010

UNESCO

EmplyAgr Employment in Agriculture 2009

World Bank

GDPenergy GDP per unit of energy use 2010 The PPP GDP per kilogram of oil equivalent of energy use. World Bank

GDPgrowth GDP growth (annual %) 2011

World Bank

GDP GDP (current USD) 2011

World Bank

ExptGDP Exports of Goods and Service (% GDP) 2011 The value of all goods and other market services provided to the rest of the world World Bank

ImprtGDP Imports of Goods and Service (% GDP) 2011 The value of all goods and other market services received from the rest of the world. World Bank

AgrGDP Agriculture, Value added (% GDP) 2011 Agriculture corresponds to ISIC divisions 1-5 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. World Bank

FDI Foreign Direct Investment, net (current USD) 2011 Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. World Bank

GNIpcap GNI per capita PP 2011 GNI per capita based on purchasing power parity (PPP). PPP GNI is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. World Bank

Inflatn Inflation, Consumer Prices (annual %) 2011 Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. World Bank

InfltnGDP Inflation, GDP deflator (annual %) 2011 Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. The GDP implicit deflator is the ratio of GDP in current local currency to GDP in constant local currency. World Bank

PctWomParl % women in national parliament 2010

United Nations

IntnetUser Internet Users, per 100 peple 2011 Internet users are people with access to the worldwide network. World Bank

HIVPrevlnc Estimated HIV Prevalence% - (Ages 15-49) 2009 Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV. UNAIDS estimates. UNAIDS

AgrLand Agricultural land (% of land area) 2009 Agricultural land refers to the share of land area that is arable, under permanent crops, and under permanent pastures. World Bank

AidRecPP Aid received per person (current US$) 2010 Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients; and is calculated by dividing net ODA received by the midyear population estimate. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). World Bank

AlcohAdul Alcohol consumption per adult (15+) in litres 2008 Liters of pure alcohol, computed as the sum of alcohol production and imports, less alcohol exports, divided by the adult population (aged 15 years and older). World Health Organization

ArmyPct Military expenditure (% of central government expenditure) 2008 Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). World Development Indicators (World Bank)

TFR Total Fertility Rate 2011 The average number of children that would be born per woman if all women lived to the end of their childbearing years and bore children according to a given fertility rate at each age. This indicator shows the potential for population change in a country. World Bank

CO2perUSD CO2 kg per USD 2008 Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. World Bank

ExpdtrPrim Expenditure per student, primary (% of GDP per capita) 2008 Public expenditure per pupil as a % of GDP per capita. Primary is the total public expenditure per student in primary education as a percentage of GDP per capita. Public expenditure (current and capital) includes government spending on educational institutions (both public and private), education administration as well as subsidies for private entities (students/households and other privates entities). World Bank

ExpdtrSecd Expenditure per student, secondary (% of GDP per capita) 2008 Public expenditure per pupil as a % of GDP per capita. Secondary is the total public expenditure per student in secondary education as a percentage of GDP per capita. World Bank

ExpdtrTert Expenditure per student, tertiary (% of GDP per capita) 2008 Public expenditure per pupil as a % of GDP per capita. Tertiary is the total public expenditure per student in tertiary education as a percentage of GDP per capita. World Bank

FDIoutf Foreign direct investment, net outflows (% of GDP) 2010 Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This series shows net outflows of investment from the

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Lebanon or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank's team that works in Lebanon, more in-depth insight into how the Bank's work is perceived. This is one tool the World Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Lebanon.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Lebanon perceive the Bank - Obtain systematic feedback from stakeholders in Lebanon regarding · Their views regarding the general environment in Lebanon · Their overall attitudes toward the World Bank in Lebanon · Overall impressions of the World Bank's effectiveness and results, knowledge and research, and communication and information sharing in Lebanon · Perceptions of the World Bank's future role in Lebanon - Use data to help inform the Lebanon country team's strategy

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Lebanon

Kind of data

Sample survey data [ssd]

Sampling procedure

In April-May 2013, 574 stakeholders of the World Bank in Lebanon were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President/Prime Minister/Minister, the office of a Parliamentarian; a ministry, ministerial department, or implementation agency; consultants/ contractors working on World Bank-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community-based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; the judiciary branch; and other organizations.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues Facing Lebanon: Respondents were asked to indicate whether Lebanon is headed in the right direction, what they thought were the top three development priorities in Lebanon, which areas would contribute most to reducing poverty and generating economic growth, and what best illustrates how "shared prosperity" would be achieved in Lebanon.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank's effectiveness in Lebanon, Bank staff preparedness to help Lebanon solve its development challenges, their agreement with various statements regarding the Bank's work, and the extent to which the Bank is an effective development partner. Respondents were asked to indicate the Bank's greatest values, greatest weaknesses, the most effective instruments in helping reduce poverty in Lebanon, with which stakeholder groups the Bank should collaborate more, in which sectoral areas the Bank should focus most resources, to what extent the Bank should seek to influence the global development agenda, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results, the extent to which the Bank meets Lebanon's needs for knowledge services and financial instruments, the extent Lebanon received value for money from the Bank's fee-based products/services, and the Bank's level of effectiveness across thirty three development areas, such as public sector governance/reform, social protection, job creation/employment, anti-corruption, and transport.

D. The World Bank's Knowledge: Respondents were asked to indicate how frequently they consult Bank knowledge work and activities, the areas on which the Bank should focus its research efforts and to rate the effectiveness and quality of the Bank's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank's "Safeguard Policy" requirements being reasonable, the Bank imposing reasonable conditions on its lending, disbursing funds promptly, increasing Lebanon's institutional capacity, and providing effective implementation support.

F. The Future Role of the World Bank in Lebanon: Respondents were asked to rate how significant a role the Bank should play in Lebanon in the near future and to indicate what the Bank should do to make itself of greater value.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the Bank, and their usage and evaluation of the Bank's websites. Respondents were asked about their awareness of the Bank's Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank's Open Data policy. Respondents were also asked about their level of agreement that they know how to find information from the Bank, that the Bank's websites are easy to navigate and useful, and that the Bank is responsive to information requests. Respondents were also asked to indicate whether they primarily use the Bank's country website or the Bank's main website and whether they primarily use high speed or dial-up Internet connection when visiting a World Bank website. Respondents were asked if they used/had used the Bank's Public information Centers (PICs) in Lebanon and to what extent the agree that PICs are a great source of information related to development in Lebanon.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in Lebanon, and their geographic location.

Response rate

A total of 196 stakeholders participated in the survey (34% response rate).

Explore comprehensive data on various indicators such as self-employment, female employment, average tariffs, net ODA provided, AIDS estimated deaths, fertility rate, school enrollment, GNI, gender parity index, agricultural support, poverty, and much more from the World Bank Millennium Development Goals dataset.

Self-employed, female (% of female employment), Average tariffs imposed by developed countries on agricultural products from developing countries (%), Net ODA provided to the least developed countries (% of donor GNI), AIDS estimated deaths (UNAIDS estimates), Fertility rate, total (births per woman), School enrollment, primary (% net), GNI, Atlas method (current US$), Average tariffs imposed by developed countries on clothing products from developing countries (%), School enrollment, primary (gross), gender parity index (GPI), Self-employed, total (% of total employment), Agricultural support estimate (% of GDP), Share of women in wage employment in the nonagricultural sector (% of total nonagricultural employment), Linear mixed-effect model estimates, Net ODA provided, total (current US$), School enrollment, secondary (gross), gender parity index (GPI), India, Bilateral, sector-allocable ODA to basic social services (% of bilateral ODA commitments), Average tariffs imposed by developed countries on clothing products from least developed countries (%), Bilateral ODA commitments that is untied (current US$), Qatar, Rural poverty gap at national poverty lines (%), GNI per capita, Atlas method (current US$), Urban poverty headcount ratio at national poverty lines (% of urban population), PPP conversion factor, private consumption (LCU per international $), Forest area (% of land area), Terrestrial protected areas (% of total land area), Poverty gap at national poverty lines (%), Annual, Proportion of seats held by women in national parliaments (%), Vulnerable employment, female (% of female employment), Contributing family workers, total (% of total employment), Net ODA provided, total (% of GNI), Total debt service (% of exports of goods, services and primary income), Total bilateral sector allocable ODA commitments (current US$), Average tariffs imposed by developed countries on textile products from least developed countries (%), Weighted Average, Net official development assistance received (current US$), Average tariffs imposed by developed countries on textile products from developing countries (%), Tuberculosis case detection rate (%, all forms), Oman, School enrollment, primary and secondary (gross), gender parity index (GPI), Prevalence of undernourishment (% of population), Population living in slums (% of urban population), Vulnerable employment, male (% of male employment), Debt service (PPG and IMF only, % of exports of goods, services and primary income), Ratio of school attendance rate of orphans to school attendance rate of non orphans, Weighted average, Net ODA received per capita (current US$), Population, total, Contributing family workers, male (% of male employment), Trade (% of GDP), Goods (excluding arms) admitted free of tariffs from least developed countries (% total merchandise imports excluding arms), Self-employed, male (% of male employment), PPP conversion factor, GDP (LCU per international $), Marine protected areas (% of territorial waters), Average tariffs imposed by developed countries on agricultural products from least developed countries (%), Pregnant women receiving prenatal care of at least four visits (% of pregnant women), Forest area (sq. km), Persistence to last grade of primary, total (% of cohort), Persistence to last grade of primary, female (% of cohort), Tuberculosis treatment success rate (% of new cases), Primary completion rate, total (% of relevant age group), School enrollment, tertiary (gross), gender parity index (GPI), Improved sanitation facilities (% of population with access), Poverty headcount ratio at national poverty lines (% of population), Net official development assistance and official aid received (current US$), Gross capital formation (% of GDP), Births attended by skilled health staff (% of total), Rural poverty headcount ratio at national poverty lines (% of rural population), Status under enhanced HIPC initiative, Children orphaned by HIV/AIDS, Vulnerable employment, total (% of total employment), Kuwait, Life expectancy at birth, total (years), Bahrain, Bilateral ODA commitments that is untied (% of bilateral ODA commitments), Persistence to last grade of primary, male (% of cohort), Bilateral, sector-allocable ODA to basic social services (current US$), Renewable internal freshwater resources per capita (cubic meters), Antiretroviral therapy coverage (% of people living with HIV), Pregnant women receiving prenatal care (%), Contributing family workers, female (% of female employment), Improved water source (% of population with access), Goods (excluding arms) admitted free of tariffs from developing countries (% total merchandise imports excluding arms), China, Total bilateral ODA commitments (current US$), Gap-filled total, Saudi Arabia, Adjusted net enrollment rate, primary (% of primary school age children), Reported cases of malaria, Annual freshwater withdrawals, total (% of internal resources), Net ODA received (% of GNI), Urban poverty gap at national poverty lines (%), Sum, Net ODA provided to the least developed countries (current US$), %

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

Follow data.kapsarc.org for timely data to advance energy economics research.

Abstract

The UNHCR Livelihoods Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation).

The process for developing the indicators began in 2015 with a review of existing tools and approaches. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices.

Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.

More info is available on the official website: https://lis.unhcr.org

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling was conducted by each participating operations based on general sampling guidance provided as the following: - At least 100 randomly selected beneficiaries for each project - Representativeness of sub-groups (gender, camp, etc.) should be kept as much as possible - Baseline and endline beneficiaries should be the same

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire contains the following sections: - partner information - general information on beneficiary - agriculture - self-employment - wage-employment

Wage and salaried workers, total (% of total employment) (modeled ILO estimate) in Mozambique was reported at 14.94 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mozambique - Wage and salaried workers; total (% of total employed) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Abstract

This research was conducted in Mongolia between December 2012 and July 2013, as part of the fifth round of the Business Environment and Enterprise Performance Survey (BEEPS V), a joint initiative of the World Bank and the European Bank for Reconstruction and Development. The objective of the study is to obtain feedback from enterprises in client countries on the state of the private sector. The research is also used to build a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through face-to-face interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Data from 360 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses.

The survey topics include firm characteristics, information about sales and suppliers, competition, infrastructure services, judiciary and law enforcement collaboration, security, government policies, laws and regulations, financing, overall business environment, bribery, capacity utilization, performance and investment activities, and workforce composition.

In 2011, the innovation module was added to the standard set of Enterprise Surveys questionnaires to examine in detail how introduction of new products and practices influence firms' performance and management.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with five or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was selected using stratified random sampling technique. Three levels of stratification were used: industry, establishment size, and region.

Industry was stratified into one manufacturing and two service sectors (retail, and other services).

Size stratification was defined following the standardized definition for the roll-out: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in 5 regions (city and the surrounding business area) throughout Mongolia.

The sample frame was from Business Registry, National Statistical Office (NSO) of Mongolia. The enumerated establishments were then used as the frame for the selection of a sample with the aim of obtaining interviews at 360 establishments with five or more employees.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 10.2% (59 out of 577 establishments).

In the dataset, the variables a2 (sampling region), a6a (sampling establishment's size), and a4a (sampling sector) contain the establishment's classification into the strata chosen for each country using information from the sample frame. Variable a4a coded using ISIC Rev 3.1 codes for the chosen industries for stratification. These codes include most manufacturing industries (15 to 37), retail (52), and (45, 50, 51, 55, 60-64, 72) for other services.

Mode of data collection

Face-to-face [f2f]

Research instrument

The structure of the data base reflects the fact that three different versions of the questionnaire were used. The basic questionnaire, the Core Module, includes all common questions asked to all establishments from all sectors. The second expanded variation, the Manufacturing Questionnaire, is built upon the Core Module and adds some specific questions relevant to manufacturing sectors. The third expanded variation, the Retail Questionnaire, is also built upon the Core Module and adds to the core specific questions relevant to retail firms. Each variation of the questionnaire is identified by the index variable a0.

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

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether, while the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond as a different option from don't know. b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of realized interviews per contacted establishments was 0.62. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.13.

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely designed modules in the Employer Survey aim to assess the structure of the labor force; the skills (cognitive skills, behavior and personality traits, and job-relevant skills) currently being used; the skills that employers look for when hiring new workers; the propensity of firms to provide training (including satisfaction with education, training, and levels of specific skills) and the link between skills and compensation and promotion. The survey also captures background characteristics (size, legal form, industry, full time vs. non-standard employment and occupational breakdown), performance (revenues, wages and other costs, profits and scope of market), key labor market challenges and their ranking relative to other challenges, and job skill requirements of the firms being interviewed.

The questionnaire can be adapted to address a sample of firms in both informal and formal sectors, with varying sizes and industry classifications.

Geographic coverage

Capital Tbilisi and other urban areas with the exclusion of Abkhazia and South Ossetia

Analysis unit

The units of analysis are establishments and workplaces – a single location at which one or more employees work. The larger legal entity may include multiple establishments.

Universe

The universe of the study are non-government enterprise workplaces registered with the Georgia State Department of Statistics with at least twenty employees in the following sectors: tourism, construction and IT and telecommunication.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling objective of the survey was to obtain interviews from 400 non-government enterprise workplaces in the capital and urban regions of Georgia. Firms with less than 20 employees were excluded from the target population.

Two-stage stratified random sampling was used in the survey. A list of businesses registered with the Georgia State Department of Statistics served as the sampling frame.

Detailed information about the sampling is available in the Georgia Employer Survey Design planning Report and Georgia Employer Survey Weighting Procedure, provided as an external resource.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire for the STEP Employer Survey consists of five modules: Section 1 – Work Force Section 2 – Skills Used Section 3 – Hiring Practices Section 4 – Training and Compensation Section 5 – Background

It has been provided as an external resource.

In the case of Georgia, the questionnaire was adapted to the Georgian context and published in English and Georgian.

Cleaning operations

STEP Data Management Process:

1) Raw data is sent by the survey firm.

2) The World Bank (WB) STEP team runs data checks on the Questionnaire data. Comments and questions are sent back to the survey firm.

3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data.

4) The WB STEP team again check to make sure the data files are clean. This might require additional iterations with the survey firm.

5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies.

Response rate

An overall response rate of 53.6% was achieved in Georgia STEP Survey. Detailed distribution of responses by stratum can be found in the Georgia Employer Survey Weighting Procedure (Table 3), available as an external resource.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Sierra Leone or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank's team that works in Sierra Leone, greater insight into how the Bank's work is perceived. This is one tool the World Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Sierra Leone. The World Bank commissioned an independent firm to oversee the logistics of this effort in Sierra Leone.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Sierra Leone perceive the Bank; - Obtain systematic feedback from stakeholders in Sierra Leone regarding: · Their views regarding the general environment in Sierra Leone; · Their overall attitudes toward the World Bank in Sierra Leone; · Overall impressions of the World Bank's effectiveness and results, knowledge work and activities, and communication and information sharing in Sierra Leone; · Perceptions of the World Bank's future role in Sierra Leone. - Use data to help inform Sierra Leone team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Sierra Leone

Kind of data

Sample survey data [ssd]

Sampling procedure

In March-April 2013, 600 stakeholders of the World Bank in Sierra Leone were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President; the office of the Prime Minister; the office of a Minister; the office of a Parliamentarian; employees of a ministry, ministerial department, or implementation agency; consultants/ contractors working on World Bank-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community-based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; judiciary branches; and other organizations.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues Facing Sierra Leone: Respondents were asked to indicate whether Sierra Leone is headed in the right direction, what they thought were the top three most important development priorities in the country, and which areas would contribute most to reducing poverty and generating economic growth in Sierra Leone.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank's effectiveness in Sierra Leone, Bank staff preparedness to help Sierra Leone solve its development challenges, their agreement with various statements regarding the Bank's work, and the extent to which the Bank is an effective development partner. Respondents were asked to indicate the sectoral areas on which it would be most productive for the Bank to focus its resources, the Bank's greatest values and weaknesses in its work, the most effective instruments in helping to reduce poverty in Sierra Leone, with which stakeholder groups the Bank should collaborate more, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results in Sierra Leone, the extent to which the Bank meets Sierra Leone's needs for knowledge services and financial instruments, and the Bank's level of effectiveness across forty-two development areas, such as education, energy, agricultural development, job creation/employment, infrastructure, and others.

D. The World Bank's Knowledge: Respondents were asked to indicate how frequently they consult Bank knowledge work/activities, the areas on which the Bank should focus its research efforts, and to rate the effectiveness and quality of the Bank's knowledge work/activities, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank's "Safeguard Policy" requirements being reasonable, the Bank imposing reasonable conditions on its lending, disbursing funds promptly, increasing Sierra Leone's institutional capacity, and providing effective implementation support. Respondents also were asked that to what extent they believed the Bank was adequately staffed in Sierra Leone.

F. The Future Role of the World Bank in Sierra Leone: Respondents were asked to rate how significant a role the Bank should play in Sierra Leone's development in the near future and to indicate what the Bank should do to make itself of greater value. They were also asked about the effectiveness of the donors in their work to see through development results on the ground and the effectiveness of the Bank in helping forge regional economic integration.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the Bank, and their usage and evaluation of the Bank's websites. Respondents were asked about their awareness of the Bank's Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank's Open Data policy. Respondents were also asked about their level of agreement that they know how to find information from the Bank and that the Bank is responsive to information requests.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in Sierra Leone, and their geographic location.

Response rate

A total of 340 stakeholders participated in the survey (57% response rate).

Abstract

In December 2017, the World Bank, in collaboration with Somali statistical authorities conducted the second wave of the Somali High Frequency Survey to monitor welfare and perceptions of citizens in all accessible areas of 17 regions within Somalia’s pre-war borders including Somaliland which self-declared independence in 1991. The survey interviewed 4,011 urban households, 1,106 rural households, 468 households in Internally Displaced People (IDP) settlements and 507 nomadic households. The sample was drawn randomly based on a multi-level clustered design. This dataset contains information on economic conditions, education, employment, access to services, security, perceptions and details before displacement for displaced households. It also includes comprehensive information on assets and consumption, to allow estimation of poverty based on the Rapid Consumption methodology as detailed in Pape and Mistiaen (2014).

Geographic coverage

The following pre-war regions: Awdal, Bakool, Banadir, Bari, Bay, Galgaduug, Gedo, Hiran, Lower Juba, Mudug, Nugaal, Sanaag, Middle and lower Shabelle, Sool, Togdheer and Woqooyi Galbeed (Somaliland self-declared independence in 1991).

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

Wave 2 of the SHFS employed a multi-stage stratified random sample, ensuring a sample representative of all subpopulations of interest. Strata were defined along two dimensions - administrative location (pre-war regions and emerging states) and population type (urban areas, rural settlements, IDP settlements, and nomadic population). Households were clustered into enumeration areas (EAs), with 12 interviews was expected for each selected EA. Primary sampling units (PSUs) were generated using a variety of techniques depending on the population type. The primary sampling unit (PSU) in urban as well as rural strata was the enumeration area (EA). For IDP strata, primary sampling units were IDP settlements as defined by UNCHR’s Shelter Cluster. Across all strata, PSUs were selected using a systematic random sampling approach with selection probability proportional to size (PPS). In IDP strata, PPS sampling is applied at the IDP settlement level. In second- and final-stage sample selection, a microlisting approach was used, such that EAs were divided into 12 smaller enumeration blocks, which were selected with equal probability. Every block was selected as 12 interviews per EA were required. A similar second-stage sampling strategy was employed for IDP strata. Each IDP settlement was segmented manually into enumeration blocks. Finally, one household per block was interviewed in all selected blocks within the enumeration area.The household was selected randomly with equal probability in two stages, following the micro-listing protocol. The strategy for sampling nomadic households relied on lists of water points. The list of water points was divided up by stratum at the federated member state level and they served as primary sampling units. Water points were selected in the first stage with equal probability, with 12 interviews to be conducted at each selected water point. The selection of nomadic households to interview relied on a listing process at each water point whose aim was to compile an exhaustive list of all nomadic households at the water point. For more details, see accompanying documents, available under the related materials tab.

Sampling deviation

EAs were replaced if security rendered field work unfeasible. Replacements were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits of the household.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The household questionnaire is in English. It includes the following modules: - Introduction - Module A: Administrative Information - Module B: Interview Information and Filters - Module C: Household Roster - Module D: Household Characteristics - Module E: Food Consumption - Module F: Non-Food Consumption - Module G: Livestock - Module H: Durable Goods - Module I: Perceptions and Social Services - Module J: Displacement - Module K: Fishing - Module L: Catastrophic Events and Disasters - Module M: Enumerator Conclusions - Appendix A - Enabling Conditions - Appendix B - Validation Conditions and Messages - Appendix C - Instructions - Appendix D - Options - Appendix E - Variables - Appendix F - Option Filters

The household questionnaire is provided under the Related Materials tab.

Abstract

The survey was conducted in Botswana between May and November 2010 as part of the Africa Enterprise Survey 2010, an initiative of the World Bank. Data from 268 establishments were analyzed.

The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private 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. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

Three levels of stratification were used in Botswana: industry, establishment size, and region.

For industry stratification, universe was divided into one manufacturing industry, one service industry (retail), and one residual sector. The manufacturing industry, service industry, and residual sectors had a target of 120 interviews each.

Size stratification was defined following the standardized definition for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined by two regions (city and the surrounding business area): Gaborone and Francistown.

In Botswana, two sample frames were used.

The first was supplied by the World Bank and consists of enterprises interviewed in Botswana 2006. The World Bank required that attempts should be made to re-interview establishments responding to the Botswana 2006 survey where they were within the selected geographical regions and met eligibility criteria. Due to the fact that the previous round of surveys seemed to have utilized different stratification criteria (or no stratification at all) and due to the prevalence of small firm in the 2006 sample the following convention was used. To avoid oversampling smaller firms and to limit the presence of Panel firms to a maximum of 50% of the achieved interviews, a decision was made to restrict the number of issued firms with less than 20 employees. That sample is referred to as the Panel.

The second sample frame was produced by Central Statistics Office of Botswana (CSO). A copy of that frames was sent to the TNS statistical team in London to select the establishments for interview.

The quality of the frame was assessed at the onset of the project through visits to a random subset of firms and local contractor knowledge. The sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc. In addition, the sample frame contains no telephone/fax numbers so the local contractor had to screen the contacts by visiting them. Due to response rate and ineligibility issues, additional sample had to be extracted by the World Bank in order to obtain enough eligible contacts and meet the sample targets.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 4.5% (47 out of 1040 establishments).

Sampling deviation

Due to the limitations of the sample frame obtained for the fresh sample a non-standard size stratification was used. Thus, the small size strata include firms with 5 to 29 employees and the medium size strata - firms with 30 to 99 employees.

The enumerated establishments were then used as the frame for the selection of a sample with the aim of obtaining interviews at 360 establishments with five or more employees. However, due to the smaller universe size the actual number of interviews that were achieved is 268.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire.

The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

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

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times, days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey

Labor force, total in Pakistan was reported at 83643815 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Labor force, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Abstract

This survey was conducted in Indonesia between April 2015 and November 2015, as part of the Enterprise Survey project, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries. Only registered businesses are surveyed in the Enterprise Survey.

Data from 1,320 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country's business environment. The remaining questions assess the survey respondents' opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this 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

The sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into seven manufacturing industries and two services industries- Food and Beverages (ISIC Rev. 3.1 code 15), Garments (ISIC code 18), Textiles (ISIC code 17), Chemicals (ISIC code 24), Rubber and Plastics (ISIC code 25), Non-metallic mineral products (ISIC code 26), Other Manufacturing (ISIC codes 16, 19-23, 27-37), Retail (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 55, 60-64, and 72).

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not common practice, apart from the construction and agriculture sectors which are not included in the survey.

Regional stratification for the Indonesia ES was done across nine regions: Jawa Barat, Jawa Timur, Jawa Tengah, DKI Jakarta, Banten, Sulawesi Selatan, Sumatera Utara, Bali and Lampung.

The sample frame consisted of listings of firms from four sources: First, for panel firms the list of 1,444 firms from the Indonesia 2009 ES was used. Second, for fresh firms (i.e., firms not covered in 2009), economic census data from Statistics Indonesia known in Indonesia as Badan Pusat Statistik, henceforth BPS, was used. 2006 BPS data was used for service firms and small manufacturing firms and 2012 BPS data was used for medium and large manufacturing firms.

Data for service firms were updated by cross-checking with lists from several business associations namely Aprindo 2013 for retail, AKI 2013, AKSINDO 2012 and Gapenri 2014 for construction, PHRI 2012 for hotels and restaurants and ALFI/ILFA 2014 for transportation.

The quality of the frame was enhanced by the verification process conducted by the contractor Kadence International. However, the sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 4.1% (108 out of 2,629 establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

The structure of the data base reflects the fact that 2 different versions of the survey instrument were used for all registered establishments. Questionnaires have common questions (core module) and respectfully additional manufacturing- and services-specific questions. The eligible manufacturing industries have been surveyed using the Manufacturing questionnaire (includes the core module, plus manufacturing specific questions). Retail firms have been interviewed using the Services questionnaire (includes the core module plus retail specific questions) and the residual eligible services have been covered using the Services questionnaire (includes the core module). Each variation of the questionnaire is identified by the index variable, a0.

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

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a - For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b - Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of interviews per contacted establishments was 0.50. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The share of rejections per contact was 0.23.

Wage and salaried workers, total (% of total employment) (modeled ILO estimate) in Kuwait was reported at 98.05 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kuwait - Wage and salaried workers; total (% of total employed) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Abstract

This research was conducted in Hungary in February-March 2010 as part of the second round of The Financial Crisis Survey. Data from 152 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Hungary.

Researchers revisited establishments interviewed in Hungary Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study was the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors were the primary business sectors of interest. This corresponded to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies were targeted for interviews. Services firms included construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government ownership were excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

291 establishments that participated in Hungary Enterprise Survey 2009 were contacted for The Financial Crisis Survey. The implementing contractor received directions that the final achieved sample should include at least 150 establishments.

For Hungary Enterprise Survey 2009, the sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into 23 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. Each sector had a target of 90 interviews.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in three regions. These regions are Central Hungary, West Hungary and East Hungary.

Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

For most countries covered in 2008-2009 BEEPS, two sample frames were used. The first was supplied by the World Bank and consisted of enterprises interviewed in BEEPS 2005. The World Bank required that attempts should be made to re-interview establishments responding to the BEEPS 2005 survey where they were within the selected geographical regions and met eligibility criteria. That sample is referred to as the Panel. The second frame for Hungary was the Dun & Bradstreet database, which was considered the most reliable for the country. That frame was sent to the TNS statistical team in London to select the establishments for interviews.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 4.6% (29 out of 630 establishments).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The following survey instrument is available: - Financial Crisis Survey Questionnaire

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 and callbacks.