An Enterprise Survey (ES) is a firm-level survey of a representative sample of an economy's private sector. Firm-level surveys have been conducted since 1998 by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit (FPDEA). The Enterprise Surveys are conducted across all geographic regions and cover small, medium, and large companies. Data are used to create indicators that benchmark the quality of the business and investment climate across countries.
The ES currently cover over 185,000 firms in 151 countries, of which 143 have been surveyed following the standard methodology. This allows for better comparisons across countries and across time. Data are used to create statistically significant business environment indicators that are comparable across countries. The ES are also used to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms.
The documentation covers Enterprise Survey panel datasets that were collected in Uzbekistan in 2008, 2013 and 2019.
The Uzbekistan ES 2008 was conducted between 2008 and 2009. The Uzbekistan ES 2013 was conducted between January 2013 and October 2013. Finally, the Uzbekistan ES 2019 was conducted between February 2019 and August 2019. The objective of the Enterprise Survey is to gain an understanding of what firms experience in the private sector.
As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving the business environment as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both objective data based on firms' experiences and enterprises' perception of the environment in which they operate.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
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 take 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.
Version 01. Edited, anonymous dataset for public distribution.
The scope of the study includes:
- General information and characteristics of the establishment
- Infrastructure and services
- Sales and supplies
- Degree of competition
- Land and permits
- Business-government relations
- Business environment
- Green Economy Module:
- Environment-related impacts
- Management and the environment
- Environmental policy and regulation
- Environmental impact of the establishment
For the Uzbekistan ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
Producers and sponsors
World Bank Group (WBG)
European Bank for Reconstruction and Development (EBRD)
World Bank Group
European Bank for Reconstruction and Development
The sample for Uzbekistan ES 2008, 2013, 2019 were were selected using stratified random sampling, following the methodology explained in the Sampling Manual for Uzbekistan ES 2008 and Uzbekistan ES 2013, and in the Sampling Note for 2019 Uzbekistan ES.
Three levels of stratification were used in this country: industry, establishment size, and oblast (region). The original sample designs with specific information of the industries and regions chosen are described in the "Republic of Uzbekistan Enterprise Surveys Data Set" report for Uzbekistan ES 2008 and "The Uzbekistan 2013 Enterprise Surveys Data Set" report for Uzbekistan ES 2013, Appendix E. For Uzbekistan 2019 ES, specific information of the industries and regions chosen is described in the "The Uzbekistan 2019 Enterprise Surveys Data Set" report, Appendix C.
For Uzbekistan ES 2008, 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 as defined in the sampling manual. Each sector had a target of 120 interviews.
For Uzbekistan ES 2013, industry stratification was designed in the way that follows: the universe was stratified into one manufacturing industry, and two service industries (retail, and other services).
Finally, for Uzbekistan ES 2019, industry stratification was designed in the way that follows: the universe was stratified into six manufacturing industries and two services industries: Food and Beverages (ISIC Rev. 3.1 code 15), Textiles (ISIC 17), Garments (ISIC code 18), Rubber and Plastics Products (ISIC code 25), Non-Metallic Mineral Products (ISIC code 26), Other Manufacturing (ISIC codes 16, 19-24, 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 Uzbekistan ES 2008, regional stratification was defined in 3 regions. These regions are Tashkent, Samarkandskaya, and Tashkentskaya.
For Uzbekistan ES 2013, regional stratification was defined in 3 regions (city and the surrounding business area) throughout Uzbekistan.
For Uzbekistan ES 2019, Regional stratification was done across nine regions: Andijan Region, Fergana Region, Qashqadaryo Region, Samarqand Region, Tashkent Region, Tashkent, Karakalpakstan, Navoiy and Jizzakh Region, and Surxondaryo Region.
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 the refusal to respond as a different option from don’t know (-7).
b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response.
For Uzbekistan ES 2008 and 2013, survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Up to 4 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. Further research is needed on survey non-response in the Enterprise Surveys regarding potential introduction of bias.
For 2008, the number of contacted establishments per realized interview was 1.61. 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 relatively low ratio of contacted establishments per realized interview (1.61) suggests that the main source of error in estimates in the Uzbekistan may be selection bias and not frame inaccuracy.
For 2013, the number of realized interviews per contacted establishment was 33%. 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 11%.
Finally, for 2019, the number of interviews per contacted establishments was 37.9%. 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 36.3%.
Since the sampling design was stratified and employed differential sampling individual observations should be properly weighted when making inferences about the population. Under stratified random sampling unweighted estimates are biased unless sample sizes are proportional to the size of each stratum. With stratification the probability of selection of each unit is, in general, not the same. Consequently, individual observations must be weighted by the inverse of their probability of selection (probability weights or pa in Stata.)
Special care was given to the correct computation of the weights. Considering the varying quality of the sample frames, it was imperative to accurately adjust the totals within each region/industry/size stratum to account for the presence of ineligible units (the firm discontinued businesses or was unattainable, education or government establishments, establishments with less than 5 employees, no reply after having called in different days of the week and in different business hours, out of order, no tone in the phone line, answering machine, fax line, wrong address or moved away and could not get the new references) The information required for the adjustment was collected in the first stage of the implementation: the screening process. Using this information, each stratum cell of the universe was scaled down by the observed proportion of ineligible units within the cell. Once an accurate estimate of the universe cell (projections) was available, weights were computed using the number of completed interviews. Specifically for Slovenia 2009 ES, note that panel firms with less than 5 employees were also included in the eligible sample and special coded zero was used in a6a and a6b (sample and screener size) to reflect those cases.
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
The surveys were implemented following a 2-stage procedure. Typically, first a screener questionnaire is applied over the phone to determine eligibility and to make appointments. Then a face-to-face interview takes place with the Manager/Owner/Director of each establishment. However, sometimes the phone numbers were unavailable in the sample frame, and thus the enumerators applied the screeners in person. Interviews were conducted using Computer-assisted personal interviewing (CAPI) in Uzbekistan. The variables a4b and a6c contain the industry and size of the establishment from the screener questionnaire.
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.
Enterprise Analysis Unit
The World Bank Group
Where necessary please site the source as "Enterprise Analysis Unit - World Bank Group https://www.enterprisesurveys.org"
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
DDI Document ID
Development Economics Data Group
The World Bank
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 01 (July 2020)