Micro-Enterprise Survey 2019
Georgia, 2019
Get MicrodataIdentification
GEO_2019_MES_v01_M
Micro-Enterprise Survey 2019
| Name | Country code |
|---|---|
| Georgia | GEO |
Enterprise Survey [en/oth]
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.
An Enterprise Survey 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 2005-2006, most data collection efforts have been centralized within the Enterprise Analysis Unit. The Enterprise Surveys are conducted across all geographic regions and cover small, medium, and large companies. The surveys are administered to a representative sample of firms in the non-agricultural formal private economy. Data are used to create indicators that benchmark the quality of the business and investment climate across countries.
The ES currently cover over 190,000 firms in 152 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 survey was conducted in Georgia between July and November 2019 by the World Bank Group (WBG). In addition to the standard ES that covers formal private sector firms with five or more employees, in Georgia, a separate survey is fielded simultaneously to collect data from micro-enterprises - formal firms with less than five employees.
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.
Sample survey data [ssd]
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.
Version
Version 01. Edited, anonymous dataset for public distribution.
943938000
Scope
The Georgia 2019 Micro-Enterprise Survey covered the following topics:
- General information of the firm/ establishment
- Infrastructure and services
- Sales and supplies
- Business practices
- Degree of competition
- Innovation
- Capacity
- Land and permits
- Crime
- Finance
- Business-Government relations
- Labor
- Business environment
- Performance
Coverage
Georgia Micro-Enterprise Survey covers formal private sector firms with less than five employees.
Producers and sponsors
| Name |
|---|
| World Bank Group (WBG) |
| Name |
|---|
| World Bank Group |
Sampling
The sample for 2019 Georgia Micro-Enterprise was selected using stratified random sampling, following the methodology explained in the Sampling Note.
Two levels of stratification were used in this country: industry and region. The original sample design with specific information of the industries and regions chosen is described in "The Georgia 2019 Micro-Enterprise Surveys Data Set" report, Appendix C.
Industry stratification was designed in the way that follows: the universe was stratified into two manufacturing industries and three services industries- Food and Beverages (ISIC Rev. 3.1 code 15), Other Manufacturing (ISIC codes 16-37), Retail (ISIC code 52), Hospitality and Tourism (ISIC code 55) and Other Services (ISIC codes 45, 50, 51, 60-64, and 72).
There is no further breakdown by firm size for the micro-enterprise survey for sampling purpose and all firms are classified in to one size group, i.e., (1 to 4 employees).
Regional stratification was done across five regions: Tbilisi, East, Adjara, (Guria, Samegrelo, Zemo Svaneti) and Center. For the purposes of achieving the thresholds for representativeness, the ES indicators are calculated with some regions combined. In particular, Adjara and (Guria, Samegrelo, Zemo Svaneti) are combined.
Note: See Sections II and III of "The Georgia 2019 Micro-Enterprise Surveys Data Set" report for additional details on the sampling procedure.
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 (-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. However, there were clear cases of low response. Please, note that for this specific question, refusals were not separately identified from “Don’t know” responses.
The number of interviews per contacted establishments was 17%. 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 31.5%.
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 pw in Stata.)
Special care was given to the correct computation of the weights. 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, no reply after having called in different days of the week and in different business hours, 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.
Survey 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.
Data collection
| Start | End |
|---|---|
| 2019-07 | 2019-11 |
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. The variables a4b and a6c contain the industry and size of the establishment from the screener questionnaire.
Access policy
Enterprise Surveys
https://www.enterprisesurveys.org/Portal/
Cost: None
Depositor information
| Name | Affiliation |
|---|---|
| Joshua Seth Wimpey | The World Bank |
Data Access
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| Yes | Confidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised. |
The use of this dataset must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online).
Example:
The World Bank. Georgia - Micro-Enterprise Survey (MES) 2019, Ref. GEO_2019_MES_v01_M. Dataset downloaded from https://www.enterprisesurveys.org/portal/login.aspx on [date].
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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Enterprise Analysis Unit | World Bank Group | enterprisesurveys@worldbank.org |
Metadata production
DDI_GEO_2019_MES_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Economics Data Group | The World Bank | Documentation of the DDI |
2020-06-30
Metadata version
Version 01 (June 2020)