Enterprise Survey 2009-2017, Panel Data
Liberia, 2009 - 2017
World Bank, Liberia Institute for Statistics and Geo-Information Services
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June 15, 2018
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June 15, 2018
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Identification
Survey ID Number
LBR_2009-2017_ES-P_v01_M
Title
Enterprise Survey 2009-2017, Panel Data
Subtitle
Panel Data
Country
| Name | Country code |
|---|---|
| Liberia | LBR |
Study type
Enterprise Survey [en/oth]
Series Information
As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving business environments as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys 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 (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 2005-2006, 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 is used to create indicators that benchmark the quality of the business and investment climate across countries.
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 2005-2006, 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 is used to create indicators that benchmark the quality of the business and investment climate across countries.
Abstract
The documented dataset covers Enterprise Survey (ES) panel data collected in Liberia in 2009 and 2017, as part of the Enterprise Survey initiative of the World Bank. An Indicator Survey is similar to an Enterprise Survey; it is implemented for smaller economies where the sampling strategies inherent in an Enterprise Survey are often not applicable due to the limited universe of firms.
The objective of the 2009-2017 Enterprise Survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as 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. Through interviews with firms in the manufacturing and services sectors, the Indicator Survey data provides information on the constraints to private sector growth and is used to create statistically significant business environment indicators that are comparable across countries.
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.
The objective of the 2009-2017 Enterprise Survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as 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. Through interviews with firms in the manufacturing and services sectors, the Indicator Survey data provides information on the constraints to private sector growth and is used to create statistically significant business environment indicators that are comparable across countries.
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 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 Description
v01, edited, anonymous dataset for public distribution
The Enterprise Surveys panel datasets have the following common format:
- Variable panel allows easy identification of panel observations
- Variable panel id is the same across the waves for the same firm
- Variable eligibility<year> reports eligibility status of all firms interviewed in the previous wave as of the <year> of the latest wave, e.g. in 2009-2016 panel, eligibility2016 reports status as of 2016 of all firms interviewed in 2009
- Wherever possible variables are matched across waves. If needed, matches are made by converting variable names in older waves to variable names in the most recent wave
- Due to methodological changes and evolution of the survey instrument it is not possible to match all variables in the datasets
- Variables that are not matched across waves are named as _<year>_<variable>, with the year in which the variable was collected (e.g. _2009_date)
- It is recommended that users thoroughly familiarize themselves with the questionnaires from each of the years contained in the dataset before proceeding with analysis
- Some monetary unit variables in 2002 and 2005 surveys (in U.S. currency) are converted into the local currency units (LCU) using the market, period average, exchange rates. The sources of the exchange rates are the International Financial Statistics (IFS - IMF) websites
- Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
The Enterprise Surveys panel datasets have the following common format:
- Variable panel allows easy identification of panel observations
- Variable panel id is the same across the waves for the same firm
- Variable eligibility<year> reports eligibility status of all firms interviewed in the previous wave as of the <year> of the latest wave, e.g. in 2009-2016 panel, eligibility2016 reports status as of 2016 of all firms interviewed in 2009
- Wherever possible variables are matched across waves. If needed, matches are made by converting variable names in older waves to variable names in the most recent wave
- Due to methodological changes and evolution of the survey instrument it is not possible to match all variables in the datasets
- Variables that are not matched across waves are named as _<year>_<variable>, with the year in which the variable was collected (e.g. _2009_date)
- It is recommended that users thoroughly familiarize themselves with the questionnaires from each of the years contained in the dataset before proceeding with analysis
- Some monetary unit variables in 2002 and 2005 surveys (in U.S. currency) are converted into the local currency units (LCU) using the market, period average, exchange rates. The sources of the exchange rates are the International Financial Statistics (IFS - IMF) websites
- Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
Scope
Notes
The scope of the study includes:
- Characteristics of establishment
- Infrastructure and services
- Sales and supplies
- Degree of competition
- Capacity
- Land and permits
- Innovation
- Crime
- Finance
- Business-government relations
- Labor
- Business environment
- Performance
- Characteristics of establishment
- Infrastructure and services
- Sales and supplies
- Degree of competition
- Capacity
- Land and permits
- Innovation
- Crime
- Finance
- Business-government relations
- Labor
- Business environment
- Performance
Coverage
Geographic Coverage
National
Geographic Unit
Regions covered are selected based on the number of establishments, contribution to employment, and value added. In most cases these regions are metropolitan areas and reflect the largest centers of economic activity in a country.
Universe
The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| World Bank | |
| Liberia Institute for Statistics and Geo-Information Services | Government of Liberia |
Producers
| Name | Role |
|---|---|
| Kantar Belgium SA (previously TNS OPINION) | Main contractor - Sampling implementation |
| Kantar TNS Senegal | Main contractor - Sampling implementation |
| TNS Opinion – UK | Sample selection |
Funding Agency/Sponsor
| Name |
|---|
| The World Bank |
Sampling
Sampling Procedure
The sample for the 2009-2017 Liberia Enterprise Survey (ES) was selected using stratified random sampling, following the methodology explained in the Sampling Note. Stratified random was preferred over simple random sampling for several reasons:
- To obtain unbiased estimates for different subdivisions of the population with some known level of precision.
- To obtain unbiased estimates for the whole population. 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 subsector 72, IT, which was added to the population under study), and all public or utilities sectors.
- To make sure that the final total sample includes establishments from all different sectors and that it is not concentrated in one or two of industries/sizes/regions.
- To exploit the benefits of stratified sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e., lower standard errors, other things being equal.)
- Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous.
- The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.
Three levels of stratification were used in this country: industry, establishment size, and region. Industry stratification was designed as follows: the universe was stratified as into manufacturing and services industries. Manufacturing (ISIC Rev. 3.1 codes 15 - 37), and Services (ISIC codes 45, 50-52, 55, 60-64, and 72).
For the Liberia ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
Regional stratification for the Liberia ES was done across three regions: Montserrado, Margibi, and Nimba.
- To obtain unbiased estimates for different subdivisions of the population with some known level of precision.
- To obtain unbiased estimates for the whole population. 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 subsector 72, IT, which was added to the population under study), and all public or utilities sectors.
- To make sure that the final total sample includes establishments from all different sectors and that it is not concentrated in one or two of industries/sizes/regions.
- To exploit the benefits of stratified sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e., lower standard errors, other things being equal.)
- Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous.
- The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.
Three levels of stratification were used in this country: industry, establishment size, and region. Industry stratification was designed as follows: the universe was stratified as into manufacturing and services industries. Manufacturing (ISIC Rev. 3.1 codes 15 - 37), and Services (ISIC codes 45, 50-52, 55, 60-64, and 72).
For the Liberia ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
Regional stratification for the Liberia ES was done across three regions: Montserrado, Margibi, and Nimba.
Response Rate
There was a high response rate especially as a result of positive attitude towards the international community in collaboration with the government in their reconstruction efforts after a period of civil strife.There was also very positive attitude towards World Bank initiatives.
Weighting
For some units it was impossible to determine eligibility because the contact was not successfully completed. Consequently, different assumptions as to their eligibility result in different universe cells' adjustments and in different sampling weights. Three sets of assumptions were considered:
- Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility.
- Median assumption: eligible establishments are those for which it was possible to directly determine eligibility and those that rejected the screener questionnaire or an answering machine or fax was the only response. Median weights are used for computing indicators on the www.enterprisesurveys.org website.
- Weak assumption: in addition to the establishments included in points a and b, all establishments for which it was not possible to finalize a contact are assumed eligible. This includes establishments with dead or out of service phone lines, establishments that never answered the phone, and establishments with incorrect addresses for which it was impossible to find a new address. Note that under the weak assumption only observed non-eligible units are excluded from universe projections.
Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
- Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility.
- Median assumption: eligible establishments are those for which it was possible to directly determine eligibility and those that rejected the screener questionnaire or an answering machine or fax was the only response. Median weights are used for computing indicators on the www.enterprisesurveys.org website.
- Weak assumption: in addition to the establishments included in points a and b, all establishments for which it was not possible to finalize a contact are assumed eligible. This includes establishments with dead or out of service phone lines, establishments that never answered the phone, and establishments with incorrect addresses for which it was impossible to find a new address. Note that under the weak assumption only observed non-eligible units are excluded from universe projections.
Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2009 | 2017 |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Liberia Institute for Statistics and Geo-Information Services | LISGIS | Government of Liberia |
Questionnaires
Questionnaires
The current survey instruments are available:
- Services and Manufacturing Questionnaire
- Screener Questionnaire.
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.
- Services and Manufacturing Questionnaire
- Screener Questionnaire.
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.
Data Processing
Data Editing
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.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Enterprise Analysis Unit | The World Bank | enterprisesurveys@worldbank.org | http://www.enterprisesurveys.org |
Confidentiality
Confidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.
Access conditions
Aggregate indicators based on Enterprise Survey data are available to the public at https://www.enterprisesurveys.org
Firm-level data is also available to the public free-of-charge. In order to access the firm-level data, users must agree to abide by a strict confidentiality agreement available through Enterprise Analysis Unit website by clicking on "External users register here" at https://www.enterprisesurveys.org/Portal.
Firm-level data is also available to the public free-of-charge. In order to access the firm-level data, users must agree to abide by a strict confidentiality agreement available through Enterprise Analysis Unit website by clicking on "External users register here" at https://www.enterprisesurveys.org/Portal.
Citation requirements
The use of this dataset must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online)
Example:
The World Bank. Liberia Enterprise Survey (ES-P) 2009-2017, Panel Data, Ref. LBR_2009-2017_ES-P_v01_M. Dataset downloaded from [URL] on [date].
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online)
Example:
The World Bank. Liberia Enterprise Survey (ES-P) 2009-2017, Panel Data, Ref. LBR_2009-2017_ES-P_v01_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
DDI Document ID
DDI_LBR_2009-2017_ES-P_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the study |
Date of Metadata Production
2018-03-01
DDI Document version
v01 (February 2018)