Enterprise Survey 2009
Liberia, 2008 - 2009
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Reference ID
LBR_2009_ES_v01_M_WB
Producer(s)
World Bank,
Collection(s)
Created on
May 24, 2011
Last modified
Sep 26, 2013
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Identification
Survey ID Number
LBR_2009_ES_v01_M_WB
Title
Enterprise Survey 2009
Country/Economy
| Name | Country code |
|---|---|
| Liberia | LBR |
Study type
Enterprise/Establishment Survey [en/oth]
Series Information
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 2005-06, 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. Data are used to create indicators that benchmark the quality of the business and investment climate across countries.
The Enterprise Survey initiative includes two types of surveys: Enterprise Surveys and Indicator Surveys. This study is an Indicator Survey. An Indicator Survey, which is similar to an Enterprise Survey, 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 survey instrument is limited to just those questions which form the basis of the global indicators as presented on the Enterprise Surveys website www.enterprisesurveys.org.
The Enterprise Survey initiative includes two types of surveys: Enterprise Surveys and Indicator Surveys. This study is an Indicator Survey. An Indicator Survey, which is similar to an Enterprise Survey, 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 survey instrument is limited to just those questions which form the basis of the global indicators as presented on the Enterprise Surveys website www.enterprisesurveys.org.
Abstract
This research is an Indicator Survey conducted in Liberia from Sept. 15, 2008 to Feb. 13, 2009, as part of the Enterprise Survey initiative. The survey covered 150 establishments.
An Indicator Survey, which is similar to an Enterprise Survey, 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 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.
Questionnaire topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, land and permits, taxation, business-government relations, performance measures, AIDS and sickness. The mode of data collection is face-to-face interviews.
An Indicator Survey, which is similar to an Enterprise Survey, 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 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.
Questionnaire topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, land and permits, taxation, business-government relations, performance measures, AIDS and sickness. The mode of data collection is face-to-face interviews.
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.
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 |
|---|
| World Bank |
Producers
Funding Agency/Sponsor
| Name |
|---|
| World Bank |
Other Identifications/Acknowledgments
| Name |
|---|
| TNS opinion |
Sampling
Sampling Procedure
Three levels of stratification were used in the Liberia sample: firm sector, firm size, and geographic region.
Industry stratification was designed as follows: the universe was stratified into one manufacturing industry and one services industry (retail).
Size stratification was defined following the standardized definition used for the Indicator 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.
Regional stratification was defined in terms of the geographic locations with the largest commercial presence in the country: Montserrado, Nimba, and Margibi.
It was possible to get a single usable frame for Liberia. The frame acquired for Liberia was from its Central Bureau of Statistics and used data obtained from the 2007 Establishment Census.
The quality of the frame was assessed at the onset of the project and 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 1.37% (5 out of 364 establishments for the sample). Breaking down by industry, the following numbers of establishments were surveyed: Manufacturing - 81, Services - 69.
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Liberia
Implementation 2009" in "Technical Documents" folder.
Industry stratification was designed as follows: the universe was stratified into one manufacturing industry and one services industry (retail).
Size stratification was defined following the standardized definition used for the Indicator 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.
Regional stratification was defined in terms of the geographic locations with the largest commercial presence in the country: Montserrado, Nimba, and Margibi.
It was possible to get a single usable frame for Liberia. The frame acquired for Liberia was from its Central Bureau of Statistics and used data obtained from the 2007 Establishment Census.
The quality of the frame was assessed at the onset of the project and 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 1.37% (5 out of 364 establishments for the sample). Breaking down by industry, the following numbers of establishments were surveyed: Manufacturing - 81, Services - 69.
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Liberia
Implementation 2009" in "Technical Documents" folder.
Response Rate
The Indicator Surveys, along with all other surveys, suffer from both survey non-response and 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. Different strategies were used to address these issues.
Survey non-response was addressed by maximizing efforts to contact establishments that were initially sampled. When the survey frame was extracted from the sampling frame, several establishments with the same strata characteristics were randomly selected for each interview and each establishment was assigned a preference number. Substitutions of replacement establishments were made in order to help achieve targets on the number of interviews for each stratum. Extensive efforts were made to complete interviews with each first preference establishment before contact with a replacement establishment was allowed. At least four attempts were made to contact each sampled establishment for an interview at different times/days of the week before a replacement establishment was allowed to be contacted for an interview.
The number of contacted establishments per realized interview was 1.34. For each establishment eligible for an interview, 0.23 refused to participate.
In completed surveys, 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 on important questions including total sales, cost figures and employment levels were re-contacted in order to complete this information. However, re-contacts did not fully eliminate low response rates for some items.
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Liberia Implementation 2009" in "Technical Documents" folder.
Survey non-response was addressed by maximizing efforts to contact establishments that were initially sampled. When the survey frame was extracted from the sampling frame, several establishments with the same strata characteristics were randomly selected for each interview and each establishment was assigned a preference number. Substitutions of replacement establishments were made in order to help achieve targets on the number of interviews for each stratum. Extensive efforts were made to complete interviews with each first preference establishment before contact with a replacement establishment was allowed. At least four attempts were made to contact each sampled establishment for an interview at different times/days of the week before a replacement establishment was allowed to be contacted for an interview.
The number of contacted establishments per realized interview was 1.34. For each establishment eligible for an interview, 0.23 refused to participate.
In completed surveys, 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 on important questions including total sales, cost figures and employment levels were re-contacted in order to complete this information. However, re-contacts did not fully eliminate low response rates for some items.
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Liberia Implementation 2009" in "Technical Documents" folder.
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:
a- Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility.
b- 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 .
c- 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.
a- Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility.
b- 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 .
c- 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.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2008-09 | 2009-02 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Liberia
Implementation 2009" in "Technical Documents" folder.
Implementation 2009" in "Technical Documents" folder.
Data Collection Notes
Private contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and corruption-related topics, private contractors are preferred over any government agency or an organization/institution associated with government, and are hired by the World Bank to collect the data.
The Enterprise Surveys are usually implemented following a two-stage procedure. In the first stage, a screener questionnaire is applied over the phone to determine eligibility and to make appointments; in the second stage, a face-to-face interview takes place with the Manager/Owner/Director of each establishment. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey.
All Enterprise Surveys are conducted in the local languages.
The Enterprise Surveys are usually implemented following a two-stage procedure. In the first stage, a screener questionnaire is applied over the phone to determine eligibility and to make appointments; in the second stage, a face-to-face interview takes place with the Manager/Owner/Director of each establishment. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey.
All Enterprise Surveys are conducted in the local languages.
Data Collectors
| Name |
|---|
| Liberia Institute For Statistics and Geo- Information Services |
Questionnaires
Questionnaires
The current survey instruments are available:
- Indicator Survey Questionnaire
- Screener Questionnaire.
Questionnaire topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, land and permits, taxation, business-government relations, performance measures, and AIDS and sickness.
- Indicator Survey Questionnaire
- Screener Questionnaire.
Questionnaire topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, land and permits, taxation, business-government relations, performance measures, and AIDS and sickness.
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
| enterprisesurveys@worldbank.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 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 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
Where necessary please site the source as "Enterprise Analysis Unit - World Bank Group www.enterprisesurveys.org"
Metadata production
DDI Document ID
DDI_LBR_2009_ES_v01_M_WB
Producers
| Name |
|---|
| Antonina Redko |
DDI Document version
v01