Enterprise Survey 2006-2010-2016, Panel Data
El Salvador, 2006 - 2016
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Reference ID
SLV_2006-2016_ES-P_v01_M
Producer(s)
World Bank
Collection(s)
Metadata
Created on
May 12, 2017
Last modified
Sep 11, 2017
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Identification
Survey ID Number
SLV_2006-2016_ES-P_v01_M
Title
Enterprise Survey 2006-2010-2016, Panel Data
Subtitle
Panel Data
Country/Economy
| Name | Country code |
|---|---|
| El Salvador | SLV |
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 El Salvador in 2006, 2010 and 2016, as part of Latin America and the Caribbean Enterprise Surveys rollout, an initiative of the World Bank. The objective of the Enterprise 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.
Enterprise Surveys target a sample consisting of longitudinal (panel) observations and new cross-sectional data. Panel firms are prioritized in the sample selection, comprising up to 50% of the sample. For all panel firms, regardless of the sample, current eligibility or operating status is determined and included in panel datasets.
El Salvador ES 2010 was conducted in July 2010 - April 2011, El Salvador ES 2016 was carried out in March - August 2016. Stratified random sampling was used to select the surveyed businesses. Data was collected using face-to-face interviews.
Data from 1,772 establishments was analyzed: 577 businesses were from 2006 only, 87 - from 2010 only, 496 - from 2016 only, 314 firms were from 2010 and 2016, 100 - from 2006 and 2010, 198 firms were from 2006, 2010 and 2016.
The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and 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 percent of the questions objectively measure 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.
Enterprise Surveys target a sample consisting of longitudinal (panel) observations and new cross-sectional data. Panel firms are prioritized in the sample selection, comprising up to 50% of the sample. For all panel firms, regardless of the sample, current eligibility or operating status is determined and included in panel datasets.
El Salvador ES 2010 was conducted in July 2010 - April 2011, El Salvador ES 2016 was carried out in March - August 2016. Stratified random sampling was used to select the surveyed businesses. Data was collected using face-to-face interviews.
Data from 1,772 establishments was analyzed: 577 businesses were from 2006 only, 87 - from 2010 only, 496 - from 2016 only, 314 firms were from 2010 and 2016, 100 - from 2006 and 2010, 198 firms were from 2006, 2010 and 2016.
The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and 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 percent of the questions objectively measure 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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The primary sampling unit of the study is an 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 panelid 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, eligibility 2016 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 panelid 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, eligibility 2016 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 Enterprise Surveys includes:
- characteristics of an 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 an 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 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.
Producers and sponsors
Primary investigators
| Name |
|---|
| World Bank |
Funding Agency/Sponsor
| Name |
|---|
| World Bank |
| Inter-American Development Bank |
Sampling
Sampling Procedure
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).
Size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
In 2016, regional stratification was done across four regions: San Salvador Metropolitan Area, Greater San Salvador (municipalities of Sensuntepeque, Cojutepeque, Ciudad Arce, Colon, La Libertad, Quezaltepeque, San Juan Opico, Olocuilta, Zacatecoluca, Santo Tomas, and San Vicente), West (Ahuachapan, Chalchuapa, Metapan, Santa Ana, and Sonsonate) and East (La Union, Santa Rosa de Lima, San Francisco Gotera, San Miguel, and Usulutan).
The sample frame for 2016 ES consisted of listings of firms from two sources: the panel list of 360 firms from El Salvador 2010 ES and data from Dirección General de Estadística y Censos (DIGESTYC) for fresh (non-panel) establishments.
In 2010, regional stratification was defined in two locations: San Salvador and the rest of the country.
The sample frame for 2010 ES consisted of listings of firms from two sources: the panel list of firms from El Salvador 2006 ES and data from Dirección General de Estadística y Censos (DIGESTYC) for fresh (non-panel) establishments.
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).
Size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
In 2016, regional stratification was done across four regions: San Salvador Metropolitan Area, Greater San Salvador (municipalities of Sensuntepeque, Cojutepeque, Ciudad Arce, Colon, La Libertad, Quezaltepeque, San Juan Opico, Olocuilta, Zacatecoluca, Santo Tomas, and San Vicente), West (Ahuachapan, Chalchuapa, Metapan, Santa Ana, and Sonsonate) and East (La Union, Santa Rosa de Lima, San Francisco Gotera, San Miguel, and Usulutan).
The sample frame for 2016 ES consisted of listings of firms from two sources: the panel list of 360 firms from El Salvador 2010 ES and data from Dirección General de Estadística y Censos (DIGESTYC) for fresh (non-panel) establishments.
In 2010, regional stratification was defined in two locations: San Salvador and the rest of the country.
The sample frame for 2010 ES consisted of listings of firms from two sources: the panel list of firms from El Salvador 2006 ES and data from Dirección General de Estadística y Censos (DIGESTYC) for fresh (non-panel) 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.
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.
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 website.
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.
Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
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 website.
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.
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 |
|---|---|
| 2006 | 2006 |
| 2010-07 | 2011-04 |
| 2016-03 | 2016-08 |
Data Collection Mode
Face-to-face [f2f]
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 or director of each establishment. In some cases, when the phone numbers were unavailable in the sample frame, the enumerators applied the screeners in person.
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 or director of each establishment. In some cases, when the phone numbers were unavailable in the sample frame, the enumerators applied the screeners in person.
Data Collectors
| Name | Affiliation |
|---|---|
| Mercaplan Centroamérica y El Caribe | Data collection in 2010 |
| Data Research, S.A. de C.V. | Data collection in 2010 |
| Fusades | Data collection in 2016 |
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 | |
|---|---|
| Enterprise Analysis Unit | 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.
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. El Salvador Enterprise Survey (ES-P) 2006-2016, Panel Data, Ref. SLV_2006-2016_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. El Salvador Enterprise Survey (ES-P) 2006-2016, Panel Data, Ref. SLV_2006-2016_ES-P_v01_M. Dataset downloaded from [URL] on [date].
Archive where study is originally stored
Enterprise Surveys
https://www.enterprisesurveys.org/Portal/
Cost: None
https://www.enterprisesurveys.org/Portal/
Cost: None
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_SLV_2006-2016_ES-P_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the study |
Date of Metadata Production
2017-05-12
DDI Document version
v01 (May 2017)