Ecuador - Enterprise Survey 2003-2006-2010-2017, Panel Data

The documented dataset covers Enterprise Survey (ES) panel data collected in Ecuador in 2003, 2006, 2010 and 2017, 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 gain an understanding of what firms experience in 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. Ecuador ES 2010 was conducted in June 2010 - October 2010, Ecuador ES 2017 was carried out in March - October 2017. Stratified random sampling was used to select the surveyed businesses. Data was collected using face-to-face interviews. Data from 1,838 establishments was analyzed: 272 businesses were from 2003 only, 335 firms were from 2006 only, 152 - from 2010 only, 275 - from 2017 only, 74 firms were from 2010 and 2017, 204 - from 2006 and 2010, 36 firms were from 2003, 2006, 2010 and 2017. 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.

Acronym: 
ES-P 2003-17
Type: 
Microdata
Topics: 
Topic not specified
Languages Supported: 
English
Geographical Coverage: 
Ecuador
Reference ID: 
ECU_2003-2017_ES-P_v01_M
Release Date: 
February 15, 2018

Harvest Source

Harvest Source: 
Microdata

Harvest Source ID

Harvest Source ID: 
9700

Last Updated

Last Updated: 
March 6, 2018
Data Collector(s) Name: 
Encuestas y Estudios Consulting Group
Data Collector(s) Name: 
Encuestas y Estudios Consulting Group
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.
Funding Name, Abbreviation, Role: 
World Bank; Inter-American Development Bank
Primary Investigator Name, Affiliation: 
World Bank
Response Rates: 
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.
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 into Manufacturing industries (ISIC Rev. 3.1 codes 15- 37), Retail industries (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 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). The sample frame consisted of listings of firms from two sources: for panel firms the list of 366 firms from the Ecuador 2010 ES was used, and for fresh firms (i.e., firms not covered in 2010) the list obtained from the Superintendencia de Compañías Valores y Seguros del Ecuador, 2016. In 2010, Regional stratification was defined in three locations (city and the surrounding business area): Pichincha, Guayas, and Azuay.
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.
Study Type: 
Enterprise Survey
Subtitle: 
Panel Data
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.
Universe: 
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 sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.
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 reports eligibility status of all firms interviewed in the previous wave as of the of the latest wave o e.g. in 2013-2016 panel, eligibility2016 reports status as of 2016 of all firms interviewed in 2013 - 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 __, with the year in which the variable was collected (e.g. _2013_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 US 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.
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.

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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. Ecuador - Enterprise Survey (ES-P) 2003-2006-2010-2017, Panel Data, Ref. ECU_2003-2017_ES-P_v01_M. Dataset downloaded from [URL] on [date].

The documented dataset covers Enterprise Survey (ES) panel data collected in Ecuador in 2003, 2006, 2010 and 2017, 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 gain an understanding of what firms experience in 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. Ecuador ES 2010 was conducted in June 2010 - October 2010, Ecuador ES 2017 was carried out in March - October 2017. Stratified random sampling was used to select the surveyed businesses. Data was collected using face-to-face interviews. Data from 1,838 establishments was analyzed: 272 businesses were from 2003 only, 335 firms were from 2006 only, 152 - from 2010 only, 275 - from 2017 only, 74 firms were from 2010 and 2017, 204 - from 2006 and 2010, 36 firms were from 2003, 2006, 2010 and 2017. 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.

Dataset Info

These fields are compatible with DCAT, an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web.
FieldValue
Modified Date
2018-03-06
Release Date
December 31,1969
Identifier
08bc8beb-45dd-465d-b976-89e33642633b
License
License Not Specified
Rating: 
0
No votes yet
Reference ID: 
ECU_2003-2017_ES-P_v01_M
Acronym: 
ES-P 2003-17
Type: 
Languages Supported: 
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.
Response Rates: 
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.
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.
Time Periods: 
March, 2018
Data Collector(s) Name: 
Encuestas y Estudios Consulting Group
Primary Investigator Name, Affiliation: 
World Bank
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 o e.g. in 2013-2016 panel, eligibility2016 reports status as of 2016 of all firms interviewed in 2013 - 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. _2013_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 US 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.
Subtitle: 
Panel Data
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.
Universe: 
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 sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.
Geographical Coverage: 
Data Classification of a Dataset: 
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.
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 into Manufacturing industries (ISIC Rev. 3.1 codes 15- 37), Retail industries (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 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). The sample frame consisted of listings of firms from two sources: for panel firms the list of 366 firms from the Ecuador 2010 ES was used, and for fresh firms (i.e., firms not covered in 2010) the list obtained from the Superintendencia de Compañías Valores y Seguros del Ecuador, 2016. In 2010, Regional stratification was defined in three locations (city and the surrounding business area): Pichincha, Guayas, and Azuay.
Release Date: 
Thursday, February 15, 2018
Last Updated Date: 
Tuesday, March 6, 2018
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.
Harvest Source: 
Harvest Source ID: 
9700
Citation Text: 
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. Ecuador - Enterprise Survey (ES-P) 2003-2006-2010-2017, Panel Data, Ref. ECU_2003-2017_ES-P_v01_M. Dataset downloaded from [URL] on [date].
Modified date: 
17596
Study Type: 
Enterprise Survey
Primary Dataset: 
Yes

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