Ecuador - Enterprise Survey 2017

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The survey was conducted in Ecuador between March and October of 2017 as part of Enterprise Surveys project, an initiative of the World Bank. Data from 361 establishments was analyzed. The objective of the survey is to gain an understanding of what firms experience in the private sector. 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 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 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.

Type: 
Microdata
Acronym: 
ES 2017
Languages Supported: 
English
Topics: 
Topic not specified
Geographical Coverage: 
Ecuador
Release Date: 
February 15, 2018

Last Updated

Last Updated: 
February 15, 2018

Harvest System ID

Harvest System ID: 
Microdata

Harvest Source ID

Harvest Source ID: 
9698
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.
Version Description: 
v01, edited, anonymous dataset for public distribution
Funding Name, Abbreviation, Role: 
World Bank; Inter-American Development Bank
Study Type: 
Enterprise Survey
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 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.
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.
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.
Primary Investigator Name, Affiliation: 
World Bank
Sampling Procedure: 
The sample for 2017 Ecuador ES was selected using stratified random sampling. 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). For the Ecuador 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 was done across three regions: Pichincha, Guayas and Azuay. Given the stratified design, sample frames containing a complete and updated list of establishments as well as information on all stratification variables (number of employees, industry, and region) are required to draw the sample. Great efforts were made to obtain the best source for these listings. 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.
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 the refusal to respond (-8) as a different option from don’t know (-9). b- Establishments with incomplete information are usually re-contacted in order to complete this information, whenever necessary. For this survey, there were zero non-responses for the sales variable, d2. Please, note that for this specific question, refusals were not separately identified from “Don’t know” responses.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; whenever this was done, strict rules were followed to ensure replacements were randomly selected within the same stratum. Further research is needed on survey non-response in the Enterprise Surveys regarding potential introduction of bias.The share of interviews per contacted establishments was 0.23 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 0.46.
Weighting: 
Three sets of assumptions on establishment eligibility are used to construct sample adjustments using the status code information. Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility. The resulting weights are included in the variable wstrict. 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. The resulting weights are included in the variable wmedian. Weak assumption: in addition to the establishments included in points a and b, all establishments for which it was not possible to contact or that refused the screening questionnaire are assumed eligible. This definition includes as eligible 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. Under the weak assumption only observed non-eligible units are excluded from universe projections. The resulting weights are included in the variable wweak.
Questionnaires: 
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. The end date of the last complete fiscal year is identified by variables a20y, a20m, and a20d, collecting information on respectively, year, month, and day. For questions pertaining to monetary amounts, the unit is the United States dollar.
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.
Time Periods: 
March, 2018

No Visualizations Available.

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) 2017, Ref. ECU_2017_ES_v01_M. Dataset downloaded from [URL] on [date].

The survey was conducted in Ecuador between March and October of 2017 as part of Enterprise Surveys project, an initiative of the World Bank. Data from 361 establishments was analyzed. The objective of the survey is to gain an understanding of what firms experience in the private sector. 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 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 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.

FieldValue
Modified Date
2018-03-07
Release Date
Identifier
b45cbbc1-3385-427f-8677-72d8e02bda96
License
License Not Specified
Contact Email
Rating: 
0
No votes yet
Acronym: 
ES 2017
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 the refusal to respond (-8) as a different option from don’t know (-9). b- Establishments with incomplete information are usually re-contacted in order to complete this information, whenever necessary. For this survey, there were zero non-responses for the sales variable, d2. Please, note that for this specific question, refusals were not separately identified from “Don’t know” responses.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; whenever this was done, strict rules were followed to ensure replacements were randomly selected within the same stratum. Further research is needed on survey non-response in the Enterprise Surveys regarding potential introduction of bias.The share of interviews per contacted establishments was 0.23 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 0.46.
Weighting: 
Three sets of assumptions on establishment eligibility are used to construct sample adjustments using the status code information. Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility. The resulting weights are included in the variable wstrict. 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. The resulting weights are included in the variable wmedian. Weak assumption: in addition to the establishments included in points a and b, all establishments for which it was not possible to contact or that refused the screening questionnaire are assumed eligible. This definition includes as eligible 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. Under the weak assumption only observed non-eligible units are excluded from universe projections. The resulting weights are included in the variable wweak.
Time Periods: 
March, 2018
Primary Investigator Name, Affiliation: 
World Bank
Funding Name, Abbreviation, Role: 
World Bank; Inter-American Development Bank
Version Description: 
v01, edited, anonymous dataset for public distribution
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.
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.
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 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.
Sampling Procedure: 
The sample for 2017 Ecuador ES was selected using stratified random sampling. 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). For the Ecuador 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 was done across three regions: Pichincha, Guayas and Azuay. Given the stratified design, sample frames containing a complete and updated list of establishments as well as information on all stratification variables (number of employees, industry, and region) are required to draw the sample. Great efforts were made to obtain the best source for these listings. 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.
Release Date: 
Thursday, February 15, 2018
Last Updated Date: 
Thursday, February 15, 2018
Questionnaires: 
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. The end date of the last complete fiscal year is identified by variables a20y, a20m, and a20d, collecting information on respectively, year, month, and day. For questions pertaining to monetary amounts, the unit is the United States dollar.
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 System ID: 
9698
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) 2017, Ref. ECU_2017_ES_v01_M. Dataset downloaded from [URL] on [date].
Modified date: 
17577
Study Type: 
Enterprise Survey
Primary Dataset: 
Yes

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