Peru - Enterprise Survey 2017

Primary tabs

The survey was conducted in Peru between March 2017 to March 2018 as part of Enterprise Surveys project, an initiative of the World Bank. Data from 1003 establishments was analyzed. The objective of the Enterprise 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.

Acronym: 
ES 2017
Type: 
Microdata
Topics: 
Topic not specified
Languages Supported: 
English
Geographical Coverage: 
Peru
Reference ID: 
PER_2017_ES_v01_M
Release Date: 
November 27, 2018

Harvest Source

Harvest Source: 
Microdata

Harvest Source ID

Harvest Source ID: 
10273

Last Updated

Last Updated: 
November 27, 2018
Study Type: 

Enterprise Survey

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.
Primary Investigator Name, Affiliation: 
World Bank
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 Peruvian Sol, PEN.
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 were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response. The following graph shows non-response rates for the sales variable, d2, by sector. 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.
Sampling Procedure: 
The sample for 2017 Peru 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 three manufacturing industries and two services industries- Food and Beverages (ISIC Rev. 3.1 code 15), Textiles and Garments (ISIC codes 17,18), Other Manufacturing (ISIC codes 16, 19-37), Retail (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 55, 60-64, and 72). For the Peru 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 five regions: Lima, Arequipa, Chiclayo, Trujillo and Piura. 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 several sources. For panel firms the list of 1000 firms from the Peru 2010 ES was used, and for fresh firms (i.e., firms not covered in 2010) the lists obtained from Top 10mil 2011, Registro Mype Callao 2010, Registro Mype 2012 and SUNAT (Hacienda) 2011 were used.
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 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. 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 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
Weighting: 
Since the sampling design was stratified and employed differential sampling, individual observations should be properly weighted when making inferences about the population. Under stratified random sampling, unweighted estimates are biased unless sample sizes are proportional to the size of each stratum. With stratification, the probability of selection of each unit is, in general, not the same. Consequently, individual observations must be weighted by the inverse of their probability of selection (probability weights or pw in Stata.) Special care was given to the correct computation of the weights. It was imperative to accurately adjust the totals within each region/industry/size stratum to account for the presence of ineligible units (the firm discontinued businesses or was unattainable, education or government establishments, no reply after having called in different days of the week and in different business hours, no tone in the phone line, answering machine, fax line, wrong address or moved away and could not get the new references). The information required for the adjustment was collected in the first stage of the implementation: the screening process. Using this information, each stratum cell of the universe was scaled down by the observed proportion of ineligible units within the cell. Once an accurate estimate of the universe cell (projections) was available, weights were computed using the number of completed interviews.

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. Peru- Enterprise Survey (ES) 2017, Ref. PER_2017_ES_v01_M. Dataset downloaded from [URL] on [date].

The survey was conducted in Peru between March 2017 to March 2018 as part of Enterprise Surveys project, an initiative of the World Bank. Data from 1003 establishments was analyzed. The objective of the Enterprise 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
2019-01-17
Release Date
Identifier
e9d9e5a5-1673-4aed-bbc5-47b1a08f4bb5
License
License Not Specified
Contact Email
Public Access Level
Public
Rating: 
0
No votes yet
Reference ID: 
PER_2017_ES_v01_M
Acronym: 
ES 2017
Type: 
Languages Supported: 
Access Authority Name, Affiliation, Email: 
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 were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response. The following graph shows non-response rates for the sales variable, d2, by sector. 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.
Weighting: 
Since the sampling design was stratified and employed differential sampling, individual observations should be properly weighted when making inferences about the population. Under stratified random sampling, unweighted estimates are biased unless sample sizes are proportional to the size of each stratum. With stratification, the probability of selection of each unit is, in general, not the same. Consequently, individual observations must be weighted by the inverse of their probability of selection (probability weights or pw in Stata.) Special care was given to the correct computation of the weights. It was imperative to accurately adjust the totals within each region/industry/size stratum to account for the presence of ineligible units (the firm discontinued businesses or was unattainable, education or government establishments, no reply after having called in different days of the week and in different business hours, no tone in the phone line, answering machine, fax line, wrong address or moved away and could not get the new references). The information required for the adjustment was collected in the first stage of the implementation: the screening process. Using this information, each stratum cell of the universe was scaled down by the observed proportion of ineligible units within the cell. Once an accurate estimate of the universe cell (projections) was available, weights were computed using the number of completed interviews.
Primary Investigator Name, Affiliation: 
World 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 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 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. 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 Peru 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 three manufacturing industries and two services industries- Food and Beverages (ISIC Rev. 3.1 code 15), Textiles and Garments (ISIC codes 17,18), Other Manufacturing (ISIC codes 16, 19-37), Retail (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 55, 60-64, and 72). For the Peru 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 five regions: Lima, Arequipa, Chiclayo, Trujillo and Piura. 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 several sources. For panel firms the list of 1000 firms from the Peru 2010 ES was used, and for fresh firms (i.e., firms not covered in 2010) the lists obtained from Top 10mil 2011, Registro Mype Callao 2010, Registro Mype 2012 and SUNAT (Hacienda) 2011 were used.
Release Date: 
Tuesday, November 27, 2018
Last Updated Date: 
Tuesday, November 27, 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 Peruvian Sol, PEN.
Harvest Source: 
Harvest Source ID: 
10273
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. Peru- Enterprise Survey (ES) 2017, Ref. PER_2017_ES_v01_M. Dataset downloaded from [URL] on [date].
Modified date: 
17862
Study Type: 
Enterprise Survey
Primary Dataset: 
Yes

Data Access and Licensing

This dataset is classified as Public under the Access to Information Classification Policy. Users inside and outside the Bank can access this dataset.

This dataset is available from an external third-party website. Visit the website to obtain license information. More information

Share Metadata

The information on this page (the dataset metadata) is also available in these formats.

PRINT EMAIL JSON RDF