In 2023, the percentage of informal employment in Peru stood at 71.65 percent of the total employed population. This means that over two thirds of Peruvian workers were considered informally employed. Although this percentage decrease in comparison to the previous year, Peru is still one of the Latin American countries with the highest level of informal employment.

Abstract

The 2022 Peru Informal Sector Enterprise Survey was conducted by the World Bank Group's (WBG) Enterprise Analysis Unit (DECEA) in two cities in Peru. The survey covers the following cities: Lima and Trujillo. The fieldwork was implemented by Datum Internacional S.A., and the data was collected between June and September 2022.

The primary objectives of the Informal Sector Enterprise Surveys are to: i) understand demographics of the informal sector in the covered cities, ii) describe the environment within which these businesses operate, and iii) enable data analysis based on the samples that are representative at each city level.

Geographic coverage

Two cities in Peru: Lima and Trujillo.

Analysis unit

• Informal business

Universe

The ESIS cover all informal businesses within a well-defined geographic area, typically a city. All eligible businesses are considered as forming the universe of inference for the survey. Informality is defined as all businesses that are not legally registered with the government and, therefore, are excluded from taxation. The exact details of these criteria vary by country. For the 2022 ESIS in cities in Peru, a business is considered informal if it is not registered with SUNAT (Superintendencia Nacional de Aduanas y de Administración Tributaria). Thus, the universe of the survey includes all businesses that meet the above definition of informality, including all sectors of activity of any size. The universe excludes, however, any illicit or illegal activity.

Kind of data

Sample survey data [ssd]

Sampling procedure

A challenge to conducting a representative survey of informal sector businesses is the lack of a proper sampling frame since these businesses are not registered and, therefore, they are almost always absent from official registries or any other potential sampling frame. The ESIS follow an area-based sampling methodology. Each city is overlayed with a spatial grid, dividing the area into squares of equal size. In the case of the 2022 ESIS in cities in Peru these squares measured 150 meters by 150 meters. This spatial grid is prepared using a GIS software. Often, the boundaries of the city match a set of administrative boundaries.

Note: Detailed sampling methodology can be found on the Enterprise Surveys website under the Informal Businesses section, Methodology page (https://www.enterprisesurveys.org/en/informal-businesses/methodology).

Mode of data collection

Computer Assisted Personal Interview [capi]

Peru PE: Informal Employment: Female: % of Total Non-Agricultural Employment data was reported at 65.360 % in 2016. This records a decrease from the previous number of 66.900 % for 2015. Peru PE: Informal Employment: Female: % of Total Non-Agricultural Employment data is updated yearly, averaging 77.990 % from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 90.850 % in 2004 and a record low of 65.360 % in 2016. Peru PE: Informal Employment: Female: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

Peru PE: Informal Employment: % of Total Non-Agricultural Employment data was reported at 58.380 % in 2016. This records a decrease from the previous number of 60.110 % for 2015. Peru PE: Informal Employment: % of Total Non-Agricultural Employment data is updated yearly, averaging 69.850 % from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 87.050 % in 2004 and a record low of 58.380 % in 2016. Peru PE: Informal Employment: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

This research is a survey of unregistered businesses conducted in Peru from June 10 to July 20, 2010. Data from 480 enterprises were analyzed. Questionnaire topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. The mode of data collection is face-to-face interviews. The Informal Surveys aim to accomplish the following objectives: 1) To provide information about the state of the private sector for informal businesses in client countries; 2) To generate information about the reasons of said informality; 3) To collect useful data for the research agenda on informality; 4) To provide information on the level of activity in the informal sector of selected urban centers in each country.

Peru PE: Informal Employment: Male: % of Total Non-Agricultural Employment data was reported at 52.060 % in 2016. This records a decrease from the previous number of 53.980 % for 2015. Peru PE: Informal Employment: Male: % of Total Non-Agricultural Employment data is updated yearly, averaging 62.390 % from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 83.770 % in 2004 and a record low of 52.060 % in 2016. Peru PE: Informal Employment: Male: % of Total Non-Agricultural Employment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Employment and Unemployment. Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; ; Harmonized series

In 2022, informal employment in Ecuador constituted 68.5 percent of total employment in the country. In this year, the share of informally employed population increased by almost 5 percentage point in comparison to the percent in 2019. Informal employment is defined as work that is not formally registered or regulated by existing legal frameworks.

The informal sector in Ecuador

The COVID-19 pandemic has had a great impact on the Ecuadorian job market. It contributed to the raise of unemployment rates and worsening labor conditions, which pushed many workers towards the shadow economy sector. Although informal employment can be observed across the whole national territory, it is a particularly persistent problem in the countryside. In 2022, over 75 percent of the population in rural areas worked in the informal sector, nearly 40 percent more than in urban areas.

A common problem across Latin America

Economic growth and increasing level of education in Latin America do not seem to have a positive impact on the problem of informal employment. In almost every Latin American country, the share of the workforce employed in the informal sector exceeded half of the total working population in 2022. In Bolivia, the informal employment exceeded 80 percent. In economies such as Honduras, Guatemala, Peru, El Salvador, and Paraguay, more than two thirds of the employment force was working in the grey sector. Hindering tax revenues, data collection, or access to social benefits (such as unemployment payments or pensions) are only some of the challenges that both Latin American governments and residents have to face.

Peru Foreign Exchange Rate: Average: US Dollar: Informal: Ask data was reported at 3.333 PEN/USD in Oct 2018. This records an increase from the previous number of 3.316 PEN/USD for Sep 2018. Peru Foreign Exchange Rate: Average: US Dollar: Informal: Ask data is updated monthly, averaging 3.169 PEN/USD from Jan 1995 (Median) to Oct 2018, with 286 observations. The data reached an all-time high of 3.615 PEN/USD in Sep 2002 and a record low of 2.188 PEN/USD in Jan 1995. Peru Foreign Exchange Rate: Average: US Dollar: Informal: Ask data remains active status in CEIC and is reported by Central Reserve Bank of Peru. The data is categorized under Global Database’s Peru – Table PE.M009: Foreign Exchange Rate.

Peru Foreign Exchange Rate: Average: US Dollar: Informal: Bid data was reported at 3.332 PEN/USD in Oct 2018. This records an increase from the previous number of 3.313 PEN/USD for Sep 2018. Peru Foreign Exchange Rate: Average: US Dollar: Informal: Bid data is updated monthly, averaging 3.164 PEN/USD from Jan 1995 (Median) to Oct 2018, with 286 observations. The data reached an all-time high of 3.612 PEN/USD in Sep 2002 and a record low of 2.184 PEN/USD in Jan 1995. Peru Foreign Exchange Rate: Average: US Dollar: Informal: Bid data remains active status in CEIC and is reported by Central Reserve Bank of Peru. The data is categorized under Global Database’s Peru – Table PE.M009: Foreign Exchange Rate.

Abstract

The documented dataset covers Enterprise Survey (ES) panel data collected in Peru in 2006, 2010 and 2017, as part of the Enterprise Survey initiative of the World Bank. An Indicator Survey is similar to an Enterprise Survey; it 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 2006-2017 Enterprise Survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the Indicator Survey data provides information on the constraints to private sector growth and is used to create statistically significant business environment indicators that are comparable across countries.

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.

Geographic coverage

National

Analysis unit

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2006-2017 Peru Enterprise Survey (ES) was selected using stratified random sampling, following the methodology explained in the Sampling Manual. Stratified random sampling was preferred over simple random sampling for several reasons: - To obtain unbiased estimates for different subdivisions of the population with some known level of precision. - To obtain unbiased estimates for the whole population. The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors (group D), construction (group F), services (groups G and H), and transport, storage, and communications (group I). Groups are defined following ISIC revision 3.1. Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, excluding sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors. - To make sure that the final total sample includes establishments from all different sectors and that it is not concentrated in one or two of industries/sizes/regions. - To exploit the benefits of stratified sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e., lower standard errors, other things being equal.)

Three levels of stratification were used in every country: industry, establishment size, and region.

Industry stratification was designed in the following way: In small economies the population was stratified into 3 manufacturing industries, one services industry - retail-, and one residual sector as defined in the sampling manual. Each industry had a target of 120 interviews. In middle size economies the population was stratified into 4 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. For the manufacturing industries sample sizes were inflated by 25% to account for potential non-response in the financing data.

For the Peru ES, size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposed, the number of employees was defined on the basis of reported permanent full-time workers. This resulted in some difficulties in certain countries where seasonal/casual/part-time labor is common.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire.

The "Core Questionnaire" is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the "Core Questionnaire + Manufacturing Module" and the "Core Questionnaire + Retail Module." The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/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.

Cleaning operations

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.

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 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.

In 2023, nearly 64 percent of employees in the Brazilian construction industry were informally employed. Despite some fluctuations, the share of people working in construction with informal employment has stayed between 62 and 69 percent since 2009. Informal employment in construction was even more widespread in other Latin American countries, such as Peru, Mexico, Ecuador.

Building footprints in the form of polygons in three different informal settlements in Lima, Peru in geopackage layers. The locations of the settlements are Barrios Altos, El Agustino and José Carlos Mariátegui. The layer also contains semantic information with regards to the number of floors of the buildings and the thermal properties of the building envelope (lightweight, mediumweight, heavyweight) associated with the construction materials of the external walls and their thermal conductivity. The files can be uploaded to the freely accessible software QGIS (and other similar software packages) for editing and further use.

Abstract

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.

Geographic coverage

National Coverage

Analysis unit

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.

Kind of data

Sample survey data [ssd]

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.

Mode of data collection

Face-to-face [f2f]

Research instrument

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.

Cleaning operations

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.

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 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.

PE: Informal Payments to Public Officials: % of Firms data was reported at 13.600 % in 2017. This records a decrease from the previous number of 21.400 % for 2010. PE: Informal Payments to Public Officials: % of Firms data is updated yearly, averaging 13.600 % from Dec 2006 (Median) to 2017, with 3 observations. The data reached an all-time high of 21.400 % in 2010 and a record low of 11.500 % in 2006. PE: Informal Payments to Public Officials: % of Firms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Company Statistics. Informal payments to public officials are the percentage of firms expected to make informal payments to public officials to 'get things done' with regard to customs, taxes, licenses, regulations, services, and the like.; ; World Bank, Enterprise Surveys (http://www.enterprisesurveys.org/).; Unweighted average;

Abstract

This research was conducted in Peru between April and October 2006 as part of the Latin America and the Caribbean Enterprise Survey 2006 initiative. 632 businesses were surveyed.

The objective of the study is to obtain feedback from enterprises in client countries 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 face-to-face 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/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% 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.

Geographic coverage

National

Analysis unit

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The study was conducted using stratified random sampling. Three levels of stratification were used in the sample: firm sector, firm size, and geographic region.

Industry stratification was designed in the following way: the population was stratified into 3 manufacturing industries, one services industry - retail, and one residual sector. Each industry had a target of 120 interviews.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposed, the number of employees was defined on the basis of reported permanent full-time workers.

Regional stratification was defined the following way: Lima, Arequipa and Chiclayo.

The list of Top 10,000 Companies in Peru, which was updated in 2006 through studies conducted by a company DATUM International S.A., was the source of the sampling frame. The proportion of confirmed non-eligible units to the total number of contacts to complete the survey was 23%.

Additional information about sampling design can be found in "Sampling Report.xls", "Sampling Methodology" and "Latin America and the Caribbean Enterprise Survey 2006 Implementation Report" in "Technical documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire.

The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/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.

Cleaning operations

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.

Response rate

Information about response rates, survey and item non-response can be found in "Latin America and the Caribbean Enterprise Survey 2006 Implementation Report" in "Technical documents" folder.

This study investigates the impact of human capital on the integration of Venezuelan migrants in Peru, considering decent work as a crucial mediator. The research involved a sample of 1,193 Venezuelan adults residing in Lima and applied Partial Least Squares Structural Equation Modeling to examine the relationships among human capital, decent work, and integration. Findings reveal that human capital significantly enhances migrant integration, facilitating their participation in the labor market and contribution to the local economy. Decent work emerged as a key factor in promoting integration by providing economic stability and supporting social inclusion. However, Peru’s high level of labor informality restricts migrants’ access to formal and dignified employment, limiting the potential impact of decent work on integration. These results underscore the importance of policies aimed at labor formalization and the recognition of migrant skills, which could maximize migrants’ contributions and foster social cohesion. This study provides insights relevant for policymakers in Latin America, particularly in contexts with high labor informality, to develop effective strategies for the integration of migrant populations.

Abstract

This research was conducted in Peru between May 2010 and March 2011 as part of the Latin America and Caribbean (LAC) Enterprise Survey 2010, an initiative of the World Bank. Data from 1000 establishments was analyzed.

The objective of the study is to obtain feedback from enterprises in client countries 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 face-to-face 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/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% 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.

Geographic coverage

National

Analysis unit

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The study was conducted using stratified random sampling. Three levels of stratification were used in the sample: firm sector, firm size, and geographic region.

Industry stratification was designed in the way that follows: the universe was stratified into 5 manufacturing industries, 1 service industry -retail -, and 1 residual sector. Three manufacturing industries had targets of 160 interviews; one manufacturing industry (chemicals/rubbers & plastic) had a target of 147. The residual manufacturing, retail, and other services categories each had a target of 120 interviews.

Size stratification was defined following the standardized definition for the Enterprise 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. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in four locations (city and the surrounding business area): Lima, Arequipa, Chiclayo and Trujillo.

For Peru, two sample frames were used. The first was supplied by the World Bank and consists of enterprises interviewed in Peru 2006. The World Bank required that attempts should be made to re-interview establishments responding to the Peru 2006 survey where they were within the selected geographical locations and met eligibility criteria. That sample is referred to as the Panel. The second sample frame was obtained from National Institute of Statistics and Informatics (INEI) Economic Census 2007-2008.

The quality of the frame was assessed at the onset of the project through visits to a random subset of firms and local contractor knowledge. The sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc. In addition, the sample frame contains no telephone/fax numbers so the local contractor had to screen the contacts by visiting them. Due to response rate and ineligibility issues, additional sample had to be extracted by the World Bank in order to obtain enough eligible contacts and meet the sample targets.

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 5.58% (158 out of 2833 establishments).

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Peru Implementation" in "Technical documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module - Core Questionnaire + Retail Module - Core Questionnaire - Screener Questionnaire

The "Core Questionnaire" is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the "Core Questionnaire + Manufacturing Module" and the "Core Questionnaire + Retail Module." The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/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. The questionnaire also assesses the survey respondents' opinions on what are the obstacles to firm growth and performance.

Cleaning operations

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.

Response rate

The number of realized interviews per contacted establishment was 0.35. 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 number of rejections per contact was 0.25.

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Peru Implementation" in "Technical documents" folder.

This study investigates how self-organizing efforts by residents of informal settlements, primarily migrant and informal farmworkers, shape community resilience in Majes, a water-scarce irrigation district in the Atacama Desert of Peru. We collected 45 semi-structured interviews with residents and authorities in Majes and analyzed findings through a framework of self-organizing. Analyses revealed that self-organizing by residents of informal settlements incorporated the three components of White’s theory of Community Agency and Community Resilience, which contends that marginalized communities increase resilience by fostering a commons praxis, practicing a prefigurative politics, and developing opportunities for economic autonomy. We also found that residents self-organized into associations to increase access to resources, resulting in increased resilience. However, certain fees, corruption, and undemocratic decision-making processes can be detrimental to self-organizing. Results expand existing theories of self-organization and community resilience by highlighting how residents of informal settlements in agricultural spaces collectively organize to increase their resilience. Findings also begin to reframe narratives that describe migrants and farmworkers as powerless in the face of water scarcity, climate change, and other social-ecological risks.

Except for Peru, in all selected Latin American countries, informal employment was responsible for most of the employment recovery between the third quarter of 2020 and the third quarter of 2022. This was particularly noticeable in Paraguay and Argentina, informal employment contributed with 83 and 78 percent, respectively. According to the source, the fact that job recovery has been driven by growth in informal occupation in Latin America is due to the sharp fall in informal employment experienced during the most critical phase of the COVID-19 pandemic.

Reliability and Validity Measures for Measurement Model Constructs.