Enterprise Survey 2016
Honduras, 2016 - 2017
World Bank
Identification
IDNO
HND_2016_ES_v01_M
Title
Enterprise Survey 2016
Countries
| Name | Code |
|---|---|
| Honduras | HND |
Study notes
The survey was conducted in Honduras between July 2016 and September 2017 as part of Enterprise Surveys project, an initiative of the World Bank. Data from 332 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.
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.
Kind of data
Sample survey data [ssd]
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.
Version
Version
v01, edited, anonymous dataset for public distribution
Coverage
Geographic coverage
National Coverage
Geographic unit
Regions covered are selected based on the number of establishments, contribution to employment, and value added. In most cases these regions are metropolitan areas and reflect the largest centers of economic activity in a country.
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.
Producers and sponsors
Authoring entity
| Name |
|---|
| World Bank |
Funding agencies
| Name |
|---|
| World Bank |
Sampling
Sampling procedure
The sample for 2016 Honduras 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 Honduras 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 for the Honduras ES was done across three regions: Tegucigalpa, San Pedro Sula and Rest of the Country.
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: The panel firms list of 360 firms from the Honduras 2010 ES was used. For fresh firms (i.e., firms not covered in 2010), firm data from Servicio de Administración de Rentas, SAR was used.
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 Honduras 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 for the Honduras ES was done across three regions: Tegucigalpa, San Pedro Sula and Rest of the Country.
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: The panel firms list of 360 firms from the Honduras 2010 ES was used. For fresh firms (i.e., firms not covered in 2010), firm data from Servicio de Administración de Rentas, SAR was used.
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. 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 rejections per contact was 0.21.
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. 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 rejections per contact was 0.21.
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.
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.
Data Collection
Dates of collection
| Start | End |
|---|---|
| 2016-07 | 2017-09 |
Mode of data collection
Face-to-face [f2f]
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 last complete fiscal year is January to December 2015. For questions pertaining to monetary amounts, the unit is the Honduran Lempira.
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 last complete fiscal year is January to December 2015. For questions pertaining to monetary amounts, the unit is the Honduran Lempira.
Data Processing
Data editing
Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.
Data access
Citation requirements
The use of this dataset must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online).
Example:
The World Bank. Honduras - Enterprise Survey (ES) 2016, Ref. HND_2016_ES_v01_M. Dataset downloaded from [URL] on [date].
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online).
Example:
The World Bank. Honduras - Enterprise Survey (ES) 2016, Ref. HND_2016_ES_v01_M. Dataset downloaded from [URL] on [date].
Original archive where collection stored
Enterprise Surveys
https://www.enterprisesurveys.org/Portal/
Cost: None
https://www.enterprisesurveys.org/Portal/
Cost: None
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
Contact(s)
| Name | |
|---|---|
| Enterprise Analysis Unit | enterprisesurveys@worldbank.org |
Metadata production
IDNo
DDI_HND_2016_ES_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | DDI documentation |
Production date
2018-02-06
Version
Version 01 (February 2018)