Enterprise Survey 2005-2009-2017, Panel Data
Niger, 2005 - 2017
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NER_2005-2017_ES-P_v01_M
Enterprise Survey 2005-2009-2017
Panel Data
| Name | Country code |
|---|---|
| Niger | NER |
Enterprise Survey [en/oth]
As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving business environments as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys are an ongoing World Bank project in collecting both objective data based on firms' experiences and enterprises' perception of the environment in which they operate.
An Enterprise Survey (ES) is a firm-level survey of a representative sample of an economy's private sector. Firm-level surveys have been conducted since 1998 by different units within the World Bank. Since 2005-2006, most data collection efforts have been centralized within the Enterprise Analysis Unit. The Enterprise Surveys are conducted across all geographic regions and cover small, medium, and large companies. The surveys are administered to a representative sample of firms in the non-agricultural formal private economy. Data is used to create indicators that benchmark the quality of the business and investment climate across countries.
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. Only registered businesses are surveyed in the Enterprise Survey.
Data from 151 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.
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.
Sample survey data [ssd]
The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.
Version
The Enterprise Surveys panel datasets have the following common format:
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Variable panel allows easy identification of panel observations
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Variable panelid is the same across the waves for the same firm
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Variable eligibility reports eligibility status of all firms interviewed in the previous wave as of the of the latest wave, e.g. in 2005-2017 panel, eligibility2017 reports status as of 2017 of all firms interviewed in 2005
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Wherever possible variables are matched across waves. If needed, matches are made by converting variable names in older waves to variable names in the most recent wave
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Due to methodological changes and evolution of the survey instrument it is not possible to match all variables in the datasets
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Variables that are not matched across waves are named as __, with the year in which the variable was collected (e.g. _2005_strata)
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It is recommended that users thoroughly familiarize themselves with the questionnaires from each of the years contained in the dataset before proceeding with analysis
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Some monetary unit variables in 2005 - 2017 surveys (in U.S. currency) are converted into the local currency units (LCU) using the market, period average, exchange rates. The sources of the exchange rates are the International Financial Statistics (IFS - IMF) websites
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Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
Scope
The scope of Enterprise Surveys includes:
- characteristics of an establishment;
- infrastructure and services;
- sales and supplies;
- degree of competition;
- capacity;
- land and permits;
- innovation;
- crime;
- finance;
- business-government relations;
- labor;
- business environment;
- performance
Coverage
National
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.
The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private 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. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.
Producers and sponsors
| Name |
|---|
| World Bank |
| Name |
|---|
| World Bank |
| The Department for International Development |
| Name | Role |
|---|---|
| TNS Opinion | Survey implementation in 2009 and 2016 |
| Research & Marketing Services (RMS) - Ltd. Nigeria | Survey implementation in 2009 |
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 as into manufacturing and services industries- Manufacturing (ISIC Rev. 3.1 codes 15 - 37), and Services (ISIC codes 45, 50-52, 55, 60-64, and 72).
For the 2009 sample stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. Size stratification was defined following the standardized definition used 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. Regional stratification was defined in terms of the geographic regions with the largest commercial presence in the country: Maradi and Niamey were the two areas selected in Niger.
Two frames were used for Niger. The first one included official lists from the Chamber of commerce, craft and industries of Niger 2008 and the Repertoire of Companies (2008) operating in Niger. The second frame (the panel sample) consisted of enterprises interviewed for the Enterprise Survey in 2005, which were to be re-interviewed where they were in the selected geographical regions and met eligibility criteria. Both database contained the following information:
-Name of the firm
-Contact details
-ISIC code
-Number of employees.
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 39.9% (134 out of 344 establishments). Breaking down by industry, the following numbers of establishments were surveyed: Manufacturing - 52, Services - 98.
For 2017: Regional stratification for the Niger ES was done across two regions: Niamey and Rest of the Country.
The sample frame consisted of listings of firms from three sources:
- the list of 150 firms from the Niger 2009 ES for panel firms
- firm data from La Caisse Nationale de Sécurité Sociale (CNSS) and a list of exporting firms by the Institut National des Statistiques (INS) for fresh firms (firms not covered in 2009).
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 18.6% (76 out of 409 establishments).
Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.
Item non-response was addressed by two strategies:
a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9).
b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.
Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.
For some units it was impossible to determine eligibility because the contact was not successfully completed. Consequently, different assumptions as to their eligibility result in different universe cells' adjustments and in different sampling weights. Three sets of assumptions were considered:
a- Strict assumption: eligible establishments are only those for which it was possible to directly determine eligibility.
b- Median assumption: eligible establishments are those for which it was possible to directly determine eligibility and those that rejected the screener questionnaire or an answering machine or fax was the only response. Median weights are used for computing indicators on the www.enterprisesurveys.org website.
c- Weak assumption: in addition to the establishments included in points a and b, all establishments for which it was not possible to finalize a contact are assumed eligible. This includes establishments with dead or out of service phone lines, establishments that never answered the phone, and establishments with incorrect addresses for which it was impossible to find a new address. Note that under the weak assumption only observed non-eligible units are excluded from universe projections.
Weights are representative of the universe for the year that the firm was interviewed. They are not panel weights.
Data collection
| Start | End |
|---|---|
| 2005 | 2017 |
| Name |
|---|
| Kantar Belguim SA |
| Plus Value Research |
Private contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and corruption-related topics, private contractors are preferred over any government agency or an organization/institution associated with government, and are hired by the World Bank to collect the data.
The Enterprise Surveys are usually implemented following a two-stage procedure. In the first stage, a screener questionnaire is applied over the phone to determine eligibility and to make appointments; in the second stage, a face-to-face interview takes place with the manager, owner or director of each establishment. In some cases, when the phone numbers were unavailable in the sample frame, the enumerators applied the screeners in person.
Data processing
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.
Access policy
Enterprise Surveys
https://www.enterprisesurveys.org/Portal/
Cost: None
Depositor information
| Name | Affiliation |
|---|---|
| Joshua Seth Wimpey | World Bank Group |
Data Access
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | Confidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised. |
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. Niger Enterprise Survey (ES-P) 2005-2017, Panel Data, Ref. NER_2005-2017_ES-P_v01_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
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
| Name | |
|---|---|
| Enterprise Analysis Unit | enterprisesurveys@worldbank.org |
Metadata production
DDI_NER_2005-2017_ES-P_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Data Group | World Bank | Documentation of the study |
2018-01-17
Metadata version
v01 (Jan 2018)