Micro-Enterprise Survey 2013
Kenya, 2013 - 2014
World Bank
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April 04, 2014
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April 04, 2014
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Identification
Survey ID Number
KEN_2013_MS_v01_M
Title
Micro-Enterprise Survey 2013
Country
| Name | Country code |
|---|---|
| Kenya | KEN |
Study type
Enterprise Survey [en/oth]
Series Information
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 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. The Enterprise Surveys are conducted every three to four years across all geographic regions and cover small, medium, and large companies. Data are used to create indicators that benchmark the quality of the business and investment climate across countries.
In some countries, unregistered businesses and firms with a small number of employees make up a large part of the economy. Micro-Enterprise Surveys target registered establishments with one to four employees, while traditional Enterprise Surveys focus on businesses with five or more workers. Sampling techniques and questionnaires are the same for Micro-Enterprise and Enterprise Surveys.
In some countries, unregistered businesses and firms with a small number of employees make up a large part of the economy. Micro-Enterprise Surveys target registered establishments with one to four employees, while traditional Enterprise Surveys focus on businesses with five or more workers. Sampling techniques and questionnaires are the same for Micro-Enterprise and Enterprise Surveys.
Abstract
This research of registered businesses with one to four employees was conducted in Kenya between April 2013 and January 2014, at the same time with Kenya Enterprise Survey 2013. Data from 360 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The objective of the survey was to obtain feedback from enterprises on the state of the private sector and constraints to its growth.
Micro-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 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.
Micro-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 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 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
Version Description
v01
Scope
Notes
The scope of the study includes:
- characteristics of establishments;
- infrastructure and services;
- sales and supplies;
- degree of competition;
- capacity;
- land and permits;
- innovation;
- crime;
- finance;
- business-government relations;
- labor;
- business environment;
- performance.
- characteristics of establishments;
- infrastructure and services;
- sales and supplies;
- degree of competition;
- capacity;
- land and permits;
- innovation;
- crime;
- finance;
- business-government relations;
- labor;
- business environment;
- performance.
Coverage
Geographic Coverage
Central, Nyanza, Mombasa, Nairobi, and Nakuru regions
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.
Universe
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
Primary investigators
| Name |
|---|
| World Bank |
Funding Agency/Sponsor
| Name |
|---|
| World Bank |
Other Identifications/Acknowledgments
| Name | Role |
|---|---|
| TNS Opinion | Implementation of the Africa 2013 Enterprise Surveys rollout |
Sampling
Sampling Procedure
The sample for Ethiopia was selected using stratified random sampling. Two levels of stratification were used: firm sector and geographic region.
For industry stratification, the universe was divided into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).
Regional stratification was defined in five regions: Central, Nyanza, Mombasa, Nairobi, and Nakuru.
2012 Census of Business Establishments of the Kenya National Bureau of Statistics was used as a sample frame for the survey of micro firms.
The enumerated establishments with less than five employees (micro establishments) were used as sample frame for the Kenya micro survey with the aim of obtaining interviews at 360 establishments.
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.
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 5.2% (39 out of 756) for micro firms.
For industry stratification, the universe was divided into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).
Regional stratification was defined in five regions: Central, Nyanza, Mombasa, Nairobi, and Nakuru.
2012 Census of Business Establishments of the Kenya National Bureau of Statistics was used as a sample frame for the survey of micro firms.
The enumerated establishments with less than five employees (micro establishments) were used as sample frame for the Kenya micro survey with the aim of obtaining interviews at 360 establishments.
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.
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 5.2% (39 out of 756) for micro firms.
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 "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.
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.
Weighting
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.
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.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2013-04 | 2014-01 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Kenya ES 2013 Implementation."
Data Collection Notes
Private contractors conduct Micro-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 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. However, the phone numbers were unavailable in the sample frame, and thus the enumerators applied the screeners in person.
Micro-Enterprise Surveys are conducted in local languages.
The 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. However, the phone numbers were unavailable in the sample frame, and thus the enumerators applied the screeners in person.
Micro-Enterprise Surveys are conducted in local languages.
Data Collectors
| Name |
|---|
| TNS RMS East Africa Limited |
Questionnaires
Questionnaires
The following survey instruments are available:
- Manufacturing Module Questionnaire
- Services Module Questionnaire
The survey is fielded via manufacturing or services questionnaires in order not to 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.
There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.
- Manufacturing Module Questionnaire
- Services Module Questionnaire
The survey is fielded via manufacturing or services questionnaires in order not to 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.
There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.
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.
Access policy
Contacts
| enterprisesurveys@worldbank.org |
Confidentiality
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.
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. Kenya Micro-Enterprise Survey (MS) 2013, Ref. KEN_2013_MS_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. Kenya Micro-Enterprise Survey (MS) 2013, Ref. KEN_2013_MS_v01_M. Dataset downloaded from [URL] on [date].
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.
Metadata production
DDI Document ID
DDI_KEN_2013_MS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | DDI Documentation |
Date of Metadata Production
2014-04-02
DDI Document version
v01 (April 2014)