Small and Medium Enterprises Survey 2016
Kenya, 2016
Get MicrodataIdentification
KEN_2016_MSME_v01_M
Small and Medium Enterprises Survey 2016
| Name | Country code |
|---|---|
| Kenya | KEN |
Enterprise Census [en/census]
The MSME sector in Kenya has over the years been recognized for its role in provision of goods and services, enhancing competition, fostering innovation, generating employment and in effect, alleviation of poverty. The crucial role of MSMEs is underscored in Kenya's Vision 2030 - the development blueprint which seeks to transform Kenya into an industrialized middle-income country, providing a high-quality life to all its citizens by the year 2030. The MSME sector has been identified and prioritized as a key growth driver for achievement of the development blue print.
The measurement of the size of the sector in terms of employment as well as its contribution to Gross Domestic Product [GDP] and the generation of income is of major importance. This is not only because of their usefulness in the design of appropriate policies and programs but also in understanding their dynamics in terms of income, wages, growth patterns, sector and their evolving nature among others. MSMEs tend to be dynamic: the structure and their operations change considerably within a short time. The last comprehensive study is the 1999 National Micro and Small Enterprise (MSE) Baseline Survey. The 2016 National MSME Survey was therefore, designed to respond to the existing data gap and sought to provide data at national and county levels. The unit of observation was the establishments and the survey targeted those that engaged at most 99 persons. The terms establishment, enterprise and business are however, used interchangeably in this report.
Census/enumeration data [cen]
i) National
ii) Counties
iii) Urban and rural residence
Version
2016-06-27
Version 02 is the reviewed version produced by Development Data Group (The World Bank) based on Version 1. DDI-KEN-KNBS-MSME-2016-v1.0 done by Kenya National Bureau of Statistics. The following metadata fields were edited or updated. Citation requirement, disclaimer. Edited DDI ID number, ID number and title.
Scope
The Micro, Small and Medium Enterprises (MSMEs) are considered as sources of employment generation, economic growth, and social transformation. A significant proportion of the MSMEs are formal, while majority fall within the informal economy based on their size, location, ownership, status of formality and economic activity, together, as major job providers, they produce a significant share of total value added, and provide a large segment of the poor and middle-income populations with affordable goods and services. There is however limited or outdated data to inform MSME policy formulation and implementation.
Coverage
i) National
ii) Counties
iii) Urban and rural residence
Producers and sponsors
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics | Ministry of Planning and National development |
| Name | Role |
|---|---|
| Kenya National Bureau of Statistics | Funding of Operational Cost |
Sampling
Survey Design
The previous MSE studies used the household-based approach to identify businesses/establishments. However, the 2016 MSME survey, in addition to the household-based approach, interviewed businesses/establishments identified from business registers maintained by county governments. The 2016 MSME survey was cross-sectional and was designed to provide estimates at national and county levels. The survey used a representative probability sample design aimed at producing estimates at the following domains;
· National
· Counties and
· Urban and rural residence (For Unlicensed businesses only.
The survey adopted a stratified random sampling method for the establishment-based sample in which a systematic random sample of establishments was drawn using equal probability selection method. For the household-based sample, a two-stage stratified cluster sampling design was used where the first stage involved selection of 600 clusters (354 in rural and 246 in urban) with equal probability. In the second stage, a uniform random sample of 24 households in each cluster was selected using systematic random sampling method.
Data Weighting
Weighting of the data was necessary since the selected samples were not self-weighting due to varying probabilities of selection across different strata. Separate weights were, therefore, computed for the various sets of data. The design weights for the licensed establishments incorporated the probabilities of selection of the establishments from the establishments sampling frame. The weights were further adjusted to cater for nonresponses.
Household weights were used for the unlicensed establishments as the latter were operating from the household. These weights incorporated the probabilities of selection of the clusters from the census EAs database into the NASSEP V sampling frame, the probabilities of selection of the MSME clusters from the frame and the probabilities of selection of the households from each of the sampled clusters. These weights were then adjusted to cater for household and individual non-response.
Survey instrument
One Enterprise Questionnaire
Data collection
| Start | End |
|---|---|
| 2016-03-15 | 2016-06-15 |
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics | Ministry of Planning and National Development |
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| Kenya National Bureau of Statistics | Ministry of Planning and National Development | www.knbs.go.ke | director@knbs.go.ke |
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | Before being granted access to the dataset, all users have to formally agree: 1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor. 2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. 3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor. |
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
Kenya National Bureau of Statistics. Small and Medium Enterprises Survey (MSME) 2016. Ref. KEN_2016_MSME_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.
Copyright 2016, Kenya National Bureau of Statistics
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Director General | KNBS | directorgeneral@knbs.go.ke | www.knbs.go.ke |