Tanzania Enterprise Skills Survey was conducted between April and August 2015 by the Enterprise Analysis Unit (DECEA) and the Education Global Practice (GEDDR) of the World Bank Group.
The objective of the survey is to develop and test a methodological approach for a diagnostic of the composition and demand for skills and the relationship between skills (and/or skills constraints) and firm performance of selected economic sectors in Tanzania. A detailed skills module was developed as part of a larger firm-level Enterprise Survey, collecting information, among others, on the characteristics of firms and their owners, innovation and export activities, and firm performance.
The sample for the survey was selected using stratified random sampling, following a broadly similar methodology used in the World Bank's Enterprise Surveys.
Kind of data
Sample survey data [ssd]
v01, edited, anonymous dataset for public distribution
All variables are named using, first, the letter of each section and, second, the number of the variable within the section, i.e. a1 denotes section A, question 1 (some exceptions apply). All variables are numeric with the exception of those variables with an "x" at the end of their names. The suffix "x" denotes that the variable is alpha-numeric.
There is a unique establishment identifiers, variable name id. The variables a2 (sampling region), a6a (sampling establishment's size), and a4a (sampling sector) contain the establishment's classification into the strata chosen for each country using information from the sample frame.
Note that the fiscal years vary by firm as there is no standard for all firms in Tanzania. The start and end dates for the fiscal year for each firm can be found in the fymonb, fyyearb, fymone and fyyeare variables in the dataset.
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 an establishment. The 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.
Firms in eight selected economic activities: food processing (ISIC15), textile and garments (ISIC 17 & 18), fabricated metal products (ISIC 28), furniture (ISIC 36), construction (ISIC 45), hotel and restaurant (ISIC 55), transport (ISIC 60 & 61) and Information technology (ISIC 72)).
Producers and sponsors
The sample was selected using stratified random sampling.
Three levels of stratification were used for this survey: economic activity, establishment size, and region:
1) Eight economic activities - food processing (ISIC15), textile and garments (ISIC 17 & 18), fabricated metal products (ISIC 28), furniture (ISIC 36), construction (ISIC 45), hotel and restaurant (ISIC 55), transport (ISIC 60 & 61) and information technology (ISIC 72);
2) Three sizes - small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees);
3) Five regions (city and the surrounding business area): Arusha, Dar es Salaam, Mbeya, Mwanza, and Zanzibar.
Two sample frames were used:
1) The first frame was the 2011/2012 Central Registry of Establishment (CRE) of the National Bureau of Statistics (NBS);
2) The second frame was 2012 Central Registry of Establishment (CRE) of the Office of Chief Government Statistician (OCGS). The sample frame was used for the establishments in Zanzibar.
The enumerated establishments with 5 employees or more were then used as the sample frame for the 2015 Tanzania Skills Survey with the aim of obtaining interviews of 390 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.
Item non-response was addressed by re-contacting firms. That is, establishments with incomplete information were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response. The response rates are particularly low for questions about the names and locations of the main universities and schools attended by the establishment's recent hires (questions l13, l14, l15 and l25 in the questionnaire). Despite repeated callbacks, respondents note that they just do not know the names and locations of schools attended by their employees.
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.
The number of realized interviews per contact contacted establishments was 0.28. 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 0.07.
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.
Dates of collection
Mode of data collection
Computer Assisted Personal Interview [capi]
The data was collected using a standardized questionnaire administered to all firms. The questionnaire has eight sections: six main sections and two sections on control information.
DataVision International Ltd.
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.
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)
The World Bank. Tanzania Enterprise Skills Survey (ESS) 2015, Ref. TZA_2015_ESS_v01_M. Dataset downloaded from [URL] on [date].
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.