ZWE_2011_ES_v01_M_WB
Enterprise Survey 2011
Name | Country code |
---|---|
Zimbabwe | ZWE |
Enterprise Survey [en/oth]
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 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 are used to create indicators that benchmark the quality of the business and investment climate across countries.
The survey was conducted in Zimbabwe between May 2011 and February 2012 as part of the Africa Enterprise Survey 2011, an initiative of the World Bank. Data from 599 establishments was analyzed.
The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. 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/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% 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 mode of data collection is face-to-face interviews.
Sample survey data [ssd]
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.
First version of the dataset.
The scope of the study includes:
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 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.
Name |
---|
World Bank |
Name | Role |
---|---|
TNS Opinion | Implementation of Africa 2011 Enterprise Surveys roll out |
Name |
---|
World Bank |
Department for International Development |
The sample for Zimbabwe was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.
Industry stratification was designed in the way that follows: the universe was stratified into one manufacturing industry, ne service industry -retail -, and one residual sector as defined in the sampling manual. The manufacturing industry, service industry, and residual sectors had a target each of 120 interviews.
Size stratification was defined following the standardized definition for the rollout: 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. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.
Regional stratification was defined in four regions (city and the surrounding business area): Bulwayo, Harare, Manicaland, Midlands.
The sample frame used for the survey in Zimbabwe was Zimbabwe Statistics (ZimStats). A copy of that frame was sent to the TNS statistical team in London to select the establishments for interview.
The enumerated establishments were then used as the frame for the selection of a sample with the aim of obtaining interviews at 600 establishments with five or more employees.
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. Due to response rate and ineligibility issues, additional sample had to be extracted by the World Bank in order to obtain enough eligible contacts and meet the sample targets.
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 11% (89 out of 840 establishments).
The number of contacted establishments per realized interview was 0.71. 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 0.17.
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 as a different option from don’t know (-7).
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.
The following survey instruments are available:
The standard 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% 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.
Start | End |
---|---|
2011-05 | 2012-02 |
Name |
---|
Probe Market Research |
Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Zimbabwe Implementation" in external resources.
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/Director of each establishment. All Enterprise Surveys are conducted in the local languages.
Zimbabwe experienced a hyperinflation period during 2008-2009. This situation affected the recall variable on sales (total annual sales in fiscal year 2008) but also recall variables on capacity utilization and labor.
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.
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. |
Aggregate indicators based on Enterprise Survey data are available to the public at https://www.enterprisesurveys.org
Firm-level data is also available to the public free-of-charge. In order to access the firm-level data, users must agree to abide by a strict confidentiality agreement available through Enterprise Analysis Unit website by clicking on "External users register here" at https://www.enterprisesurveys.org/Portal
The use of the datasets must be acknowledged using a citation which would include:
Example:
World Bank. Zimbabwe Enterprise Survey (ES) 2011, Ref. ZWE_2011_ES_v01_M_WB. 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.
Name | Affiliation | |
---|---|---|
Enterprise Analysis Unit | World Bank | enterprisesurveys@worldbank.org |
DDI_ZWE_2011_ES_v01_M_WB
Name | Affiliation | Role |
---|---|---|
Antonina Redko | Data Development Group (DECDG) | Documentation of the survey micro- and metadata information in DDI format |
2012-05-08
First version of metadata and external resources description.