The survey was conducted in Ghana between December 2012 and July 2014 as part of the Africa Enterprise Survey 2013 roll-out, an initiative of the World Bank. 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.
Data from 720 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.
Kind of data
Sample survey data [ssd]
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. 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.
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
The sample for Ghana was selected using stratified random sampling. Three levels of stratification were used in this country: firm sector, firm size, and geographic region.
Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).
Size stratification was defined following the standardized definition for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).
Regional stratification for the Ghana ES was defined in four regions: Accra, North (Kumasi and Tamale), Takoradi, and Tema.
For the Ghana ES, several sample frames were used. The first was supplied by the World Bank and consists of enterprises interviewed in Ghana 2007. The World Bank required that attempts should be made to re-interview establishments responding to the Ghana 2007 survey where they were within the selected geographical regions and met eligibility criteria. Due to the fact that the previous round of surveys seemed to have utilized different stratification criteria (or no stratification at all) and due to the prevalence of small firms and firms located in the capital city in the 2007 sample the following convention was used. The presence of panel firms was limited to a maximum of 50% of the achieved interviews in each cell. That sample is referred to as the Panel.
The second frame was constructed using different lists acquired from relevant institutions in Ghana.
The main lists used were obtained from the Ghana Statistical Service (GSS). These include:
1) The 2012 Firm Registry. The registry lacked information on firm employee size.
2) The list of firms paying VAT. The VAT dataset included a variable on firms; turnover. The VAT dataset and Firm Registry were merged by using the firms' identification number (TIN). VAT information was not available for all firms in the Firm Registry.
3) The list of Large Tax Payers. The Large Tax Payers file also lacked information on firm employee size.
Since firm size was missing from all lists mentioned above, after having discussed with GSS and with the local contractor the following methods were used to predict firm size.
- All firms who were in the Firm Registry but not in the VAT dataset were considered to be micro firms and therefore not use in the current survey.
- Firms who were in the Firm Registry and in the VAT dataset were considered to be small firms.
- Firms in the Large Tax Payers dataset were considered medium or large firms. The original design was divided into two size groups: small firms and medium and large firms.
During fieldwork the GSS lists proved to be very inaccurate and not sufficient to reach the target sample design, As such they were complemented with additional lists of firms from the Ghana Chamber of Commerce and Industry and Business Associations. The list from the Ghana Chamber of Commerce lacked information on firm employee size or firm turnover. 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 1.3% (26 out of 1,990 establishments).
Finally, a block enumeration was also undertaken in order to build an additional list. The block enumeration allowed to physically creating a list of establishments from which to sample from. A total of 41 blocks were enumerated in the four locations included in the project out of the total 804 blocks identified. The enumeration was conducted without major problems in the time planned. The list of enumerated firms contained 958 records eligible for main Enterprise Survey.
Note: Unlike the standard ES, the universe for the Ghana ES is characterized by the presence of 5 size categories. The category medium&large was added as stratum in order to sample from the GSS large payers list, while the category "unknow size" was included in order to sample the firms in the Chamber of Commerce and Industry list.
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.
The number of interviews per contacted establishments was 0.16. 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 0.12.
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
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.
TNS RMS Ghana
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. Ghana Enterprise Survey (ES) 2013, Ref. GHA_2013_ES_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.