The Turkey Regional Enterprise Survey (RES) was conducted between August 2015 and June 2016. The objective of the survey was to gain an understanding of what Turkish firms experience in the private sector.
The RES builds from the methodology developed for the standard Enterprise Survey of the World Bank and creates a baseline dataset with full geographical coverage of the private sector in Turkey, in the period 2015-2016. Data is used to create statistically significant business environment indicators that are comparable across all regions (NUTS 2) of the country.
Data from 6,006 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses.
The survey topics include firm characteristics, information about sales and suppliers, competition, infrastructure services, judiciary and law enforcement collaboration, security, government policies, laws and regulations, financing, overall business environment, bribery, capacity utilization, performance and investment activities, and workforce composition.
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 due to comparability reasons). Variable names preceded by the prefix "TU" indicate questions specific to the Turkey RES, therefore, they may not be found in the implementation of Enterprise Surveys in other countries. All other suffixed variables are global and are present in all Enterprise Surveys of the World Bank. 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.
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 universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of NACE Revision 2.0: (group C), construction sector (group F), services sector (groups G and I), and transport, storage, and communications sector (group H and J). Note that this definition excludes the following sectors: financial intermediation (group K), real estate and renting activities (group L) and all public or utilities-sectors.
Producers and sponsors
Stratified random sampling method was used to select the sample.
Three levels of stratification were used: industry, establishment size, and region.
Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries and four services industries- Food (NACE 2.0 codes 10), Textiles and Wearing apparel (NACE codes 13 and 14), Fabricated Metal, Machinery and Motor Vehicles (NACE codes 25, 28, 29), Other Manufacturing (NACE codes 11, 12, 15-24, 26, 27, 30-32), Construction (NACE codes 41, 42, 43) Wholesale and Retail (45, 46, 47), Transport (49, 50-53) and Other Services (NACE codes 33, 55, 56, 58, 61, 62, 79, and 95).
Siize stratification was defined as follows: micro (less than 5 employees), small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
Regional stratification was done including eighty-one NUTS 3 regions: Istanbul, Tekirdag , Edirne, Kirklareli, Balikesir, Çanakkale, Izmir, Aydin, Denizli, Mugla, Manisa, Afyonkarahisar, Kütahya, Usak, Bursa, Eskisehir, Bilecik, Kocaeli, Sakarya, Düzce, Bolu, Yalova, Ankara, Konya, Karaman, Antalya, Isparta, Burdur, Adana, Mersin, Hatay, Kahramanmaras, Osmaniye, Kirikkale, Aksaray, Nigde, Nevsehir, Kirsehir, Kayseri, Sivas, Yozgat, Zonguldak, Karabük, Bartin, Kastamonu, Çankiri, Sinop, Samsun, Tokat, Çorum, Amasya, Trabzon, Ordu, Giresun, Rize, Artvin, Gümüshane, Erzurum, Erzincan, Bayburt, Agri, Kars, Igdir, Ardahan, Malatya, Elazig, Bingöl, Tunceli, Van, Mus, Bitlis, Hakkâri, Gaziantep, Adiyaman, Kilis, Sanliurfa, Diyarbakir, Mardin, Batman, Sirnak, and Siirt. However, for precision purposes, the minimum number of observations required for a minimum level of precision of 7.5% of estimates of proportions with a 95% confidence interval was guaranteed for these regions grouped into 26 NUTS 2 regions: TR10, TR21, TR22, TR31, TR32, TR33, TR41, TR42, TR51, TR52, TR61, R62, TR63, TR71, TR72, TR81, TR82, TR83, TR90, TRA1, TRA2, TRB1, TRB2, TRC1, TRC2, TRC3.
The sample frame consisted of a listing of firms from the Turkish Statistical Institute (TUIK). The quality of the frame was enhanced by the verification process conducted by the three contractors. However, the sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc.
Given the impact that non-eligible units included in the sample universe may have on the results, adjustments are 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 3.8% (1,646 out of 43,421 establishments).
Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether, while 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 the refusal to respond as a different option from don’t know.
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 contacted establishments per realized interview was 0.14. 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 share 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
Three different versions of the questionnaire were used. The basic questionnaire, the Core Module, includes all common questions asked to all establishments from all sectors. The second expanded variation, the Manufacturing Questionnaire, is built upon the Core Module and adds some specific questions relevant to manufacturing sectors. The third expanded variation, the Retail Questionnaire, is also built upon the Core Module and adds to the core specific questions.
All firms had January 2014 to December 2014 as their last complete fiscal year. For questions pertaining to monetary amounts, the unit is the New Turkish Lira.
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 the datasets 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).
World Bank. Turkey Regional Enterprise Survey (RES) 2015, Ref. TUR_2015_RES_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.