Enterprise Survey 2020
Denmark, 2020 - 2021
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Reference ID
DNK_2020_ES_v01_M
Producer(s)
The World Bank Group
Collection(s)
Metadata
Created on
Nov 17, 2021
Last modified
Nov 17, 2021
Page views
6303
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Identification
Survey ID Number
DNK_2020_ES_v01_M
Title
Enterprise Survey 2020
Country/Economy
| Name | Country code |
|---|---|
| Denmark | DNK |
Study type
Enterprise Survey [en/oth]
Series Information
As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving business environments as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys are an ongoing World Bank project in collecting both objective data based on firms' experiences and enterprises' perception of the environment in which they operate.
An Enterprise Survey (ES) 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 2005-2006, 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. Data are used to create indicators that benchmark the quality of the business and investment climate across countries.
The ES currently cover over 210,000 firms in 159 countries, of which 151 have been surveyed following the standard methodology. This allows for better comparisons across countries and across time. Data are used to create statistically significant business environment indicators that are comparable across countries. The ES are also used to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms.
An Enterprise Survey (ES) 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 2005-2006, 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. Data are used to create indicators that benchmark the quality of the business and investment climate across countries.
The ES currently cover over 210,000 firms in 159 countries, of which 151 have been surveyed following the standard methodology. This allows for better comparisons across countries and across time. Data are used to create statistically significant business environment indicators that are comparable across countries. The ES are also used to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms.
Abstract
The survey in Denmark was conducted between January 2020 and June 2021. The objective of the Enterprise Survey is to gain an understanding of what firms experience in the private sector.
As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving the business environment as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both objective data based on firms’ experiences and enterprises’ perception of the environment in which they operate.
As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving the business environment as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both objective data based on firms’ experiences and enterprises’ perception of the environment in which they operate.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
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.
Version
Version Description
v01, edited, anonymous dataset for public distribution
Scope
Notes
The Denmark 20202 Enterprise Survey covered the following topics:
- General information of the firm/ establishment
- Infrastructure and services
- Sales and supplies
- Management practices
- Degree of competition
- Innovation
- Capacity
- Land and permits
- Crime
- Finance
- Business-Government relations
- Labor
- Business environment
- Performance
- General information of the firm/ establishment
- Infrastructure and services
- Sales and supplies
- Management practices
- Degree of competition
- Innovation
- Capacity
- Land and permits
- Crime
- Finance
- Business-Government relations
- Labor
- Business environment
- Performance
Coverage
Geographic Coverage
National.
Geographic Unit
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.
Universe
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.
Producers and sponsors
Primary investigators
| Name |
|---|
| The World Bank Group |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| The World Bank Group | WBG |
Sampling
Sampling Procedure
The sample for 2020 Denmark ES was selected using stratified random sampling, following the methodology explained in the Sampling Note.
Three levels of stratification were used in this country: industry, establishment size, and region. The original sample design with specific information of the industries and regions chosen is described in Appendix C in the external resources.
Industry stratification was designed in the way that follows: the universe was stratified into seven manufacturing industries and two services industries- Food and Beverages (ISIC Rev. 4.0 code 10, 11), Rubber & Plastic Products (ISIC code 22), Non-Metallic Mineral Products (ISIC code 23), Fabricated Metal Products (ISIC code 25), Machinery and Equipment (ISIC code 28), Repair & Installation of Machinery & Equipment (ISIC code 33), Other Manufacturing (ISIC codes 12-21, 24, 27 and 29-32), Retail (ISIC code 47) and Other Services (ISIC codes 41-43, 45, 46, 49-53, 55, 56, 58, 61, 62, 79 and 95).
For the Denmark ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
Regional stratification for the Denmark ES was done across five regions: Hovedstaden, Sjælland, Syddanmark, Midtjylland, Nordjylland.
Three levels of stratification were used in this country: industry, establishment size, and region. The original sample design with specific information of the industries and regions chosen is described in Appendix C in the external resources.
Industry stratification was designed in the way that follows: the universe was stratified into seven manufacturing industries and two services industries- Food and Beverages (ISIC Rev. 4.0 code 10, 11), Rubber & Plastic Products (ISIC code 22), Non-Metallic Mineral Products (ISIC code 23), Fabricated Metal Products (ISIC code 25), Machinery and Equipment (ISIC code 28), Repair & Installation of Machinery & Equipment (ISIC code 33), Other Manufacturing (ISIC codes 12-21, 24, 27 and 29-32), Retail (ISIC code 47) and Other Services (ISIC codes 41-43, 45, 46, 49-53, 55, 56, 58, 61, 62, 79 and 95).
For the Denmark ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).
Regional stratification for the Denmark ES was done across five regions: Hovedstaden, Sjælland, Syddanmark, Midtjylland, Nordjylland.
Response Rate
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 the 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. However, there were clear cases of low response. The following graph shows non-response rates for the sales variable, d2, by sector. Please, note that for this specific question, refusals were not separately identified from “Don’t know” responses.
The number of interviews per contacted establishments was 0.19. 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 0.34.
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 (-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. However, there were clear cases of low response. The following graph shows non-response rates for the sales variable, d2, by sector. Please, note that for this specific question, refusals were not separately identified from “Don’t know” responses.
The number of interviews per contacted establishments was 0.19. 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 0.34.
Weighting
Since the sampling design was stratified and employed differential sampling, individual observations should be properly weighted when making inferences about the population. Under stratified random sampling, unweighted estimates are biased unless sample sizes are proportional to the size of each stratum. With stratification the probability of selection of each unit is, in general, not the same. Consequently, individual observations must be weighted by the inverse of their probability of selection (probability weights or pw in Stata.)
Special care was given to the correct computation of the weights. It was imperative to accurately adjust the totals within each region/industry/size stratum to account for the presence of ineligible units (the firm discontinued businesses or was unattainable, education or government establishments, no reply after having called in different days of the week and in different business hours, no tone in the phone line, answering machine, fax line6, wrong address or moved away and could not get the new references). The information required for the adjustment was collected in the first stage of the implementation: the screening process. Using this information, each stratum cell of the universe was scaled down by the observed proportion of ineligible units within the cell. Once an accurate estimate of the universe cell (projections) was available, weights were computed using the number of completed interviews.
Due to non-response rates, some stratification cells were collapsed for the purposes of weighting, to preserve the representativeness of the sample. The following cells have been transformed: (i) In Hovedstaden, medium and large firms are treated as one cell for Food, Rubber & Plastics Products, Fabricated Metal Products and Repair & Installation of Machinery & Equipment, (ii) In Sjælland, medium and large firms are treated as one cell for Machinery & Equipment and Retail; and small, medium and large firms are treated as one cell for Non-Metallic Mineral Products; (iii) In Syddanmark, small and medium firms are treated as one cell for other manufacturing; (iv) In Midtjylland, medium and large firms are treated as one cell for Repair & Installation of Machinery & Equipment and (iv) In Nordjylland, medium and large firms are treated as one cell for Rubber & Plastic Products.
Special care was given to the correct computation of the weights. It was imperative to accurately adjust the totals within each region/industry/size stratum to account for the presence of ineligible units (the firm discontinued businesses or was unattainable, education or government establishments, no reply after having called in different days of the week and in different business hours, no tone in the phone line, answering machine, fax line6, wrong address or moved away and could not get the new references). The information required for the adjustment was collected in the first stage of the implementation: the screening process. Using this information, each stratum cell of the universe was scaled down by the observed proportion of ineligible units within the cell. Once an accurate estimate of the universe cell (projections) was available, weights were computed using the number of completed interviews.
Due to non-response rates, some stratification cells were collapsed for the purposes of weighting, to preserve the representativeness of the sample. The following cells have been transformed: (i) In Hovedstaden, medium and large firms are treated as one cell for Food, Rubber & Plastics Products, Fabricated Metal Products and Repair & Installation of Machinery & Equipment, (ii) In Sjælland, medium and large firms are treated as one cell for Machinery & Equipment and Retail; and small, medium and large firms are treated as one cell for Non-Metallic Mineral Products; (iii) In Syddanmark, small and medium firms are treated as one cell for other manufacturing; (iv) In Midtjylland, medium and large firms are treated as one cell for Repair & Installation of Machinery & Equipment and (iv) In Nordjylland, medium and large firms are treated as one cell for Rubber & Plastic Products.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2020-01 | 2021-06 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collectors
| Name |
|---|
| Norstat Denmark |
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Enterprise Analysis Unit | The World Bank Group | enterprisesurveys@worldbank.org |
Confidentiality
Citation requirements
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)
Example:
The World Bank. Denmark - Enterprise Survey (ES) 2020, Ref. DNK_2020_ES_v01_M. Dataset downloaded from [URL] on [date].
- 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)
Example:
The World Bank. Denmark - Enterprise Survey (ES) 2020, Ref. DNK_2020_ES_v01_M. Dataset downloaded from [URL] on [date].
Access authority
| Name | Affiliation | |
|---|---|---|
| Enterprise Analysis Unit | World Bank Group | enterprisesurveys@worldbank.org |
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_DNK_2020_ES_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank Group | Documentation of the DDI |
Date of Metadata Production
2021-11-03
DDI Document version
Version 1 (November 2021)