Enterprise Survey 2019
Lebanon, 2019 - 2020
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LBN_2019_ES_v01_M
Enterprise Survey 2019
| Name | Country code |
|---|---|
| Lebanon | LBN |
Enterprise Survey [en/oth]
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 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit (FPDEA). 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 195,000 firms in 152 countries, of which 144 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.
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.
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.
Version
v01, edited, anonymous dataset for public distribution
Scope
The Lebanon 2019 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
- Time use of top manager
- Land and permits
- Crime
- Finance
- Business-Government relations
- Labor
- Business environment
- Performance
- Green Economy Module:
- Environment-related aspects
- Exposure to environmental impacts
- Management and the environment
- Environmental policy and regulation
- Environmental impact of the establishment
Coverage
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
| Name |
|---|
| The World Bank Group |
| The European Bank for Reconstruction and Development |
| The European Investment Bank |
| Name |
|---|
| The World Bank Group |
| The European Bank for Reconstruction and Development |
| The European Investment Bank |
Sampling
The sample for 2019 Lebanon 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 "Lebanon 2019 ES Implementation Report" Appendix C.
Industry stratification was designed in the way that follows: two manufacturing industries (food and other manufacturing) and two services industries (wholesale & retail and other services). Food (ISIC Rev. 3.1 codes 15), Other Manufacturing (ISIC codes 16-37), Wholesale and Retail (ISIC code 51, 52) and Other Services (ISIC codes 45, 50, 55, 60-64, and 72).
For the Lebanon 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 was done across five regions: Beirut, Bekaa Valley & North Lebanon, Mount Lebanon, Nabatieh and South Lebanon.
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 0.33. 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 0.29.
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.
Data collection
| Start | End |
|---|---|
| 2019-05 | 2020-04 |
| Name |
|---|
| Info Pro |
For the Lebanon 2019 ES, the survey was plagued by political turmoil, strikes, riots, and road closures (particularly in and around Beirut) from September 2019 to March 2020; further, fieldwork ended because of shutdowns due to the COVID-19 outbreak.
Depositor information
| Name |
|---|
| Joshua Seth Wimpey |
Data Access
| Is signing of a confidentiality declaration required? |
|---|
| Yes |
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, The European Bank for Reconstruction and Development, and European Investment Bank. Lebanon Enterprise Survey (ES) 2019, Ref. LBN_2019_ES_v01_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Enterprise Analysis Unit | The World Bank Group | enterprisesurveys@worldbank.org |
Metadata production
DDI_LBN_2019_ES_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Economics Data Group | The World Bank Group | Documentation of the DDI |
2020-07-14
Metadata version
Version 01 (July 2020)
2020-07-14