Enterprise Survey 2015
Timor-Leste, 2015 - 2016
Get MicrodataIdentification
TLS_2015_ES_v01_M
Enterprise Survey 2015
| Name | Country code |
|---|---|
| Timor-Leste | TLS |
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 is used to create indicators that benchmark the quality of the business and investment climate across countries.
Data from 126 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/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.
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 anonymized 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 "EA" or "MYA" indicate questions specific to countries in East Asia and Pacific region, therefore, they may not be found in the implementation of the rollout in other countries. All other suffixed variables are global and are present in all country surveys over the world. 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.
Scope
The scope of the study includes:
- characteristics of establishments;
- infrastructure;
- sales and supplies;
- competition and innovation;
- capacity;
- land and permits;
- security (crime);
- finance;
- business-government relations;
- labor;
- business environment;
- performance.
Coverage
Dili
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.
Producers and sponsors
| Name |
|---|
| World Bank |
| Name |
|---|
| World Bank |
Sampling
The sample was selected using stratified random sampling. Two levels of stratification were used in this country: industry and establishment size.
Industry stratification was designed in the way that follows: the universe was stratified into manufacturing and services industry - Manufacturing (ISIC 3.1 codes 15 - 37), and Services (ISIC codes 45, 50, 51, 52, 55, 60-64, and 72).
For the Timor-Leste 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 did not take place as all interviews took place in and around Dili.
The sample frame consisted of listings of firms from two sources: First, for panel firms the list of 150 firms from the Timor-Leste 2009 ES was used. Second, for fresh firms (i.e., firms not covered in 2009), data from National Statistics Directorate (by way of PDT) was used.
The quality of the frame was enhanced by the verification process conducted by Mekong Economics. 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 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 6.8% (15 out of 220 establishments).
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 0.57. 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 0.15.
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.
Survey instrument
The structure of the data base reflects the fact that two different versions of the survey instrument were used for all registered establishments. Questionnaires have common questions (core module) and respectfully additional manufacturing- and services-specific questions. The eligible manufacturing industries have been surveyed using the Manufacturing questionnaire (includes the core module, plus manufacturing specific questions). Retail firms have been interviewed using the Services questionnaire (includes the core module plus retail specific questions) and the residual eligible services have been covered using the Services questionnaire (includes the core module). Each variation of the questionnaire is identified by the index variable, a0.
Data collection
| Start | End |
|---|---|
| 2015-09 | 2016-06 |
| Name |
|---|
| Mekong Economics |
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.
Data processing
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.
Access policy
Enterprise Surveys Data Portal - https://www.enterprisesurveys.org/portal
Depositor information
| Name | Affiliation |
|---|---|
| Joshua Wimpey | World Bank |
Data Access
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| no | 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).
Example:
World Bank. Timor-Leste Enterprise Survey (ES) 2015, Ref. TLS_2015_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 | World Bank | enterprisesurveys@worldbank.org |
Metadata production
DDI_TLS_2015_ES_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Data Group | World Bank | Study documentation using DDI standard |
2017-03-30
Metadata version
v01 (March 2017)