Abstract

This report presents the results of the first national Labour Force Survey (LFS) to be conducted in Timor-Leste since the country gained its full independence in 2002.

The survey provides data on a variety of key employment issues: - the labour force, in terms of age, sex, and education; - the employed population, in terms of occupation, economic sector and multiple job-holding; - employment conditions, in terms of job permanency, public/private sector, hours worked, underemployment, and net monthly earnings;- informal sector and informal employment, in terms of contractual conditions, size of establishment, benefits of employment, etc.; - the unemployed, including duration of unemployment, and methods of seeking work; and - persons not in the labour force, their reasons for not being available to work, and their previous work experience.

Geographic coverage

National coverage

Analysis unit

Households Individuals

Universe

Household members ages 10 and over. Excludes institutional population: persons living in military installations, correctional and penal institutions, dormitories of schools and universities, religious institutions, hospitals, and so forth. In the case of the armed forces, this means that they were included if they lived as members of a private household, but they were excluded if they lived in dormitories, barracks or similar accommodation.

Kind of data

Sample survey data [ssd]

Sampling procedure

DNE made use of the sample of 300 census enumeration areas (EAs) that had been selected for the Timor-Leste Survey of Living Standards 2007 (SLS 2007). Those EAs had been selected with probability proportional to size (PPS), where the measure of size was the 2004 EA census count. The actual number of EAs covered in SLS 2007 was in fact 269 instead of 300, because some large EAs were selected twice (or occasionally three or more times) and therefore received the corresponding number of workloads.

For SLS 2007, an up-to-date listing of households in the selected EAs was prepared in the field, and 24 households were selected in each EA, using a random start. These 24 households were then divided up into three 'tasks' (A, B and C), one for each of the three interviewers in the team. Task A received the first eight named households, Task B the next eight, and Task C the last eight. Each interviewer was required to interview five households, but they had a reserve list of three households in case they could not contact or interview any of the first five households on their list.

For LFS 2010, attempts were made to cover exactly the same EAs as was done in SLS 2007. Occasionally an EA was missed, and in a few cases the number of workloads covered in an EA was greater than the number covered in SLS 2007. Table 1.1 shows the number of urban and rural EA workloads covered in each district, and the expected number of households. Exactly the same listing sheets were used as had been used in SLS 2007, with the same names of household heads from SLS 2007 shown on the lists.

Based on the information provided on the cover sheet of each questionnaire, the sample of 4665 households contained 12,088 males and 12,000 females, giving an average household size of 5.2 (unweighted). Among these households there were 8,610 males aged 10 and over and 8,538 females aged 10 and over; these were the people to whom most of the survey questions were directed, after the basic household listing information had been collected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were carefully designed by the ILO team that visited Dili in March 2009. The questions were worded in the correct fashion, allowing the calculation of many statistical indicators that are fully in line with current international standards in labour statistics. Two questionnaires were used - a household questionnaire and an individual questionnaire.

DNE had organized the translation of the questionnaires into Tetum and the final questionnaires were in booklet form.

Response rate

It is difficult to measure the true response rate on this survey because of the method used for selecting the households to be interviewed. Three interviewers were working in each EA. Each interviewer had five specific households to visit, and kept three households in reserve. If any of those five households could not be located, or had moved, or was out at the time of the interviewer’s visits (even after repeated visits), or refused, or was otherwise not available, the interviewer was allowed to take the first replacement household. There was officially zero nonresponse, with all quotas successfully filled and all household questionnaires being marked with code 1 (‘completed - fully responding household’).

Sampling error estimates

Because the LFS is a sample survey, all estimates are subject to sampling error. Sampling errors have not been included in this report, but all reported figures have been rounded to the nearest thousand in order to make some allowance for the effects of sampling error.

Abstract

The principal objective of the LFS is to provide current data on the employment and unemployment situation of the population at national and subnational levels covering in particular vulnerable and informal employment, timerelated underemployment, potential labour force and subsistence foodstuff production.

Geographic coverage

National coverage

Analysis unit

Households Individuals

Universe

Household members 10 years old and above. Private households exclude population living in military barracks, penal institutions, dormitories of schools and universities, religious institutions, hospitals and so forth. For the armed forces, this means that they were included if they lived as members of a private household, but excluded if living in dormitories, barracks or similar accommodation.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design of the Timor-Leste LFS 2013 was developed in two stages: first a stratified sample of enumeration areas was taken from the census sampling frame, followed by listing all private households in the sample enumeration areas; and the second stage drew 15 sample private households in each sample enumeration for interviewing. Private households exclude population living in military barracks, penal institutions, dormitories of schools and universities, religious institutions, hospitals and so forth. For the armed forces, this means that they were included if they lived as members of a private household, but excluded if living in dormitories, barracks or similar accommodation.

Sample size is divided in three parts such as: - East: Lautem, Baucau, Viqueque, Manatuto - Central: Dili, Aileu, Ermera, Ainaro, Manufahi - West: Liquica, Bobonaro, Covalima, Oecusse (Otonom).

Mode of data collection

Face-to-face [f2f]

Research instrument

There are 82 questions in the questionnaire that are group into two items: A. Household questionnaire (roster) B. Individual questionnaire (administered to all household members 10 years old and above)

Cleaning operations

Editing at this stage involved a review of the questionnaire regarding its filled-in contents, which included ensuring that there were no missing blocks of information for household members aged 15 years old and over, and no incorrect coding of occupation, branch of economic activity and other variables.

Response rate

98.6%

Sampling error estimates

The sampling error of an estimate is based on the difference between the estimate and the value that would have been obtained on the basis of a complete population count under otherwise identical conditions. it is decomposed into two components: (i) sampling bias; and (ii) sampling variance.

Abstract

This research is an Indicator Survey conducted in Timor-Leste from Aug. 20 to Oct. 30, 2009, as part of the Enterprise Survey initiative. An Indicator Survey, which is similar to an Enterprise Survey, is implemented for smaller economies where the sampling strategies inherent in an Enterprise Survey are often not applicable due to the limited universe of firms.

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.

Questionnaire topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, land and permits, taxation, business-government relations, and performance measures.

Geographic coverage

National

Analysis unit

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.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural 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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Timor-Leste 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 23 manufacturing industries, and one services sector as defined in the sampling manual.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification did not take place as all interviews took place in and around Dili.

The sample frame used in Timor-Leste was obtained from the National Statistics Directorate (by way of Peace Dividend Trust (PDT) Master Database) (Apr., 2009). The sample frame was reviewed and duplicate establishments or establishments with ineligible characteristics (industry sector, number of employees, geographic location) removed from the list. The modified sample frame was used to select the sample of establishments for the full survey. This database contained the following information: -Name of the firm -Contact details -ISIC code -Number of employees.

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 40% (132 out of 329 establishments). Breaking down by industry, the following numbers of establishments were surveyed: Manufacturing - 21, Services - 129.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Services Questionnaire - Manufacturing Questionnaire - Screener Questionnaire.

The Services Questionnaire is administered to the establishments in the services sector. The Manufacturing Questionnaire is built upon the Services Questionnaire and adds specific questions relevant to manufacturing.

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.

Cleaning operations

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.

Response rate

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Timor-Leste Implementation 2009" in "Technical Documents" folder.

Abstract

The first national census of Timor-Leste was conducted from the 11th of July to the 30th of July in 2004 with 4,000 interviewers visiting over 190,000 households across the country. The Census provides Asia's newest nation with its first full population count after the traumatic events of 1999 and base line statistics on housing, employment, fertility and literacy. The census statistical data and indicators, at both national and district levels, will assist the country's administrators and international organisations in planning for sustainable development programs.

In July 2002, a mission comprised of experts from the United Nations Population Division, the Australian Bureau of Statistics, and the Malaysian Department of Statistics was asked to explore the feasibility of conducting a Population and Housing Census in the newly independent Timor-Leste. Although considered as a difficult undertaking, it was determined to be viable.

UNFPA organized the necessary technical and human resource support and provided the major part of the funding needed to carry out the census. Since 2002 two UNFPA Census Projects have been supporting census activities and have expended more than three million dollars. This major financial contribution was supplemented by the assistance of other donors: the United States, which among other things paid for some equipment, the printing of questionnaires and other forms, and also funded technical assistance for data editing; Ireland, which funded the census publicity campaign; New Zealand, which provided funding for technical experts; and Australia, which assisted in the training of data input personnel and in funding several technical assistance missions.

Geographic coverage

National

Analysis unit

• Individual,
• Households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire developed for the pilot census went through a review. A consultant from Statistics New Zealand worked on the questionnaires and talked with government ministries, various UN agencies, NGO's and other interested parties about content and format. Where changes were made, small field tests were carried out to confirm workability and acceptability. By January 2004, the questionnaires were ready to present to the Census Technical Committee and then to government agencies for formal acceptance. During that process, some minor changes were made, but the basic questionnaire was maintained.

Three types of questionnaires were used: one for households, one for institutions (prisons, orphanages, convents, hospitals and boarding schools) and one for hotels. This section refers only to the household questionnaire.

The household questionnaire was prepared in four languages: Tetum, Portuguese, Indonesian and English.

The questionnaire was well designed. The format, wording and arrangement of questions received a great deal of attention. It was short, simple, easy to apply, and included most of the standard census questions and items. The purpose here is not to evaluate the questionnaire in detail, but it is important to mention that the data collected with it has proved to be extremely useful for a number or purposes. The usefulness of the data is a good indicator of the format adequacy and organization of the questionnaire and the relevance of the questions included. It is also important to highlight that, up to now, various data analyses have shown that most of the information is reliable. However, it is also important to recognize there is plenty of space for improvement and the questionnaire for the 2010 Census will be much better. Actually, several analyses of the data obtained with the questionnaire clearly show the need to modify the next census questionnaire and, especially, include additional questions.

Cleaning operations

The first activity was checking and editing the waypoint file. Three main problems were found: duplicate waypoints, waypoints where letters were used instead of numbers, and invalid waypoint numbers. In all cases the errors were manually corrected. Duplicate waypoints were removed, alphanumeric numbers with "o" instead of "0" or "B" instead of "8" were rectified, and waypoints close to invalid waypoints were compared to obtain a clue as to what the likely correct number should be.

After linking waypoints with questionnaire data it was realized that the vast majority of waypoint numbers could be linked to their corresponding dwelling sticker numbers. However, it also became apparent that there were still discrepancies between the two databases: Some questionnaires could not be linked to waypoints and some waypoints could not be linked to questionnaires. These problems were solved with the help of maps, comparisons with nearby waypoints and, in some cases, with new visits to suspect dwellings or entire areas. CSPro, a software package developed by the US Bureau of the Census, was used to capture, process, and edit data.

The data capture team was formed as soon as the interviewing was completed. Staff received training in subjects such as understanding the census process, the design of the census forms, and how to operate the data-entry program. Approximately 38 data-entry operators undertook the work in several shifts. The data was captured by keyboard.

After the data was entered, a process of editing and imputation of data was conducted.

It is important to mention data capture and processing was a weak part of the census operation. Data entry had to be repeated because of the many mistakes and errors done the first time. In addition, after the data was finally entered, it took an unnecessarily long period to process end edit it. Data-capture ended in February 2005 and the edited master file was not ready until December 2005. Even then there were still some inconsistencies, especially in fertility and school enrolment data. Such inconsistencies are minor, but they may reduce the credibility of some results.

The underlying causes of the previous problems were poor use of technical assistance, largely due to lack of management continuity. The NSD is aware of this weakness and the need to address it for the next census.