Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The Palestinian Central Bureau of Statistics (PCBS) carried out four rounds of the Labor Force Survey 2021 (LFS). The survey rounds covered a total sample of about 25,179 households (about 6,300 households per quarter).

The main objective of collecting data on the labour force and its components, including employment, unemployment and underemployment, is to provide basic information on the size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in the employment situation. These data, supported with information on other aspects of the economy, provide a basis for the evaluation and analysis of macro-economic policies.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.

Geographic coverage

Covering a representative sample on the region level (West Bank, Gaza Strip), the locality type (urban, rural, camp) and the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered all Palestinian households who are a usual residence of the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The methodology was designed according to the context of the survey, international standards, data processing requirements and comparability of outputs with other related surveys.

---> Target Population: It consists of all individuals aged 10 years and Above and there are staying normally with their households in the state of Palestine during 2020.

---> Sampling Frame: The sampling frame consists of a comprehensive sample selected from the Population, Housing and Establishments Census 2017: This comprehensive sample consists of geographical areas with an average of 150 households, and these are considered as enumeration areas used in the census and these units were used as primary sampling units (PSUs).

---> Sampling Size: The estimated sample size is 8,040 households in each quarter of 2021.

---> Sample Design The sample is two stage stratified cluster sample with two stages : First stage: we select a systematic random sample of 536 enumeration areas for the whole round. Second stage: we select a systematic random sample of 15 households from each enumeration area selected in the first stage.

---> Sample strata: The population was divided by: 1- Governorate (17 governorates, where Jerusalem was considered as two statistical areas) 2- Type of Locality (urban, rural, refugee camps).

---> Sample Rotation: Each round of the Labor Force Survey covers all of the 536 master sample enumeration areas. Basically, the areas remain fixed over time, but households in 50% of the EAs were replaced in each round. The same households remain in the sample for two consecutive rounds, left for the next two rounds, then selected for the sample for another two consecutive rounds before being dropped from the sample. An overlap of 50% is then achieved between both consecutive rounds and between consecutive years (making the sample efficient for monitoring purposes).

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts:

---> 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

---> 2. Quality Control: This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data.

---> 3. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level…etc.

---> 4. Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.

Cleaning operations

---> Raw Data PCBS started collecting data since 1st quarter 2020 using the hand held devices in Palestine excluding Jerusalem in side boarders (J1) and Gaza Strip, the program used in HHD called Sql Server and Microsoft. Net which was developed by General Directorate of Information Systems. From the beginning of March 2020, with the spread of the COVID-19 pandemic and the home quarantine imposed by the government, the personal (face to face) interview was replaced by the phone interview for households who had phone numbers from previous rounds, and for those households that did not have phone numbers, they were referred to and interviewed in person (face to face interview). Using HHD reduced the data processing stages, the fieldworkers collect data and sending data directly to server then the project manager can withdrawal the data at any time he needs. In order to work in parallel with Gaza Strip and Jerusalem in side boarders (J1), an office program was developed using the same techniques by using the same database for the HHD.

---> Harmonized Data - The SPSS package is used to clean and harmonize the datasets. - The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency. - All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization. - A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables. - A post-harmonization cleaning process is then conducted on the data. - Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

The survey sample consists of about 32,160 households of which 25,179 households completed the interview; whereas 16,355 households from the West Bank and 8,824 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 79.8% while in the Gaza Strip it reached 90.5%.

Sampling error estimates

---> Sampling Errors Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators: the variance table is attached with the final report. There is no problem in disseminating results at national or governorate level for the West Bank and Gaza Strip.

---> Non-Sampling Errors Non-statistical errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey, as well as practical and theoretical training during the training course. Also data entry staff were trained on the data entry program that was examined before starting the data entry process. To stay in contact with progress of fieldwork activities and to limit obstacles, there was continuous contact with the fieldwork team through regular visits to the field and regular meetings with them during the different field visits. Problems faced by fieldworkers were discussed to clarify any issues. Non-sampling errors can occur at the various stages of survey implementation whether in data collection or in data processing. They are generally difficult to be evaluated statistically.

They cover a wide range of errors, including errors resulting from non-response, sampling frame coverage, coding and classification, data processing, and survey response (both respondent and interviewer-related). The use of effective training and supervision and the careful design of questions have direct bearing on limiting the magnitude of non-sampling errors, and hence enhancing the quality of the resulting data. The implementation of the survey encountered non-response where the case ( household was not present at home ) during the fieldwork visit and the case ( housing unit is vacant) become the high percentage of the non response cases. The total non-response rate reached 16.7% which is very low once compared to the

Abstract

The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force as a means to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The broad objectives of the survey are as follows:

• To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc;
• To acquire current information on the dimensions of national labour force; i.e. number of persons employed, unemployed, and underemployed or out of labour market;
• To gather descriptive facts on the engagement in major occupational trades and the nature of work undertaken by the institutions/organizations;
• To profile statistics on employment status of the individuals, i.e. whether they are employers, own account workers, contributing family workers or paid employees (regular/casual);
• To classify non-agricultural enterprises employing household member(s) as formal and informal;
• To quantify the hours worked at main/subsidiary occupations;
• To provide data on wages and mode of payment for paid employees;
• To make an assessment of occupational health and safety of employed persons by causes, type of treatment, conditions that caused the accident/injury and time of recovery; and
• To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

Geographic coverage

National coverage

The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census, excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

All sample enumeration blocks in urban areas and mouzas/dehs/villages in rural areas were enumerated except 737 households due to non contact and refusal cases in urban and rural areas.

Analysis unit

• Household
• Individuals/ persons aged 10 years and above

Universe

The universe for Labour Force Survey consists of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding FATA and military restricted areas. The population of excluded areas constitutes about 2% of the total population. The following groups were also excluded non-settled population, persons living in institutions and foreigners.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Quarterly.

Sampling procedure

Sample Design: A stratified two-stage sample design is adopted for the survey.

Sampling Frame:Pakistan Bureau of Statistics (PBS) has developed its own sampling frame for urban areas. Each city/town is divided into enumeration blocks. Each enumeration block is comprised of 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks as updated from field on the prescribed proforma by Quick Count technique in 2013 for urban and the list of villages/mouzas/dehs or its part (block), updated during House Listing in 2011 for conduct of Population Census are taken as sampling frames.

Enumeration blocks & villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively.

Stratification Plan

Urban Domain: Large cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further sub-stratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame.

Remaining Urban Areas: In all the four provinces after excluding the population of large cities from the population of an administrative division, the remaining urban population is grouped together to form a stratum.

Rural Domain: Each administrative district in the Punjab, Sindh and Khyber Pakhtunkhwa (KP) is considered an independent stratum whereas in Balochistan, each administrative division constitutes a stratum.

Selection of primary sampling units (PSUs): Enumeration blocks in urban domain and mouzas/dehs/villages in rural are taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block by Quick Count technique in 2013 and village or its part (block), updated during House listing in 2011 for conduct of Population Census are taken as sampling frames for rural domain is considered as measure of size.

Selection of secondary sampling units (SSUs): The listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

Sample Size and Its Allocation: A sample of 41,484 households is considered appropriate to provide reliable estimates of key labour force characteristics at National/Provincial level. The entire sample of households (SSUs) is drawn from 2887 Primary Sampling Units (PSUs) out of which 1710 are rural and 1177 are urban. The overall sample has been distributed evenly over four quarters independently. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. To produce reliable estimates, a higher proportion of sample is assigned to Khyber Pakhtunkhwa and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately

Mode of data collection

Face-to-face [f2f]

Research instrument

Structured questionnaire.

Cleaning operations

Editing is done at headquarter by the subject matter section. Computer edit checks are applied to get even with errors identified at the stage of data entry. The relevant numerical techniques were used to eliminate erroneous data resulting from mistakes made during coding. The survey records are further edited through series of computer processing stages.

Response rate

98.2%

Data appraisal

Notwithstanding complete observance of the requisite codes to ensure reliability of data, co-efficient of variations, computed in the backdrop of 5% margin of error exercised for determining sample size, are also given below to affirm the reliability of estimates.

Abstract

The main objective of collecting data on the Palestinian Labour Force Survey 1998 (Fourth Quarter) including components of employment, unemployment and underemployment, is to provide basic information on the relative size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in employment. These data supported with information on other aspects of the economy provide a basis for the evaluation and analysis of macro-economic policies.

Geographic coverage

National

Analysis unit

• Household
• Individual aged 10 years and above

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: In the absence of a population census since 1967, the major task, with regard to constructing a master sample, was developing a sampling frame of suitable units covering the whole country. Such units have been used as the PSUs (Primary Sampling Units) in the first stage of selection. For the second stage of selection, all PSUs have been listed in the field at the household level. This provided a sampling frame for selecting the households.

Sample Design: The sample is a two-stage stratified cluster random sample.

Target Population: All Palestinians aged 15 years and above living in the Palestinian Territories, excluding nomads and persons living in institutions such as prisons or shelters.

Stratification: Four levels of stratification were made: 1. Stratification by District. 2. Stratification by place of residence which comprises: (a) Municipalities; (b) Villages; and (c) Refugee Camps 3. Stratification by size of locality. 4. Stratification by cell identification by locality.

Sampling Unit: First stage sampling units are the area units (Cells) in the master sample. The second stage sampling units are households.

Sample Size: The sample size in the the eleventh round/ fourth quarter (October 1998 - December 1998) about 7,631 households (23,045 persons of working age).

Target cluster size: The next important issue in sample design is the target cluster size or "sample-take," the number of households to be selected per PSU on the average. In this survey persons of working age had been selected from 480 master sample areas. Therefore, the sample take was around 16 households.

Sample Rotation: Each round covered all the 480 master sample areas (except for the first round which covers 5/6 of these, i.e. 480 areas with proportionately increased sample-take per cluster so as to keep the same sample size). Basically, the areas remained fixed over time, but within each area a proportion of the households was replaced each round. During the first phase when the survey was conducted at 6- monthly interval or quarterly surveys were introduced, the same households remain in the sample over 6 consecutive rounds. A high overlap of 5¤6 is then achieved between consecutive rounds (making the sample efficient for monitoring trends), reducing linearly to zero overlap after 6 rounds. In each round, 1 6 (i.e. 80) clusters are listed - i.e. 320 over the whole year as before.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts: 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

1. Quality Control: This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data).

2. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level.etc.

3. Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.

Response rate

• Response rate in the fourth quarter was 86.4%

Abstract

This survey intends to: -

· Measure the labour force or economically active population size in relation to the general population in the country. · Identify and analyse the factors leading to the emergence and growth of Labour Force in the country. · Monitor the labour force participation. · Identify and measure the informal sector from within the labour force. · Monitor other Key Indicators of the Labour Market such as employment rates,unemployment rates, hours of work, average income and/or wages etc.

Furthermore, the survey seeks to examine the relationships of socio-economic factors such as education, health, social security, employment within the labour force, and more importantly to measure the causes and effects of children’s involvements in economic activities with special focus on the conditions and environment under which affected children operate.

The main objective of the 2012 LFS was to collect data on the social and economic activities of the population, including detailed information on employment, unemployment, underemployment, wages, informal sector, general characteristics of the labour force and economically inactive population. The survey was designed to specifically measure and monitor Key Indicators of the Labour Market (KILM) such as employment levels, unemployment, income and child labour in Zambia. However, indicators on child labour are not part of this 2012 LFS report. There will be a separate report on child labour later. The measurement of the KILM was with a view to informing users and policy-makers for decision-making. The methodology used in carrying out the survey and the design of questionnaire conform to internationally acceptable standards.

Geographic coverage

The 2012 Labour Force Survey (LFS) was a nation-wide survey covering household population in all the ten provinces and, in both rural and urban areas. The survey covered a representative sample of 11, 520 households, which were selected at two stages. In the first stage, 576 Standard Enumeration Areas (SEAs) were selected from a sampling frame developed from the 2010 Census of Population and Housing. In the second stage, households in each of the selected SEA were first listed/updated and then 20 households for enumeration were selected. The total sample of 11,520 households was first allocated between rural, urban and the provincial domains in proportion to the population of each domain according to the 2010 Census results.

Analysis unit

The unit of analysis was Households and Individuals ( Men and Women of 5 years and older). Additionally, the analysis focused on national level at both rural/urban and provincial level. The micro-data has provisions to generate major indicators at district and constituency levels. As much as possible the micro-data have also been analyzed by sex and age.

Universe

The survey covered all de jure household members (usual residents) in non-institutionalised housing units, all women and men aged 5 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to allow separate estimates at national level for rural and urban areas. Further, it also allowed for provincial estimates. A cluster, which is equivalent to a Standard Enumeration Area (SEA), was the primary sampling unit in the ?rst stage. In the second stage, a household was a sampling unit for enumeration purposes. Zambia is administratively divided into ten provinces. Each province is in turn subdivided into districts. For statistical purposes each district is subdivided into Census Supervisory Areas (CSAs) and these are in turn demarcated into Standard Enumeration Areas (SEAs). The Census mapping exercise of 2006-2010 in preparation for the 2010 Census of Population and Housing, demarcated the CSAs within wards, wards within constituencies and constituencies within districts. As at the time of the survey, Zambia had 74 districts, 150 constituencies, 1,430 wards and about 25,000 SEAs. Information borne on the list of SEAs from the sampling frame also includes number of households and the population size as at the last update of the SEA. The number of households determined the selection of primary sampling units (PSU). The SEAs are stratifed as urban and rural. The total sample of 11,520 households was first allocated between rural, urban and the provincial domains in proportion to the population of each domain according to the 2010 Census results. The proportional allocation does not however allow for reliable estimates for lower domains like district, ward or constituency. Adjustments to the proportional allocation of the sample were made to allow for reasonable comparison to be achieved between strata or domains. Therefore, disproportionate allocation was adopted, for the purpose of maximizing the precision of survey estimates. The disproportionate allocation is based on the optimal square root allocation method designed by Leslie Kish. The sample was then selected using a stratifed two-stage cluster design.

Sampling deviation

There was no deviation from sample design.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires (Form A and Forma B) were used to collect data from the household members. Form A was used in the first stage for listing purposes while Form B was used in the second stage for collecting detailed data from the selected households. It was a requirement for each household member to provide responses during the face-to-face interview to the questions that were asked.

The main questionnaire has ten sections namely:

a. Demographic Characteristics b. Education, Literacy and Skills Training c. Economic Activity d. Employment e. Hours of Work and Underemployment f. Income g. Unemployment/Job Search h. Previous Work Experience i. Household Chores j. Working Conditions (i.e. Forced labour)

Cleaning operations

Data editing took place at a number of stages throughout the processing. These included:

1. Field editing
2. Office editing and coding
3. During data entry
4. Structure checking and completeness
5. Secondary editing
6. Strucural checking of SAS data files

Response rate

At the end of the field work and editing in the provinces, a total of at least 11,000 of completed questionnaires, representing a 99.8 percent response rate were sent to Head Office for data processing.

Data appraisal

A series of data quality tables and graphs are available to review the quality of the data and in addition to this, external resources such as the 2012 Labour Force Survey report has been attached.

Labour Force Survey 2nd Quarter 2013, Persons with Disabilities

In the second quarter of each year, the Labor Force Survey (LFS) has some additional questions about disability. The statistics provide information on the situation in the labor market for people with disabilities, and the development over time, compared with the entire population. This data set contains a supplementary survey to the Labor Force Survey (LFS) in the second quarter of 2013. Corresponding surveys have been conducted annually since 2002.

As of the 1st quarter of 1972, SSB has conducted official quarterly labour force surveys (AKU). These surveys aim to give the labour force authorities (and other people interested) knowledge of the occupational structure of the population and how it develops over time. The surveys are meant to give a foundation and statistical material for occupational prognoses and labour research. The samples in AKU are from 1992 representative at county level. In the period 1972-1991 they were representative on county pair level.

As from January 2006 some major changes were introduced to AKU in order to enhance its comparability to similar surveys in other countries. The changes consist of minor definitional adjustments of unemployment, some adjustments and enlargement of the questionnaire and a change in age definition (age at reference point instead of at the end of the year). Simultaneously the lower age limit to be included in AKU was lowered from 16 to 15 years. This led to some breaks in the time series in the aforementioned areas.

Originally, AKU respondents were interviewed in two consecutive quarters of a year, followed by a pause of two quarters, and then another two quarters of interviews. The sample was approximately 10-11.000 respondents in each quarter up until 1988. Originally, AKU was intended to be an analytical supplement to the monthly occupational statistics that was based on the social security membership index file. However, the social security-based statistics disappeared when the sickness benefit was included in the National Insurance as of 1st of January 1971, and AKU has after gradually developed into the most significant source of knowledge of the state of the labour market and its development.

In 1975, Statistics Norway changed the sampling frame of survey research, see article 37: "Om bruk av stikkprøver ved kontoret for intervjuundersøkelser", SSB (About the Use of Random Samples at the Office for Survey Research, Statistics Norway) by Steinar Tamsfoss, and SØS 33: "Prinsipper og metoder for Statistisk sentralbyrås utvalgsundersøkelse (Principles and Methods for Statistics Norway's sample research) by Ib Thomsen. Simultaneously, the method for estimation of inflation to national numbers was changed, so that reasonable numbers for regions do exist from 1975 and onwards. The change in 1975 led to a different way of interviewing in groups. This caused amongst other things a break with the AKU panel systematics.

In the AKU survey of 1976, a slightly changed questionnaire was introduced. Also, there was a return to the original 6-quarter rotation scheme. The new questionnaire implied a better identification of family workers and persons that are temporarily without paid work. Thus, 30-35 000 more people were defined as employed. The group of "job-seekers without income" were also extended to include persons that were on an involuntary leave of absence. The questions concerning underemployment and "over employment" in the original questionnaire were abandoned.

From the 1st quarter of 1987, the estimation method (inflation to national numbers) was slightly changed. There was also a minor adjustment in the definition of employment. In order to ensure that the numbers were to be comparable to earlier surveys, new versions of the 1980-1986 AKU-files were drawn up. Consequently two versions of the 1980-1987 files - respectively with the old and new methods of estimation - exist. The "old" means that the data are comparable to the original numbers published in the period of 1972 - 1987, whilst the "new" implies that the data are comparable to numbers published after 1987.

Between the 1st and 2nd quarter of 1988, the AKU file description was changed. The variable "Labour-market status" was given a different coding. In addition, adjustments in the data collections were made - from interviewing a specific week every quarter to carry out continuous weekly interviews. In addition, an escalation scheme to increase the sample size was started. This affected the weights, and from the 2nd quarter of 1988, these were recalculated monthly. To balance out the quarterly or yearly files to total national numbers, the monthly weights therefore had to be divided in three or twelve to give the correct total number.

In 1996, AKU was significantly revised: The questionnaire, the...

Abstract

The purpose of the LFS is to provide information on the economically active population. The main objective of collecting data on the economically active population is among others to provide basic information on the size and structure of Botswana’s workforce.

Unlike the first and second Labour Force Surveys, the 2005/06 survey collected information from persons aged 7 years old and above while the previous surveys collected information from persons aged 12 years and above. The inclusion of the 7 years and above category was to measure the extent of child labour in this country. The coding of the occupations was based on the 1988 International Standard Classification of Occupation (ISCO-88), whilst the definition of the informal sector is in accordance with the 1993 System of National Accounts (SNA -1993). Few questions were asked about the informal activities and migration status of the labour force as this survey was mainly designed to capture information on the labour force characteristics.

Survey Objectives The broad objective of the survey was to obtain comprehensive data on the status of the labour market prevailing in Botswana. More detailed objectives were; • To provide measures of both current and usual economic activity. • To obtain a measure of the size of employment in both formal and informal sector. • To provide measures of unemployment and underemployment. • To estimate the extent of child labour, obtain child employment activities and reasons for working. • To estimate total population for the period.

The survey data would provide, among others, baseline information on indicators of employment and unemployment levels, and information necessary that can be used to develop, manage, evaluate and report on labour market policies.

Geographic coverage

National

Analysis unit

• Households
• Individuals aged 7 years and above

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME In general the 2001 Population and Housing Census, undertaken in August, is the Sampling Frame on which sample selection for the Survey Programmes are based. The census result gives information on population, number of household at Locality, Enumeration Area (EA), village and district/town levels. Also given for each EA is information on ecological zones in rural areas.

The Sampling frame was defined and constituted by all Enumeration Areas (EAs) found in three geographical regions viz. (i) Cities & Towns (ii) Urban Villages, and (iii) Rural Districts as defined by the 2001 Population and Housing Census.

Being a two-stage design, two frames were required one for each stage.

The sampling frame for the first stage based on the 2001 Population and Housing Census. This comprised the list of all Enumeration Area (EA) together with number of households. In the census the EAs were frames of manageable size (in terms of dwellings/households).

The sampling frame for the second stage was produced only in the selected EAs. Before the beginning of the survey interviews, the field teams listed all private habitable dwellings/households in their EAs. Thus the number of occupied households in the selected EA served as sampling frame for that EA.

The frame for the Botswana Labour Force Survey 2005/6 consisted of 4,143 EAs being the total number of Enumeration Areas (EAs) delineated during the 2001 Population and Housing Census.

STRATIFICATION When national level estimates are the main focus a type of stratification that is simple to implement and highly efficient is implicit stratification. It is a form of geographic stratification, which when used together with systematic pps sampling automatically distributes the sample proportionately into each of the nation's administrative subdivisions, as well as the urban and rural sectors.

Creation of strata is dictated by two principal criteria. These include a need to: i. provide estimates for each major region of the country. ii. increase precision

Thus, stratification variables included cities/towns and administrative districts. Apart from national and rural estimates, the Government, which is the main user of CSO data, requires accurate estimates for all regions for planning and monitoring of development projects. Stratification was therefore undertaken such that all districts and major urban centres become their own strata. With regard to increase precision consideration was also given to group EAs according to ecological zones in rural districts and according to income categories in cities/towns.

Geographical stratification along ecological zones and income categories was expected to improve the accuracy of survey data in view that homogeneity of the variables was relatively high (implicit stratification).

There are five major rural ecological zones, namely: -Village, -Lands -Cattle Post -Freehold Farms -Mixture of Land and Cattle Post

During the delineation of the maps, each EA was associated with unique ecological zone and thus, grouping the EAs into respective zones was not a problem. To facilitate the selection according to the stratification variables and EAs were listed in some order, for example starting cattle post, then farms etc. in case of rural areas.

Note: See detail sampling procedure description in final report

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires are the primary recording documents of the survey. In the development of the questionnaires, a reference group was formed to work into the questionnaire. The final version of the questionnaires were finalized on the basis of the experiences gained from the Pilot Survey conducted using the drafted questionnaires for the survey.

The 2005/6 BLFS consisted of two questionnaires, namely i. The Household Questionnaire, and ii. The Individual Questionnaire

Household Questionnaire: This questionnaire is a standardized questionnaire of the CSO's Household Survey Programme except with a little modification as per the need of the designated survey. This questionnaire also set the criteria for eligibility of being an BLFS individual questionnaire respondent.

The Household questionnaire was divided into four major sets of questions, namely i. Socio-Demographic Characteristics ii. Parental Survivor and Fostering iii. Education and Training

Eligibility Criteria was not a question asked by the respondent. It was meant for the interviewer to identify persons who were eligible for an individual questionnaire. UCriteriaU: “Those respondents who were aged 7 years and more and also usual members of this household were eligible for an individual respondent.”

Individual Questionnaire: All the eligible individuals from the household questionnaire were asked questions on the individual questionnaire.

The process of individual questionnaire development was not a simple task. The challenge was to develop the types of questions that led to achieving the survey objectives. Standardised questionnaire were developed so as to provide the basis for current (where feasible) and future comparability. More specifically, questions and the design structure of the questionnaire took into full account a set of objectives spelt out above with a view to address them.

The individual questionnaire has the questions mainly on the following topics: Section 1: For all persons aged 7 years and above A: Usual Activity. B: Current Activity Section 2: For all who did not work in the last 7 days and who were available for work (12 years and above) Section 3: For all employed in the 7 days. A: Main Economic Activity (for 7 years and above) B: Secondary Activity (for 12 years and above) C: Usual Hours Worked (for 7 years and above) D: Actual Hours Worked (for 7 years and above) E: Additional Work F: Different Work G: On the Job Training H: Income from Employment Business Section 4: Migration (For all persons aged 12 years and above) Section 5: Housework and Work at School Section 6: Health and Safety

PRE-TEST The Botswana Labour Force Survey instruments (household and individual) were pretested in areas in and around Gaborone on the 14-16 April 2005. Households were selected at random from EAs belonging to different strata according to the stratification in the sample design.

Cleaning operations

Before data entry was carried out, questionnaires were edited to check if all the relevant questions have been responded to and coded according to the codes designed for the study. Editing and coding started in August 2005 by 19 Coders and finished in August 2006. Data entry was carried out under the supervision of one programmer/supervisor. Consistency checks on the data set as per the Computer edit Specifications were performed.

The European Union Labour Force Survey (EU-LFS) pilot data collection carried out in 2022 provided information on Digital Platform Employment (DPE).

The DPE statistics provide information on the type of digital platform work or service, encompassing details on working conditions and arrangements. Together with demographic characteristics, such as sex and age, these statistics allow the description of the profile of digital platform workers.

The results of the pilot data collection are published as experimental statistics. In particular, these statistics show the share of digital platform workers among all people aged 15 to 64 , defined as those who have worked for at least one hour through a digital platform in the last 12 months, broken down by type of DPE activity.

For those who reported to be in DPE for at least 1 hour during the last month, indicators on employment characteristics and working arrangements are also presented by:

• number of hours worked,
• share of income from DPE in total income,
• social insurance coverage,
• type of the assignment of the work, service or task,
• degree of autonomy in accepting work or services, deciding on working hours or price setting.

The pilot data collection included 13 variables: see the annexed methodological note.

The experimental statistics tested:

• the conceptual framework and
• the measurement approach to this new form of employment.

The data was collected on a voluntary basis by 17 countries: 16 EU countries and 1 EFTA country. The indicators are presented for an aggregate of 17 countries.

Abstract

The main objective of the 2011 Labour Force Survey is to collect information on the structure and distribution of labour force, employment and unemployment. Besides furnishing estimates at national and state levels, the survey also produces useful data for urban and rural areas. The comprehensive and systematic approach in the data collection and processing has been maintained over a period of time with the aim of obtaining comparable time series data.

Geographic coverage

The Labour Force Survey covers both urban and rural areas of all states in Malaysia.

Analysis unit

People aged 15 years and over

Universe

The survey population is defined to cover persons who live in private living quarters and hence excludes persons residing in institutions such as hotels, hostels, hospitals, prisons, boarding houses and military barracks. The survey comprises the economically active and inactive population.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling frame

The frame used for the Labour Force Survey is from the Household Sampling Frame, Department of Statistics, Malaysia which is made up of Enumeration Blocks (EBs) created for the 2000 Population and Housing Census.

EBs are geographically contiguous areas of land with identifiable boundaries. On average, each EB contains about 80 to 120 living quarters. Generally, all EBs are formed within gazetted boundaries, i.e. within administrative district, mukim or local authority areas.

The EBs in the sampling frame are also classified by urban and rural areas. Urban areas are as defined in the 2000 Population and Housing Census. Urban areas are gazetted areas with their adjoining built-up areas which have a combined population of 10,000 or more at the time of the 2000 Population and Housing Census. All other gazetted areas with a population of less than 10,000 persons and non-gazetted areas are classified as rural. Built-up areas are defined as areas contiguous to a gazetted area and has at least 60 per cent of their population (aged 10 years and over) engaged in nonagricultural activities as well as having modern toilet facilities in their housing units.

Urbanisation is a dynamic process and keeps changing in line with the progress and development. Thus, the urban areas for the 1991 and 2000 censuses do not necessarily refer to the same areas, as areas fulfilling the criteria of urban continue to increase or grow.

For the purpose of urban/rural analysis, the stratum are combined as follows: Urban = Metropolitan + Urban large Rural = Urban small + Rural

Sample design

A stratified two-staged sample design is adopted, that is: Primary stratum = made up of the states in Malaysia Secondary stratum = made up of the urban and rural stratum as defined in para 6.7 and formed within the primary stratum

Samples are drawn independently within each level of the secondary stratum. The first stage units of sample selection are the EBs while the second stage units are the living quarters (LQs) within the EBs. All households and persons within the selected LQs are canvassed. At every stage of selection, the units are selected systematically with equal probability within each level of the secondary stratum.

Sample size

The sample size required is based on the reliability of available past data. Other factors such as cost and availability of staff are also taken into consideration in determining the sample size.

The sampling procedures are more fully described in "Malaysia Labour Force Survey 2011 - Report" pp. 261-264.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is designed to collect pertinent information on personal characteristics of the survey population and detailed information on economic characteristics of the labour force.

All household members will be asked the following information: (i) relationship to the head of household; (ii) sex; (iii) age; (iv) ethnic and citizenship; (v) marital status; and (vi) educational attainment.

For those aged 15 years and over, their activity status either employed unemployed or outside labour force will be determined. Information collected from the employed include whether they had been working or not during the reference week, the number of hours worked, occupation, industry and status in employment. If they have worked less than 30 hours per week, reasons and willingness to accept additional work is also obtained. If they have not been working during the reference week but have a job to return to, the reasons for not working would be sought.

The following questions will be asked to those who are unemployed: (i) action taken to look for work; (ii) work experience; and (iii) duration of unemployment.

Those who are classified as outside labour force will be asked to state the reasons for not seeking work and work experience, if any.

Sampling error estimates

Sampling error is a result of estimating data based on a probability sampling, not on census. Such error in statistics is termed as relative standard error and often denoted as RSE which is given in percentage. This error is an indication to the precision of the parameter under study. In other words, it reflects the extent of variation with other sample-based estimates.

Sampling errors of estimates on a few important variables at national and state levels are calculated separately. For Labour Force Survey 2011, the labour force participation rate for Malaysia was 64.4 percent with an RSE of 0.25 percent and standard error (SE) of 0.16 percent. At 95 per cent confidence interval (a = 0.05), the labour force participation rate was in the range of 64.08–64.72 percent.

Abstract

The Labor Force Survey (LFS) of Cambodia conducted in November 2001 is the second of the series of nationwide labor force surveys. Its primary purpose was to gather data on labor force and employment levels and structures needed for national accounts estimation. The results of the survey are intended for national account estimation and for providing a quantitative framework for planning and policy formulation affecting the labor market.

Geographic coverage

National (24 Provinces) Urban, Rural

Analysis unit

1.Individuals

2.Household

Universe

The survey coverd the members (individuals) from the sample households of resident households in Cambodia:

1. All members for geographic part

2. All members aged 10 and over for education and labour force parts

Kind of data

Sample survey data [ssd]

Sampling procedure

The LFS adopted a stratified two-stage systematic sampling design with villages as the primary sampling units (PSUs) and households as secondary sampling units (SSUs).

The sample consisted of 500 villages sampled from 12,739 villages in Cambodia. Then from each sample village, a fix sample of 10 households was taken using circular systematic sampling with a random start. It covered 500 sample villages or a total of 5000 sample households nationwide

Mode of data collection

Face-to-face [f2f]

Research instrument

The following are the LFS forms used during the field enumeration and a brief outline of the fieldwork procedures:

2.1 Listing Sheet (LFS Form 1)

This is a sheet containing a list the buildings, housing units and households within an enumeration area (EA). Other information pertaining to population of households were also recorded.

Listing sheet was used to record all households in the village or part thereof selected for household enumeration. The current list of households was necessary for sampling households and also as an input to derive household weights

2.2 Questionnaire (LFS Form 2)

This is the form used for interviewing and recording information about a household. This questionnaire also contains information on the demographic and economic characteristics of the population.

1. Part I - For all persons

   a) Relationship to Household Head

   b) Age

   c) Sex

2. Part II - For Persons 10 Years and Over

   a) Education (Current School Attendance and Highest Educational Attainment)

   b) Current Activity (Past Week)

   c) Primary Occupation

   d) Economic Activity or Industry

   e) Nature and Status of Employment

   f) Remuneration, Earnings and Commissions Received

   g) Hours Worked

   h) Availability for /Seeking Additional Work

   i) Reasons for not Being Available for Work

Cleaning operations

All completed questionnaires were brought to NIS for processing. Although completed questionnaires were checked and edited by supervisors in the field, specially because of the length of questionnaires and the complexity of the topics covered the need for manual editing and coding by trained staff was accepted as an essential priority activity to produce a cleaned data file without delay. In all 4 staff comprising 3 processing staff and 1 supervisor were trained for two days by the project staff. An instruction manual for manual editing and coding was prepared and translated into Khmer for the guidance of processing staff.

In order to produce an unedited data file, keying in the data as recorded by field enumerators and supervisors, (without subjecting data to manual edit as required by the Analysis Component Project staff), it was necessary to structure manual editing as a two-phase operation. Thus in the first phase, the processing staff coded the questions such as those industry, and occupation which required coding. Editing was restricted to selected structural edits and some error corrections. These edits were restricted to checking the completeness and consistency of responses, legibility, and totaling of selected questions. Error corrections were made without canceling or obliterating the original entry made by the enumerator, by inserting the correction close to the original entry.

Much of the manual editing was carried out in the second phase, after key entry and one hundred percent verification and extraction of error print outs. A wide range of errors had to be corrected which was expected in view of the complexity of the survey and the skill background of the enumeration and processing staff. The manual edits involved the correction of errors arising from incorrect key entry, in-correct/ failure to include identification, miss-coding of answers, failure to follow skip patterns, misinterpretation of measures, range errors, and other consistency errors.

Response rate

Despite the length of the questionnaire, the respondents cooperated with the survey staff and provided answers to both questionnaires and it was possible to achieve a 100% response rate. At this stage it is not possible to comment on item non-response, and completeness of information provided by the respondents, and the respondent's fatigue arising from the length of the interviews which may have had a bearing on these issues.

Sampling error estimates

Sampling errors are those that are related to the size of the sample and the kind of samples selected. Non-sampling errors are those such as arising from errors committed by the interviewers in recording information, response errors and encoding or processing errors.

The results obtained from the survey are subject to sampling errors. Sampling errors in surveys occur as a result of limiting the survey observations to a subset rather than the whole population. These errors are related to the sample size selected and sampling design adopted in the survey. In order to maintain these errors within acceptable levels, the efficient sampling design with the sample allocation described earlier was adopted.

In addition to sampling errors, the estimates are also subject to non-sampling errors that arise in different stages of any survey operation. These include errors that are introduced at the preparatory stage errors committed during data collection including those committed by interviewers and respondents processing errors

The first item includes errors arising from questionnaire design, preparation of definitions and instructions, preparation of table formats etc. The other two categories are clear from the terminology used. The use of trained enumerators and processing staff and careful organization and thorough supervision are essential to control and minimize these errors.

As already referred to, it was possible to obtain responses from all the villages and households that were sampled, and thus it was not necessary to adjust the data for non-response. Thus the bias that is introduced into the estimates as a result of non-response was avoided.

The Business Register and Employment Survey (BRES) is the official source of employee and employment estimates by detailed geography and industry. It is also used to update the Inter-Departmental Business Register (IDBR), the main sampling frame for business surveys conducted by the Office for National Statistics (ONS), with information on the structure of businesses in the UK.

The survey collects employment information from businesses across the whole of the UK economy for each site that they operate. This allows the ONS to produce employee and employment estimates by detailed geography and industry split by full-time/part-time workers and whether the business is public/private.

The ONS produces a number of different measures of employment including Workforce Jobs and the Annual Population Survey/Labour Force Survey. However, BRES is the recommended source of information on employment by detailed geography and industry.

The BRES has two purposes: collecting data to update local unit information and business structures on the IDBR, and producing published annual employment statistics.

The BRES sample does not include Northern Ireland. Northern Ireland data are received direct from the Northern Ireland Department of Enterprise, Trade and Investment (DETINI) which are used to create UK estimates. The UK Data Archive holds data only for Great Britain.

The BRES replaced the Annual Business Inquiry, Part 1 (ABI/1) in 2009. ABI/1 data for 2009 and earlier are held as part of the Annual Respondents Database under UK Data Archive SN 6644.

Change in sampling from 2015-2016
In 2015, ONS made a strategic decision to include business units with a single PAYE code for which VAT data are available. Prior to 2015, such units were excluded from the sampling frame and therefore not estimated for in ONS outputs. So from January 2016, the coverage of BRES was extended to include a population of solely PAYE based businesses. This improvement in coverage is estimated to have increased the business survey population by around 100,000 businesses, with a total of around 300,000 employment and 200,000 employees between December 2015 and January 2016. The increase in business population has led to an increase in the estimate of employment and employees for the 2015 dataset. Further information is available in documentation file '7463_bres_2015_change_in_firm_sampling.pdf'.

Linking to other business studies
These data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

For Secure Lab projects applying for access to this study as well as to SN 6697 Business Structure Database and/or SN 7683 Business Structure Database Longitudinal, only postcode-free versions of the data will be made available.

Latest edition information
For the fourteenth edition (September 2025), the 'revised 2022' and 'provisional 2023' data files have been added, along with a variable list for the same years.

Abstract

The main objective of collecting data on the Palestinian Labour Force Survey 1998 (Frist Quarter) including components of employment, unemployment and underemployment, is to provide basic information on the relative size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in employment. These data supported with information on other aspects of the economy provide a basis for the evaluation and analysis of macro-economic policies.

Geographic coverage

National

Analysis unit

• Household
• Individual aged 10 years and above

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: In the absence of a population census since 1967, the major task, with regard to constructing a master sample, was developing a sampling frame of suitable units covering the whole country. Such units have been used as the PSUs (Primary Sampling Units) in the first stage of selection. For the second stage of selection, all PSUs have been listed in the field at the household level. This provided a sampling frame for selecting the households.

Sample Design: The sample is a two-stage stratified cluster random sample.

Target Population: All Palestinians aged 15 years and above living in the Palestinian Territories, excluding nomads and persons living in institutions such as prisons or shelters.

Stratification: Four levels of stratification were made: 1. Stratification by District. 2. Stratification by place of residence which comprises: (a) Municipalities; (b) Villages; and (c) Refugee Camps 3. Stratification by size of locality. 4. Stratification by cell identification by locality.

Sampling Unit: First stage sampling units are the area units (Cells) in the master sample. The second stage sampling units are households.

Sample Size: The sample size in the eighth round/ first quarter (January 1998 - March 1998) consisted of 7,640 households (about 22,872 persons of working age).

Target cluster size: The next important issue in sample design is the target cluster size or "sample-take," the number of households to be selected per PSU on the average. In this survey persons of working age had been selected from 480 master sample areas. Therefore, the sample take was around 16 households.

Sample Rotation: Each round covered all the 480 master sample areas (except for the first round which covers 5/6 of these, i.e. 480 areas with proportionately increased sample-take per cluster so as to keep the same sample size). Basically, the areas remained fixed over time, but within each area a proportion of the households was replaced each round. During the first phase when the survey was conducted at 6- monthly interval or quarterly surveys were introduced, the same households remain in the sample over 6 consecutive rounds. A high overlap of 5¤6 is then achieved between consecutive rounds (making the sample efficient for monitoring trends), reducing linearly to zero overlap after 6 rounds. In each round, 1 6 (i.e. 80) clusters are listed - i.e. 320 over the whole year as before.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was designed according to the International Labour Organization (ILO) recommendations. The questionnaire includes four main parts: 1. Identification Data: The main objective for this part is to record the necessary information to identify the household, such as, cluster code, sector, type of locality, cell, housing number and the cell code.

1. Quality Control: This part involves groups of controlling standards to monitor the field and office operation, to keep in order the sequence of questionnaire stages (data collection, field and office coding, data entry, editing after entry and store the data).

2. Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level.etc.

3. Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 15 years and over household member, to be able to explore their labour force status and recognize their major characteristics toward employment status, economic activity, occupation, place of work, and other employment indicators.

Response rate

• Response rate in the first quarter was 87.5%

Labour Force Survey 2014, 2nd quarter, Persons with Disabilities.

Based on yearly ad hoc modules to the Labour force survey on persons with disabilities, SSB achive data on their situation at the labour market compared with the whole population. The statistics also give information on changes over time for this group. This data set contains a supplementary survey to the Labor Force Survey in the second quarter of 2014. Corresponding surveys have been conducted annually since 2002.

As of the 1st quarter of 1972, SSB has conducted official quarterly labour force surveys (AKU). These surveys aim to give the labour force authorities (and other people interested) knowledge of the occupational structure of the population and how it develops over time. The surveys are meant to give a foundation and statistical material for occupational prognoses and labour research. The samples in AKU are from 1992 representative at county level. In the period 1972-1991 they were representative on county pair level.

As from January 2006 some major changes were introduced to AKU in order to enhance its comparability to similar surveys in other countries. The changes consist of minor definitional adjustments of unemployment, some adjustments and enlargement of the questionnaire and a change in age definition (age at reference point instead of at the end of the year). Simultaneously the lower age limit to be included in AKU was lowered from 16 to 15 years. This led to some breaks in the time series in the aforementioned areas.

Originally, AKU respondents were interviewed in two consecutive quarters of a year, followed by a pause of two quarters, and then another two quarters of interviews. The sample was approximately 10-11.000 respondents in each quarter up until 1988. Originally, AKU was intended to be an analytical supplement to the monthly occupational statistics that was based on the social security membership index file. However, the social security-based statistics disappeared when the sickness benefit was included in the National Insurance as of 1st of January 1971, and AKU has after gradually developed into the most significant source of knowledge of the state of the labour market and its development.

In 1975, Statistics Norway changed the sampling frame of survey research, see article 37: "Om bruk av stikkprøver ved kontoret for intervjuundersøkelser", SSB (About the Use of Random Samples at the Office for Survey Research, Statistics Norway) by Steinar Tamsfoss, and SØS 33: "Prinsipper og metoder for Statistisk sentralbyrås utvalgsundersøkelse (Principles and Methods for Statistics Norway's sample research) by Ib Thomsen. Simultaneously, the method for estimation of inflation to national numbers was changed, so that reasonable numbers for regions do exist from 1975 and onwards. The change in 1975 led to a different way of interviewing in groups. This caused amongst other things a break with the AKU panel systematics.

In the AKU survey of 1976, a slightly changed questionnaire was introduced. Also, there was a return to the original 6-quarter rotation scheme. The new questionnaire implied a better identification of family workers and persons that are temporarily without paid work. Thus, 30-35 000 more people were defined as employed. The group of "job-seekers without income" were also extended to include persons that were on an involuntary leave of absence. The questions concerning underemployment and "over employment" in the original questionnaire were abandoned.

From the 1st quarter of 1987, the estimation method (inflation to national numbers) was slightly changed. There was also a minor adjustment in the definition of employment. In order to ensure that the numbers were to be comparable to earlier surveys, new versions of the 1980-1986 AKU-files were drawn up. Consequently two versions of the 1980-1987 files - respectively with the old and new methods of estimation - exist. The "old" means that the data are comparable to the original numbers published in the period of 1972 - 1987, whilst the "new" implies that the data are comparable to numbers published after 1987.

Between the 1st and 2nd quarter of 1988, the AKU file description was changed. The variable "Labour-market status" was given a different coding. In addition, adjustments in the data collections were made - from interviewing a specific week every quarter to carry out continuous weekly interviews. In addition, an escalation scheme to increase the sample size was started. This affected the weights, and from the 2nd quarter of 1988, these were recalculated monthly. To balance out the quarterly or yearly files to total national numbers, the monthly weights therefore had to be divided in three or twelve to give the correct total number.

In 1996, AKU was significantly revised: The questionnaire, the file description and the standard for...

Abstract

The main objective of collecting data on the Palestinian labour force 1995 including components of employment, unemployment and underemployment, is to provide basic information on the relative size and structure of the Palestinian labour force. Data collected at different points in time provide a basis for monitoring current trends and changes in the labour market and in employment. These data supported with information on other aspects of the economy provide a basis for the evaluation and analysis of macro-economic policies.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates.

Analysis unit

• Household
• Individual

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame In the absence of a population census since 1967, the major task, with regard to constructing a master sample, was developing a frame of suitable units covering the whole country. Such units have been used as the PSUs (Primary Sampling Units) in the first stage of selection. For the second stage of selection, all PSUs have been listed in the field at the household level. This provided a sampling frame for selecting the households.

Sample Unit First stage sampling units are the erea units in the master sample. the second stage sampling units are households.

Sample Size The sample size is about 7,625 households allowing for non-reponse and related losses. This amounts to a sample of around 26,000 persons of working age for the survey round. The sample size is large enough to provide estimates of the main characteristics of labour force at the national level and for major domains or sub-populations, and also to monitor significant changes in those characteristics (especially after the survey frequency is increased to quaterly rounds).

Stratification Four levels of stratification have been made: - Stratification by District. - Stratification by type of (Locality) which comprises: (a) Municipalities (b)Villages (c)Refugee Camps

• Stratification by locality size.
• Stratification by cell identification in that order.

Sampling deviation

Sample Design The target population: consist of all Palestinian individuals aged 15 years and above living in West Bank and Gaza Strip, excluding nomads and persons living in institutions such as prisons, shelters.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey tool was designed taking into account the Palestinian conditions, international standards, data processing requirements and the comparability of outputs with other related surveys conducted in the West Bank and Gaza Strip. The questionnaire included four parts:

• The first part for recoding necessary elements for survey management and controls;
• The second part for identifying the sample household;
• The third part for recoding the household roster and the demographic characteristics for household members
• The last part for recoding the labour force characteristics for household members in the working age.

Cleaning operations

Editing after data entry In this stage, all questionnaires were edited after data entry in order to minimize errors related data entry.

Data were entered to the computer using a data entry template written in BLAISE. Data entry was organized in one files, corresponding to the main parts of the questionnaire. A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks: logical check, range checks, consisting checks and cross-validation. Complete manual inspection of results after data entry was performed, and questionnaires containing field-related errors were sent back to the field for correction.

Response rate

" The overall response rate for the survey was 87.1%.

Sampling error estimates

Since the data reported here are based on a sample suvrey and not on coplete enumeration, they are subject to two main types of errors: sampling errors and nonsampling errors.

Sampling errors are random outcomes of the sample design, and are, therefore, easily measurable. A description of the estimated variances and the effects of the sample design on sampling errors are provided in the report and Table A. In general, the assessments is that the sample size and sample design provide reliable estimates of the main labour force indicators.

Data appraisal

Detailed information on the data appraisal is available in the Survey Report.

Abstract

The Volunteer Activities Survey (VAS) is a household-based survey conducted by Statistics South Africa (Stats SA). The VAS collects information on the volunteer activities of individuals aged 15 years and older in South Africa. The respondents were selected from households who took part in the second quarter Quarterly Labour Force Survey (QLFS). Volunteer activities covers unpaid non-compulsory work; that is, the time individuals give without pay to activities performed either through an organization or directly for others outside their own household.

Data on volunteering provides important information on skills application, social network development, social capital and quality of life outcomes. The main aim of the survey is to provide information on the scale of volunteer work and bring into view the sizeable part of the labour force that is invisible in existing labour statistics. The objectives of the VAS are:

• To collect reliable data about people who are involved in volunteer activities. • To identify organization-based and direct volunteering. • To give a profile of those engaged in volunteer activities. • To estimate the economic value of volunteer work.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of individuals aged 15 years and older who live in South Africa and who are members of households living in dwellings that have been selected to take part in the second quarter Quarterly Labour Force Survey (QLFS).

Kind of data

Sample survey data [ssd]

Sampling procedure

The Quarterly Labour Force Survey (QLFS) sample frame was used for data collection in the VAS. The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The frame was developed as a general-purpose household survey frame that can be used by all other household surveys irrespective of the sample size requirement of the survey. The sample is based on information collected by Statistics SA during the 2001 Population Census and is designed to be representative at the provincial level and within provinces at the metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal land.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2018 VAS questionnaire consists of the following sections: - Particulars of the dwelling - Households at selected dwelling unit - Response details - Main activities

Abstract

The 1998/99 Integrated Labour Force Survey (ILFS) was the first of its kind to integrate three related surveys (labour force, informal sector and child labour modular surveys) into a single cost-effective survey. It was conducted over the whole country on the household-based NASSEP III sample frame, and covered 11,049 households giving a response rate of 86.2 per cent. As such, the survey collected a wide range of representative information that can be used in the design, implementation, monitoring and evaluation of various policies and programmes. In particular, it provides indicators such as school enrolments rates, housing conditions, access to amenities and facilities, income and expenditures, unemployment rates, and income and expenditure levels which should provide invaluable inputs into the monitoring and evaluation of the economic reforms and poverty reduction programmes that are being implemented by the Government.

The key objectives of the survey were to update data on the labour force, determine the size and output of the informal sector, and estimate the extent of child labour. A rich data bank has been created as a by-product of data processing exercise, which can be used to carry out further analysis of the information collected by the survey.

In designing and implementing the survey, CBS worked closely with other stakeholders through the Inter-Ministerial Steering Committee (IMSC) that was formed to provide overall guidance on the implementation of the survey. The committee was composed of representatives from Ministry of Labour and Human Resource Development, Ministry of Education Science and Technology, and the Macro Planning and Human Resources and Social Services departments in the Ministry of Finance and Planning. A Technical Working Group (TWG) was formed as the survey's secretariat that undertook day-to-day activities on the implementation of the survey.

The Surveyed Population

Age-sex Structure The age-sex pyramid of the surveyed population depicts a youthful population, with those aged below 15 years absorbing 42.3 per cent of the population, leading to a dependency ration of 85.3 per cent. The sex ratio was 0.997 for the whole population and 1.06 at birth (age 0-4). The average household size was 4.2 persons (3.3 persons in urban areas and 4.7 persons in rural areas).

Marital status and migration patterns An estimated 42.7 per cent of the population aged over 12 years had never married. Of those ever married, 51.3 per cent were in current marriage, 3.5 per cent widowed and 3.6 per cent separated or divorced. There was evidence of early marriages where 5.0 percent of the population aged 13-17 reported they were currently married.

Education and Literacy There were 3.6 million children in primary and 0.9 million children in secondary schools, giving gross enrolment ratios of 89.1 percent and 30.7 percent respectively. Student sex ratio, or ratio of males for females, in primary schools was 1.08, while that for secondary schools was 1.20. About 16.4 percent of the Kenyan population aged over 5 years and over reported to have had no formal education at all. Those with primary education constituted 59.0 per cent of the referenced population while 19.7 percent had attained secondary education. Only 1.1 per cent had attained university education.

Housing and amenities About 31.0 per cent of the households had a permanent dwelling unit. Majority of the rural households reported that they owned both the dwelling units they lived in and the land on which it was built, while almost all the urban residents lived in rented dwelling units. About 12.5 per cent of households, mainly in the rural areas, reported they had no toilet facilities. The commonest type of waste disposal was pit latrine, but flush toilet was prevalent in urban areas. Most of the rural households travelled long distances to fetch water, while 80.4 percent of the urban households had water within 50 meters. Firewood was the commonest type of cooking fuel in rural areas, while paraffin (53.3 per cent) and charcoal (22.6 per cent) were the main types of cooking fuels in urban areas. About 77.2 per cent of responding households were using paraffin to light their houses, with 90.5 per cent in rural areas. Urban areas mainly relied on paraffin (50.7 per cent) and electricity (41.8 per cent) as the chief sources of lighting.

Migration Patterns The overall out-migration rate was 13.2 percent, with rural areas losing a large portion of its population to urban areas. Among the eight provinces, Nairobi, Western and Central experienced significant out-migration of over 15.0 percent. Overall, urban areas were net gainers in population flows within the country.

Household expenditure Overall mean monthly expenditure per household amounted to Kshs 6,343. Monthly mean expenditures for rural households were estimated at Kshs 4,101, while the urban equivalent was Kshs 10,826. There were expenditure differentials between male- and female-headed households, where mean monthly expenditures for female-headed households in rural areas was Kshs 2,986, quite below he monthly expenditure of Kshs 4,620 for male-headed households. Similarly, mean expenditure for male-headed households in urban areas was almost twice that of female-headed households.

The Labour Force Participation

Economic activity The results show that there were 15.9 million persons aged 15-64 (the working population) of which 77.4 per cent reported to be economically active. Most of the active population was youth between 24-34 years of age. About 14.6 percent of the economically active were unemployed. Some 3.6 million persons reported to be economically inactive, representing 22.6 per cent of the population aged 15-64 years. Majority of the inactive population was full time students (47.3 per cent). Only 2.0 per cent of the inactive population reported they were out of the labour force because they were retired.

Participation Rates The overall labour force participation rate for the population aged 15 - 64 years stood at 73.6 per cent. Urban areas had higher labour force participation rate of 86.4 per cent compared to rural areas with a rate of 73.8 per cent. Males had a slightly higher participation rate of 74.7 per cent compared to that of females at 72.6 per cent. The results show that participation rates increase along the age spectrum to about 95.2 for the age group 40 - 44 before levelling to 80. 1 per cent for the age cohort 60 - 64. Also, participation rates tend to rise with the level of formal education, rising from 83.7 per cent for those with no education to over 98.8 per cent for those who have completed post-graduate education.

Employment The number of employed persons aged 15-64 years stood at 10.5 million persons, giving employment rate of 85.4 per cent. The overall employment sex ratio was 1.08, but females dominated rural based small-scale farming and pastoralist activities, with a sex ratio of 0.67. Rural area absorbed 70.1 per cent of the employed persons. The working population was largely made up of unpaid family workers (39.6 per cent), mostly working in the rural areas and paid employees, largely concentrated in urban areas (33.4 per cent). Self-employed persons constituted 23.8 per cent of the employed. Of the three sectors of the economy, small-scale farming and pastoralist activities engaged 42.1 per cent of workers. Informal sector and formal or modern sector absorbed 31.6 per cent and 26.3 per cent of the total workforce.

Occupations and industry Most of the employed persons reported to be skilled agricultural and fishery workers (37.3 per cent), largely self-employed based in rural areas. Professionals were mainly in paid employment, and accounted for only 1.2 per cent of the employed persons. The agricultural activities absorbed 63.1 per cent of the employed persons. The other major employers were the service industries with community, social and personal services accounting for 6.1 per cent of the employed. The least popular industries were private households with employed persons, and electricity and water supply. The number of females employed in activities traditionally dominated by males such as construction, mining and quarrying was notably low. However, females were concentrated in agricultural activities, trades, and educational services.

Hours of work Most workers reported 40 working hours per week with a significant proportion of the urban population working above the average hours. Urban workers generally reported to have worked for longer hours than workers in rural areas. Gender analysis shows that females worked for fewer hours than males, particularly in the rural areas. However, females who worked in urban areas (in private households as housemaids) were working quite above 40 hours in a week.

Wage levels Average earnings amounted to KShs 7,766 per month, with the main source of employee's remuneration being basic salary, which formed 81.3 per cent of the overall earnings per person. Earnings in urban were almost double the average earnings in rural areas. There were significant disparities in earnings by gender as females were earnings wages quite below their male counter parts in both rural and urban areas.

Unemployment There were 1.8 million unemployed persons aged 15-64 years, giving an overall unemployment rate of 14.6 per cent. The urban unemployment rate had risen from -- per cent in 1989 to 25.1 per cent by 1999. Like wise, unemployment in the rural areas was high at 9.4 per cent, but less acute then in urban areas. Most of the unemployed were youth and females. Most of the unemployed persons (94.2 per cent) were looking for paid employment during the one-week reference period. It is also worth noting the shift from subsistence farming, as more jobs searchers were ready to start self-employment (mainly found in mostly in the expanding informal sector) than farming activities

The European Union Labour Force Survey (EU-LFS) pilot data collection carried out in 2022 provided information on Digital Platform Employment (DPE).

The DPE statistics provide information on the type of digital platform work or service, encompassing details on working conditions and arrangements. Together with demographic characteristics, such as sex and age, these statistics allow the description of the profile of digital platform workers.

The results of the pilot data collection are published as experimental statistics. In particular, these statistics show the share of digital platform workers among all people aged 15 to 64 , defined as those who have worked for at least one hour through a digital platform in the last 12 months, broken down by type of DPE activity.

For those who reported to be in DPE for at least 1 hour during the last month, indicators on employment characteristics and working arrangements are also presented by:

• number of hours worked,
• share of income from DPE in total income,
• social insurance coverage,
• type of the assignment of the work, service or task,
• degree of autonomy in accepting work or services, deciding on working hours or price setting.

The pilot data collection included 13 variables: see the annexed methodological note.

The experimental statistics tested:

• the conceptual framework and
• the measurement approach to this new form of employment.

The data was collected on a voluntary basis by 17 countries: 16 EU countries and 1 EFTA country. The indicators are presented for an aggregate of 17 countries.

Abstract

The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force. The survey profiles information to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The specific objectives of the survey are as follows: - To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc; - To acquire current information on the dimensions of Pakistan’s labour force; i.e. number of persons employed, unemployed, underemployed or out of labour market; - To gather descriptive facts on the engagement in major occupational trades and the nature of work undertaken by the institution/organization; - To profile statistics on employment status of the individuals, i.e. whether they are employers, own account workers, unpaid family workers or paid employees (regular/casual); - To classify non-agricultural enterprises employing household member(s) as formal and informal; - To put figure on the hours worked at main/subsidiary occupations; - To provide data on wages and mode of payment for paid employees; To quantify occupational health and safety of employed persons by causes, type of injuries/diseases occurred, parts of body injured, type of treatment received and period of absence from work; and - To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

Geographic coverage

The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census, excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population. All enumeration Blocks in urban areas and mouzas/dehs/villages in rural areas have been enumerated. The number of sample households (32,640) enumerated is less than the estimated sample size (32,744) due to non-contact and refusal cases in urban and rural areas.

Analysis unit

Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame

Federal Bureau of Statistics (FBS) has developed its own sampling frame for urban areas. Each city/town is divided into a number of enumeration blocks. Each enumeration block is based on 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks as updated through Economic Census 1999-2000 and the list of villages/mouzas/dehs of 1998 Population Census have been taken as sampling frame. Enumeration blocks and villages are considered as Primary Sampling Units (PSUs) from urban and rural domains respectively.

Stratification Plan: - Urban Domain: Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further substratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame. - Remaining Urban Areas: After excluding the population of large cities from the population of respective ex-administrative division, the remaining urban population of exadministrative division from provinces is grouped together to form another stratum called other urban. Thus each ex-division in remaining urban areas in the four provinces constitutes a stratum - Rural Domain: Each administrative district in the Punjab, Sindh and NWFP is considered an independent stratum whereas in Balochistan, each ex-administrative division constitutes a stratum. - Universe: The universe for Labour Force Survey consists of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census. The universe is adjusted for the extent of coverage.

Sample Design

• Procedure: A stratified two-stage sample design is adopted for the survey.
• Selection of primary sampling units (PSUs): Enumeration blocks in urban domain and mouzas/dehs/villages in rural are taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum have been selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block as updated through Economic Census and respective population of 1998 Census for a stratum is considered as measure of size.
• Selection of secondary sampling units (SSUs): The constituent households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU have been selected with equal probability using systematic sampling technique with random a start.
• Sample Size and Its Allocation: Methodologically, a sample of 32744 households is considered appropriate to provide reliable estimates of key labour force characteristics. The entire sample of households (SSUs) is drawn from 2319 Primary Sampling Units (PSUs) out of which 1090 are urban and 1229 are rural. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. As a means to get reliable estimates, a higher proportion of sample is assigned to NWFP and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately.

Note: More information on the sampling procedure is available in the report extract document available as external resources, and on the PBS website at http://www.pbs.gov.pk/sites/default/files/Labour%20Force/publications/lfs2005_06/methodology.pdf

Mode of data collection

Face-to-face [f2f]

Research instrument

Federal Bureau of Statistics has been carrying out Labour Force Survey (LFS) since 1963. As an ongoing process, the survey’s questionnaire was revised in 1990. Major improvement constituted the addition of probing questions on particular economic activities that tend to go unrecorded with conventional questions, and are mostly carried out by women. The questionnaire was further improved in 1995 to reckon with the size and composition of migration and informal sector. The scope of the survey was extended in 2001-02 to occupational safety and health as well. The questionnaire was further articulated in 2005 for the present LFS 2005-06, the 1st ever held on quarterly basis.

Cleaning operations

Soon after data collection, the supervisors clean, edit and check the filled in questionnaires manually for consistency and completeness and refer back to field where necessary. Editing is done at headquarter by the subject matter section. Computer edit checks are applied to get even with errors identified at the stage of data entry. The relevant numerical techniques are used to eliminate erroneous data resulting from mistakes made during coding. The survey records are further edited and rectified through a series of computer processing stages.

Abstract

The Labor Force Survey (LFS) of Cambodia conducted in November 2000 is the first of the series of nationwide labor force surveys. Its primary purpose was to gather data on labor force and employment levels and structures needed for national accounts estimation. The results of the survey are intended for national account estimation and for providing a quantitative framework for planning and policy formulation affecting the labor market.

Geographic coverage

National, Urban, Rural, All of provinces in Cambodia (24 Provinces)

Analysis unit

Individuals

Universe

The survey covered the members (individuals) from the sample households of resident households in Cambodia:

1. All members for geographic part from the sample households of resident households

2. All members aged 10 and over for education and labour force parts from the sample households of resident households

Kind of data

Sample survey data [ssd]

Sampling procedure

The LFS adopts a stratified two-stage systematic sampling design with villages as the primary sampling units (PSUs) and households as secondary sampling units (SSUs). In each village, a systematic sample of 10 households were taken.

The sample consisted of 500 villages sampled from the truncated 1999 CSES sampling frame. Then from each sample village, a fix sample of 10 households was taken using circular systematic sampling with random start. It covered 500 sample villages or a total of 5000 sample households nationwide

Mode of data collection

Face-to-face [f2f]

Research instrument

The following are the LFS forms used during the field enumeration and a brief outline of the fieldwork procedures:

2.1 Listing Sheet (LFS Form 1)

This is a sheet containing a list the buildings, housing units and households within an enumeration area (EA). Other information pertaining to population of households were also recorded.

Listing sheet was used to record all households in the village or part thereof selected for household enumeration. The current list of households was necessary for sampling households and also as an input to derive household weights

2.2 Questionnaire (LFS Form 2)

This is the form used for interviewing and recording information about a household. This questionnaire also contains information on the demographic and economic characteristics of the population.

1. Part I - For all persons

   a) Relationship to Household Head

   b) Age

   c) Sex

2. Part II - For Persons 10 Years and Over

   a) Education (Current School Attendance and Highest Educational Attainment)

   b) Current Activity (Past Week)

   c) Primary Occupation

   d) Economic Activity or Industry

   e) Nature and Status of Employment

   f) Remuneration, Earnings and Commissions Received

   g) Hours Worked

   h) Availability for /Seeking Additional Work

   i) Reasons for not Being Available for Work

Cleaning operations

All completed questionnaires were brought to NIS for processing. Although completed questionnaires were checked and edited by supervisors in the field, specially because of the length of questionnaires and the complexity of the topics covered the need for manual editing and coding by trained staff was accepted as an essential priority activity to produce a cleaned data file without delay. In all 4 staff comprising 3 processing staff and 1 supervisor were trained for two days by the project staff. An instruction manual for manual editing and coding was prepared and translated into Khmer for the guidance of processing staff.

In order to produce an unedited data file, keying in the data as recorded by field enumerators and supervisors, (without subjecting data to manual edit as required by the Analysis Component Project staff), it was necessary to structure manual editing as a two-phase operation. Thus in the first phase, the processing staff coded the questions such as those industry, and occupation which required coding. Editing was restricted to selected structural edits and some error corrections. These edits were restricted to checking the completeness and consistency of responses, legibility, and totaling of selected questions. Error corrections were made without canceling or obliterating the original entry made by the enumerator, by inserting the correction close to the original entry.

Much of the manual editing was carried out in the second phase, after key entry and one hundred percent verification and extraction of error print outs. A wide range of errors had to be corrected which was expected in view of the complexity of the survey and the skill background of the enumeration and processing staff. The manual edits involved the correction of errors arising from incorrect key entry, in-correct/ failure to include identification, miss-coding of answers, failure to follow skip patterns, misinterpretation of measures, range errors, and other consistency errors.

Response rate

Despite the length of the questionnaire, the respondents cooperated with the survey staff and provided answers to both questionnaires and it was possible to achieve a 100% response rate. At this stage it is not possible to comment on item non-response, and completeness of information provided by the respondents, and the respondent's fatigue arising from the length of the interviews which may have had a bearing on these issues.

Sampling error estimates

Sampling errors are those that are related to the size of the sample and the kind of samples selected. Non-sampling errors are those such as arising from errors committed by the interviewers in recording information, response errors and encoding or processing errors.

The results obtained from the survey are subject to sampling errors. Sampling errors in surveys occur as a result of limiting the survey observations to a subset rather than the whole population. These errors are related to the sample size selected and sampling design adopted in the survey. In order to maintain these errors within acceptable levels, the efficient sampling design with the sample allocation described earlier was adopted.

In addition to sampling errors, the estimates are also subject to non-sampling errors that arise in different stages of any survey operation. These include errors that are introduced at the preparatory stage errors committed during data collection including those committed by interviewers and respondents processing errors

The first item includes errors arising from questionnaire design, preparation of definitions and instructions, preparation of table formats etc. The other two categories are clear from the terminology used. The use of trained enumerators and processing staff and careful organization and thorough supervision are essential to control and minimize these errors.

As already referred to, it was possible to obtain responses from all the villages and

households that were sampled, and thus it was not necessary to adjust the data for non-response. Thus the bias that is introduced into the estimates as a result of non-response was avoided.

Abstract

The National Bureau of Statistics (NBS) has enhanced its methodology of collecting labour market data through the Nigeria Labour Force Survey (NLFS) in line with International Labour Organisation (ILO) guidelines.The data collection for the revised NLFS is based on a sample of 35,520 households nationwide of which 8,880 were selected quarterly. It is conducted continuously throughout the year, with national-level results produced quarterly and state-level results at the end of a full year.

About three-quarter of working-age Nigerians were employed - 73.6% in Q4 2022.This shows that most people were engaged in some type of jobs for at least one hour in a week, for pay or profit.About one-third (36.4% in Q4 2022) of employed persons worked less than 40 hours per week in this quarter. This was most common among women, individuals with lower levels of education, young people, and those living in rural areas.Underemployment rate which is a share of employed people working less than 40 hours per week and declaring themselves willing and available to work more was 13.7% in Q4 2022.The share of wage employment was 13.4% in Q4 2022 .Most Nigerians operate their own businesses or engaged in farming activities with 73.1% in Q4 2022.

Furthermore, 10.7% in Q4 2022 were engaged helping (without pay or profit) in a household businesses. In Q4 2022, 2.6% were engaged as Apprentices/Interns.Unemployment stood at 5.3% in Q4 2022 and this aligns with the rates in other developing countries where work, even if only for a few hours and in low-productivity jobs, is essential to make ends meet, particularly in the absence of any social protection for the unemployed.22.3% of the working age population were out of labour force in Q4 2022 while the rate of informal employment among the employed Nigerians was 93.5%.

Geographic coverage

National Zone State Sector

Analysis unit

Individual

Universe

Household Members

Kind of data

Sample survey data [ssd]

Sampling procedure

The National frame of EAs demarcated for the forthcoming Housing and Population Census was used to select the study units.A household listing exercise was carried out on quarterly basis to update the sampling frame from which households were selected for interview. A two-stage cluster sampling design was adopted for this survey. The first was the selection of Enumeration Areas while,the second was the selection of households.

First Stage Selection Ninety Six (96) EAs was selected in each State in which 24 EAs was canvassed quarterly in each State Nationally, a total of 3,552 EAs was covered in the 36 States of the Federation and FCT .

For the Second Stage Selection, 10 HHs were systematically selected per EA. In each State, 240 HHs were interviewed in every quarter.Nationally, a total of 35,520 HHs will be covered while 8,880 were covered quarterly.All eligible household members aged 15 years and above were interviewed.

Sampling deviation

No Deviations

Mode of data collection

Face-to-face [f2f]

Research instrument

A structured questionnaire was used for NLFS. A household questionnaire was administered in each household, which collected various information on Identification, Demographic Characteristics, Education, Employed at work,Temporarily absence, Agricultural work and Market Orientation, Characteristics of main and secondary job, Unemployent and out of labour.Some of the questions were administered at household level while others were at individual level.

Cleaning operations

Real - Time data editing took place at different stages throughout the processing which includes: 1) Data editing and cleaning 2) Structure checking and completeness 3) Secondary editing 4) Structural checking of data files

Response rate

The household response rate is 98.9%.

Sampling error estimates

The margin of error of each quarter is 1% for national estimates.

Data appraisal

A series of data quality tables and graphs are available in the reports.

The Current Population Survey (CPS) is the primary source of labor force statistics for the U.S. population. It is the source of numerous high-profile economic statistics, including the national unemployment rate, and provides data on a wide range of issues relating to employment and earnings. The CPS also collects extensive demographic data that complement and enhance our understanding of labor market conditions in the nation. The survey is jointly sponsored by the U.S. Census Bureau and the Bureau of Labor Statistics (BLS).