In 2023, Indonesia's labor force participation rate was around **** percent. The labor force participation rate in the country has been slowly increasing over the past few years.
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The global market size of Labor is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Labor Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Labor industry. The key insights of the report:
1.The report provides key statistics on the market status of the Labor manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Labor industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Labor Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Labor as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share
For product type segment, this report listed main product type of Labor market
* Product Type I
* Product Type II
* Product Type III
For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III
For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.
Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.
Represents a comprehensive collection of occupational wage data available for Pennsylvania. Data are collected through the Occupational Employment Statistics program in cooperation with the U.S. Department of Labor’s Bureau of Labor Statistics. Occupational wage information can be used as a reference by educators, PACareerLink® staff, career counselors, Workforce Development Boards, economic developers, program planners, and others.
Technical Note Occupational wages do not represent a time series. Due to the prescribed production methodology, current occupational wages are not comparable to previously published occupational wages.
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 CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)
In any society, the human element represents the basis of the work force which exercises all the service and production activities. Therefore, it is a mandate to produce labor force statistics and studies, that is related to the growth and distribution of manpower and labor force distribution by different types and characteristics.
In this context, the Central Agency for Public Mobilization and Statistics conducts "Quarterly Labor Force Survey" which includes data on the size of manpower and labor force (employed and unemployed) and their geographical distribution by their characteristics.
By the end of each year, CAPMAS issues the annual aggregated labor force bulletin publication that includes the results of the quarterly survey rounds that represent the manpower and labor force characteristics during the year.
---> Historical Review of the Labor Force Survey:
1- The First Labor Force survey was undertaken in 1957. The first round was conducted in November of that year, the survey continued to be conducted in successive rounds (quarterly, bi-annually, or annually) till now.
2- Starting the October 2006 round, the fieldwork of the labor force survey was developed to focus on the following two points: a. The importance of using the panel sample that is part of the survey sample, to monitor the dynamic changes of the labor market. b. Improving the used questionnaire to include more questions, that help in better defining of relationship to labor force of each household member (employed, unemployed, out of labor force ...etc.). In addition to re-order of some of the already existing questions in much logical way.
3- Starting the January 2008 round, the used methodology was developed to collect more representative sample during the survey year. this is done through distributing the sample of each governorate into five groups, the questionnaires are collected from each of them separately every 15 days for 3 months (in the middle and the end of the month)
4- Starting the January 2012 round, in order to follow the international recommendation, to avoid asking extra questions that affect the precision and accuracy of the collected data, a shortened version of the questionnaire was designed to include the core questions that enable obtaining the basic Egyptian labor market indicators. The shortened version is collected in two rounds (January-March), (April-June), and (October-December) while the long version of the questionnaire is collected in the 3rd round (July-September) that includes more information on housing conditions and immigration.
---> The survey aims at covering the following topics:
1- Measuring the size of the Egyptian labor force among civilians (for all governorates of the republic) by their different characteristics. 2- Measuring the employment rate at national level and different geographical areas. 3- Measuring the distribution of employed people by the following characteristics: Gender, age, educational status, occupation, economic activity, and sector. 4- Measuring unemployment rate at different geographic areas. 5- Measuring the distribution of unemployed people by the following characteristics: Gender, age, educational status, unemployment type “ever employed/never employed”, occupation, economic activity, and sector for people who have ever worked.
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.
Covering a sample of urban and rural areas in all the governorates.
1- Household/family. 2- Individual/person.
The survey covered a national sample of households and all individuals permanently residing in surveyed households.
Sample survey data [ssd]
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 CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)
---> Sample Design and Selection
At the beginning of the first quarter in 2018 (January-March),the sample design was developed. sample size was withdrawn 50% of the (panel households) visited in the same quarter last year and 50% of the sample size (new households) visited for the first time, as well as to divide the sample of each governorate into six parts instead of five , in addition to Develop research questions according to the goals of Nineteenth Congress of Labor Statistics held at Geneva in 2013, therefore new questions to measure informal employment and the informal sector. An application for the new questionnaire has been designed and implemented on the tablet, Entry application has been designed for the new questionnaire so that the question will be completed on the field and then The data is entered through the researchers at the offices, correcting the errors first-hand and returning to the family again and sending data daily.
The sample of Labor Force Survey is a two-stage stratified cluster sample and selfweighted to the extent practical.
The main elements of the sampling design are described as follows:
Sample Size The sample size in each quarter is 22,626 households with a total number of 80804 households annually. These households are distributed on the governorate level (urban/rural), according to the estimated number of households in each governorate in accordance with the percentage of urban and rural population in each governorate.
Cluster size The cluster size is 18 households.
Sampling stages:
(1) Primary Sampling Unit (PSU): The 2006 Population Census provided sufficient data at the level of the Enumeration Area (EA). Hence, the electronic list of EA's represented the frame of the first stage sample; in which the corresponding number of households per EA was taken as a measure of size. The size of an EA is almost 200 households on average, with some variability expected. The size of first stage national sample was estimated to be 5,024 EA.
(2) Sample Distribution by Governorate: The primary stratifying variable is the governorate of residence, which in turn is divided into urban and rural sub-strata, whenever applicable.
(3) First Stage Sample frame: The census lists of EAs for each substratum, associated with the corresponding number of households, constitute the frame of the first stage sample. The identification information appears on the EA's list includes the District code, Shiakha/Village code, Census Supervisor number, and Enumerator number. Prior to the selection of the first stage sample, the frame was arranged to provide implicit stratification with regard to the geographic location. The urban frame of each governorate was ordered in a serpentine fashion according to the geographic location of kism/ district capitals. The same sort of ordering was made on the rural frame, but according to the district location. The systematic selection of EA's sample from such a sorted frame will ensure a balanced spread of the sample over the area of respective governorates. The sample was selected with Probability Proportional to Size (PPS), with the number of census households taken as a Measure of Size (MOS).
(4) Core Sample allocation The core sample EAs (5,024) were divided among the survey 4 rounds, each round included 1,257 EAs (565 in urban areas and 692 in rural areas).
A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.
Face-to-face [f2f]
The questionnaire design follows the latest International Labor Organization (ILO) concepts and definitions of labor force, employment, and unemployment.
The questionnaire comprises 4 tables in addition to the identification and geographic data of household on the cover page.
---> Table 1- The housing conditions of the households
This table includes information on the housing conditions of the household: - Type of the dwelling, - Tenure of the dwelling (owned/rent) , - Availability of facilities and services connected to the house - Ownership of durables.
---> Table 2- Demographic and employment characteristics and basic data for all household individuals
Including: gender, age, educational status, marital status, residence mobility and current work status
---> Table 3- Employment characteristics table
This table is filled by employed individuals at the time of the survey or those who were engaged to work during the reference week, and provided information on: - Relationship to employer: employer, self-employed, waged worker, and unpaid family worker - Economic activity - Sector - Occupation - Effective working hours - Health and social insurance - Work place - Contract type - Average monthly wage
---> Table 4- Unemployment characteristics table
This table is filled by all unemployed individuals who satisfied the unemployment criteria, and provided information on:
Focuses mainly on labor force key indicators, main characteristics of the employed, unemployed, underemployed and persons outside the labor force, labor force according to level of education, distribution of the employed population by occupation, economic activity, place of work, employment status, hours and days worked and average daily wage in NIS for the employees.
The data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates.
Household, Individual.
The survey covered all the Palestinian persons aged 10 years and above who are usual residents in the State of Palestine.
Sample survey data [ssd]
The sample of this survey is implemented periodically every quarter by PCBS since 1995, so this survey is implemented every quarter of the year (distributed over 13 weeks).
The sample is a two stage stratified cluster sample with two stages: - First stage: we selected a systematic random sample of 536 enumeration areas for the whole round, and excluded enumeration area that contain less that 40 households. - Second stage: we selected a random area sample of average 16 households from each enumeration area selected in the first stage, from each region where the number of households counted 80 households or more; while enumeration areas containing less than 80 households we selected 8 households.
The estimated sample size in the first quarter is 7,452 households, 7,597 households in the second quarter, while 7,750 households in the third, and 7,703 households in the fourth quarter.
Computer Assisted Personal Interview [capi]
The labor force survey questionnaire consists of four main sections:
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.
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).
Household Roster: This part involves demographic characteristics about the household, like number of persons in the household, date of birth, sex, educational level, etc.
Employment Part: This part involves the major research indicators, where one questionnaire had been answered by every 10 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.
All questionnaires were edited after data entry in order to minimize errors related data entry.
The response rate was 85.4% in 2018, and in quarters: - First quarter 2018: 85.9% - Second quarter 2018: 85.4% - Third quarter 2018: 84.7% - Fourth quarter 2018: 85.4%
Data of this survey affected by sampling errors due to use of the sample and not a complete enumeration. Therefore, certain differences are expected in comparison with the real values obtained through censuses. Variance were calculated for the most important indicators, the variance table is attached with the final report (found under downloads). There is no problem to disseminate results at the national level and at the level of governorates of the West Bank and Gaza Strip.
The concept of data quality encompasses various aspects, started with planning of the survey to how to publish, understand and benefit from the data. The most important components of statistical quality elements are accuracy, comparability and quality control procedures
This statistic shows the annual percentage change of the unit labor costs in Belgium from 2018 to 2020, with a forecast for 2021 to 2023. As of 2020, the annual percentage change of the unit labor costs was *** percent. Furthermore, it was forecast that this percent change would decrease by *** percent in 2021.
This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.
The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.
The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.
National coverage.
There are six statistical regions known as Division's in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'pai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks. The sample for the 2018 Labour Force Survey (LFS) was designed to cover at least 2500 employed population aged 10 years and over from all the regions. This was made mainly to have sufficient cases to provide information on the employed population.
Population living in private households in Tonga. The labour force questionnaire is directed to the population aged 10 and above. Disability short set of questions is directed to all individuals age 2 and above and the food insecurity experience scale is directed to the head of household.
Sample survey data [ssd]
2018 Tonga Labour force survey aimed at estimating all the main ILO indicators at the island group level (geographical stratas). The sampling strategy is based on a two stages stratified random survey.
15 households per block are randomly selected using uniform probability
The sampling frame used to select PSUs (census blocks) and household is the 2016 Tonga population census.
The computation of sample size required the use of: - Tonga 2015 HIES dataset (labour force section) - Tonga 2016 population census (distribution of households across the stratas) The resource variable used to compute the sample size is the labour force participation rate from the 2015 HIES. The use of the 2015 labour force section of the Tonga HIES allows the computation of the design effect of the labour force participation rate within each strata. The design effect and sampling errors of the labour force participation rate estimated from the 2015 HIES in combination with the 2016 household population distribution allow to predict the minimum sample size required (per strata) to get a robust estimate from the 2018 LFS.
Total sample size: 2685 households Geographical stratification: 6 island groups Selection process: 2 stages random survey where census blocks are selected using Probability Proportional to Size (Primary Sampling Unit) in the first place and households are randomly selected within each selected blocks (15 households per block) Non response: a 10% increase of the sample happened in all stratas to account for non-response Sampling frame: the household listing from the 2016 population census was used as a sampling frame and the 2015 labour force section of the HIES was used to compute the sample size (using labour force participation rate.
No major deviation from the original sample has taken place.
Computer Assisted Personal Interview [capi]
The 2018 Tonga Labour Force Survey questionnaire included 15 sections:
IDENTIFICATION SECTION B: INDIVIDUAL CHARACTERISTICS SECTION C: EDUCATION (AGE 3+) SECTIONS B & C: EMPLOYMENT IDENTIFICATION AND TEMPORARY ABSENCE (AGE 10+) SECTION D: AGRICULTURE WORK AND MARKET DESTINATION SECTION E1: MAIN EMPLOYMENT CHARACTERISTICS SECTION E2: SECOND PAID JOB/ BUSINESS ACTIVITY CHARACTERISTICS SECTION F: INCOME FROM EMPLOYMENT SECTION G: WORKING TIME SECTION H: JOB SEARCH SECTION I: PREVIOUS WORK EXPERIENCE SECTION J: MAIN ACTIVITY SECTION K: OWN USE PRODUCTION WORK FOOD INSECURITY EXPERIENCES GPS + PHOTO
The questionniares were developed and administered in English and were translated into Tongan language. The questionnaire is provided as external resources.
The draft questionnaire was pre-tested during the supervisors training and during the enumerators training and it was finally tested during the pilot test. The pilot testing was undertaken on the 27th of May to the 1st of June 2018 in Tongatapu Urban and Rural areas. The questionnaire was revised rigorously in accordance to the feedback received from each test. At the same time, a field operations manual for supervisors and enumerators was prepared and modified accordingly for field operators to use as a reference during the field work.
The World Bank Survey Solutions software was used for Data Processing, STATA software was used for data cleaning, tabulation tabulation and analysis.
Editing and tabulation of the data will be undertaken in February/March 2019 in collaboration with SPC and ILO.
A total, 2,685 households were selected for the sample. Of these existing households, 2,584 were successfully interviewed, giving a household response rate of 96.2%.
Response rates were higher in urban areas than in the rural area of Tongatapu.
-1 Tongatapu urban: 97.30%
-2 Tongatapu rural: 93.00%
-3 Vava'u: 100.00%
-4 Ha'pai: 100.00%
-5 Eua: 95.20%
-6 Niuas: 80.00%
-Total: 96.20%.
Sampling errors were computed and are presented in the final report.
The sampling error were computed using the survey set package in Stata. The Finite Population Correction was included in the sample design (optional in svy set Stata command) as follow: - Fpc 1: total number of census blocks within the strata (variable toteas) - Fpc 2: Here is a list of some LF indicators presented with sampling error
-RSE: Labour force population: 2.2% Employment - population in employment: 2.2% Labour force participation rate (%): 1.7% Unemployment rate (%): 13.5% Composite rate of labour underutilization (%): 7.3% Youth unemployment rate (%): 18.2% Informal employment rate (%): 2.7% Average monthly wages - employees (TOP): 12%.
-95% Interval: Labour force population: 28,203 => 30,804 Employment - population in employment: 27,341 => 29,855 Labour force participation rate (%): 45.2% => 48.2% Unemployment rate (%): 2.2% => 3.9% Composite rate of labour underutilization (%): 16% => 21.4% Youth unemployment rate (%): 5.7% => 12.1% Informal employment rate (%): 44.3% => 49.4% Average monthly wages - employees (TOP): 1,174 => 1,904.
The metadata set does not comprise any description or summary. The information has not been provided.
The table Labor force data by county, 2018 annual averages is part of the dataset Local Area Unemployment Statistics **, available at https://redivis.com/datasets/gqcs-0rrxw8r6h. It contains 3221 rows across 9 variables.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Indonesia Labour Wages: Housekeeper: per Month: Real: 2018 Base data was reported at 384,855.000 IDR in Dec 2022. This records a decrease from the previous number of 387,100.000 IDR for Nov 2022. Indonesia Labour Wages: Housekeeper: per Month: Real: 2018 Base data is updated monthly, averaging 398,407.500 IDR from Jan 2020 (Median) to Dec 2022, with 36 observations. The data reached an all-time high of 401,916.000 IDR in Jan 2020 and a record low of 384,855.000 IDR in Dec 2022. Indonesia Labour Wages: Housekeeper: per Month: Real: 2018 Base data remains active status in CEIC and is reported by Statistics Indonesia. The data is categorized under Global Database’s Indonesia – Table ID.GBB001: Labor Wage: by Occupation.
National coverage
households/individuals
survey
Quarterly: average based on 3 monthly data points
Sample size:
Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically
Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
License information was derived automatically
The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job’s issues – occupation, sector of economic activity, hours worked, contracts’ type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of the population. This database is the result of the union of the four quarterly datasets for the year 2018. In this way, it is possible to calculate the annual estimations at the national, macro-regional and regional levels. The documentation available on this page refers to the survey conducted in the last quarter. For more information, please refer to the pages of the individual quarterly surveys of 2018: Italian Labour Force Survey – January (2018) Italian Labour Force Survey – April (2018) Italian Labour Force Survey – July (2018) Italian Labour Force Survey – October (2018) 64,018 households, 374,790 individuals. Two-stage stratified random sample Computer-Assisted Telephone Interviewing (CATI) Computer-Assisted Personal Interviewing (CAPI)
"The Egypt Labor Market Panel Survey, carried out by the Economic Research Forum (ERF) in cooperation with Egypt’s Central Agency for Public Mobilization and Statistics (CAPMAS). Over its twenty-year history, the ELMPS has become the mainstay of labor market and human development research in Egypt, being the first and most comprehensive source of publicly available micro data on the subject.
The 2018 wave of the Egypt Labor Market Panel Survey (ELMPS) is the fourth wave of a longitudinal survey carried out by the Economic Research Forum (ERF) in cooperation with the Egyptian Central Agency for Public Mobilization and Statistics (CAPMAS). The 2018 wave follows previous waves in 1998, 2006 and 2012. Over its twenty-year history, the ELMPS has become the mainstay of labor market and human development research in Egypt, being the first and most comprehensive source of publicly available micro data on the subject.
The ELMPS is a wide-ranging, nationally representative panel survey that covers topics such as parental background, education, housing, access to services, residential mobility, migration and remittances, time use, marriage patterns and costs, fertility, women’s decision making and empowerment, job dynamics, savings and borrowing behavior, the operation of household enterprises and farms, besides the usual focus on employment, unemployment and earnings in typical labor force surveys. ELMPS 2018 also provided more detailed information on health, gender role attitudes, food security, hazardous work, community infrastructure and the cost of housing. It incorporated specific questions on vulnerability, coping strategies and access to social safety net programs. (Krafft, C, Assaad, R., and Rahman, K .,2019)
In addition to the survey’s panel design, which permits the study of various phenomena over time, the survey also contains a large number of retrospective questions about the timing of major life events such as education, residential mobility, jobs, marriage and fertility. The survey provides detailed information about place of birth and subsequent residence, as well information about schools and colleges attended at various stages of an individual’s trajectory, which permit the individual records to be linked to information from other data sources about the geographic context in which the individual lived and the educational institutions s/he attended.
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For details on the the key characteristics of the ELMPS 2018, see: Krafft, C., Assaad, R., and Rahman, K. (2019) . Introducing the Egypt Labor Market Panel Survey 2018. Economic Research Forum Working Paper No. 1360
Regions:
Greater Cairo
Alexandria and Suez Canal
Urban Lower Egypt
Urban Upper Egypt
Rural Lower Egypt
For detailed information on the regions and governorates used in the ELMPS 2018 Sample, see: Krafft, C., Assaad, R., and Rahman, K. (2019) . Introducing the Egypt Labor Market Panel Survey 2018. Economic Research Forum Working Paper No. 1360
1- Households. 2- Individuals. 3- Enterprises.
The survey covered a national sample of households and all households members aged 6 and above. In addition to Enterprises operated by the household.
Sample survey data [ssd]
"As a longitudinal survey, the ELMPS attempts to track households included in the previous waves and interview all their remaining and new members. The survey also tries to locate any individuals who may have split from these households between waves, and attempts to interview them, as well as any other individuals found in the households they formed or joined.
In every wave of the survey, a refresher sample of 2,000-3,000 households is added to maintain the representativeness of the overall sample and to allow for a more in-depth examination of phenomena of interest. The focus we selected for the 2018 wave of the ELMPS was economic vulnerability among Egypt's poorest communities. Accordingly, we added a refresher sample of 2,000 households that oversampled rural communities that were among the "1,000 poorest villages" of Egypt, as ascertained by the most recent national poverty map available to us.
The final sample included 15,746 households and 61,231 individuals. Of these households, 13,793 households included members from 2012 (10,042 panel and 3,751 split households) and 1,953 were refresher households. Among individuals, 53,040 were in households that included at least one individual interviewed in 2012 (i.e., either panel or split households), while 8,191 were in refresher households. Of the 49,186 individuals included in the 2012 sample, 39,153 (79.6%) were successfully re-interviewed in 2018.
Of the 37,140 individuals in the 2006 sample, 22,901 (61.7%) were successfully tracked over three waves. Finally, of the 23,997 individuals included in the 1998 wave, 10,145 (42.3%) were successfully tracked over four waves. We present a detailed discussion of sample attrition patterns in Section 2 and the creation of weights to address such attrition in Section 3. We also discuss the design of the refresher sample and the calculation of the weights for it. In the subsequent section, we compare the (weighted) results of the ELMPS on key demographic and labor market indicators to those of other data sources, namely Egypt's 2017 Census and various rounds of the LFS. First, however, we discuss the design of the questionnaires, sample, and fielding practices." (Krafft, C., Assaad, R., and Rahman, K. ,2019)
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For details on The Pattern of Attrition from 2012 to 2018, see: Krafft, C., Assaad, R., and Rahman, K. (2019) . Introducing the Egypt Labor Market Panel Survey 2018. Economic Research Forum Working Paper No. 1360
Face-to-face [f2f]
"Each wave of the survey attempts to maintain consistency for the indicators measured in previous waves while adding additional modules and questions to examine new issues or allow more in-depth examination of existing issues. Accordingly, the 2018 wave devoted more attention to the measurement of the instability of employment, focusing in particular on job turnover among casual workers. It also provided more detailed information on health, gender role attitudes, food security, hazardous work, community infrastructure and the cost of housing. It incorporated specific questions on vulnerability, coping strategies and access to social safety net programs.
The 2018 wave has two primary questionnaires, a household questionnaire and an individual questionnaire. The modules in these two questionnaires are;
A) The household questionnaire includes; Statistical Identification; Tracking Splits, Individual Roster; Housing Information; Current Migrants; Transfers from Individuals; Other Sources of Income; Shocks and Coping; Household Non-Farm Activities; Agriculture Assets: Lands; Agriculture Assets: Livestock/Poultry; Agriculture Assets: Equipment; Agricultural Crops and Other Agricultural Income.
B) The individual questionnaire includes; Statistical Identification; Residential Mobility; Father's Characteristics; Mother's Characteristics; Siblings; Health; Education; Past Seven Days Subsistence & Domestic Work; Employment in the Past Seven Days; Unemployment; Employment in the Past Three Months; Characteristics of Main Job; Secondary Job; Labor Market History; Marriage; Fertility; Female Employment; Earnings; Earnings in Secondary Job; Return Migration; Information Technology; Savings & Borrowing and Attitudes.
They are for the most part the same as those in the previous waves of the survey with a few exceptions. The “tracking splits” module in the household questionnaire allows interviewers to ascertain whether the composition of the household has changed since the 2012 wave and inquire about new members present in the household as well as those who may have split to form new households. The “shocks and coping module” is also new in the 2018 wave and enquires about both idiosyncratic and community level shocks that the household may have been exposed to, household food security, and coping mechanisms that the household may have used to respond to shocks. The main changes in the individual questionnaire relative to the 2012 wave were a substantial expansion of the health module, a reconfiguration of the labor market history module to better capture past periods of non-employment7 and the addition of a module on attitudes." (Krafft, C., Assaad, R., and Rahman, K. ,2019)
.. Visit https://dataone.org/datasets/sha256%3A7a4cbcab15f9af70e8018e6c17bb8e625d97af8510f66d0a9b9c2fad721d1ffc for complete metadata about this dataset.
https://dataverse.theacss.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.25825/FK2/RT8OWPhttps://dataverse.theacss.org/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.25825/FK2/RT8OWP
The Egypt Labor Market Panel Survey, carried out by the Economic Research Forum (ERF) in cooperation with Egypt’s Central Agency for Public Mobilization and Statistics (CAPMAS). Over its twenty-year history, the ELMPS has become the mainstay of labor market and human development research in Egypt, being the first and most comprehensive source of publicly available micro data on the subject. The 2018 wave of the Egypt Labor Market Panel Survey (ELMPS) is the fourth wave of a longitudinal survey carried out by the Economic Research Forum (ERF) in cooperation with the Egyptian Central Agency for Public Mobilization and Statistics (CAPMAS). The 2018 wave follows previous waves in 1998, 2006 and 2012. Over its twenty-year history, the ELMPS has become the mainstay of labor market and human development research in Egypt, being the first and most comprehensive source of publicly available micro data on the subject. The ELMPS is a wide-ranging, nationally representative panel survey that covers topics such as parental background, education, housing, access to services, residential mobility, migration and remittances, time use, marriage patterns and costs, fertility, women’s decision making and empowerment, job dynamics, savings and borrowing behavior, the operation of household enterprises and farms, besides the usual focus on employment, unemployment and earnings in typical labor force surveys. ELMPS 2018 also provided more detailed information on health, gender role attitudes, food security, hazardous work, community infrastructure and the cost of housing. It incorporated specific questions on vulnerability, coping strategies and access to social safety net programs. (Krafft, C, Assaad, R., and Rahman, K .,2019) In addition to the survey’s panel design, which permits the study of various phenomena over time, the survey also contains a large number of retrospective questions about the timing of major life events such as education, residential mobility, jobs, marriage and fertility. The survey provides detailed information about place of birth and subsequent residence, as well information about schools and colleges attended at various stages of an individual’s trajectory, which permit the individual records to be linked to information from other data sources about the geographic context in which the individual lived and the educational institutions s/he attended. The data may be accessed through the ERF Data Portal: http://www.erfdataportal.com/index.php/catalog/157
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Taiwan Labor Cost Index: Mfg: Textiles Mills data was reported at 110.750 2011=100 in Apr 2018. This records an increase from the previous number of 105.130 2011=100 for Mar 2018. Taiwan Labor Cost Index: Mfg: Textiles Mills data is updated monthly, averaging 82.940 2011=100 from Jan 1982 (Median) to Apr 2018, with 436 observations. The data reached an all-time high of 264.830 2011=100 in Jan 2009 and a record low of 58.720 2011=100 in Mar 1982. Taiwan Labor Cost Index: Mfg: Textiles Mills data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G046: Unit Output Labour Cost Index: 2011=100.
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United States Labour Force Participation Rate: Male: Age 35 to 39 data was reported at 91.400 % in Oct 2018. This records an increase from the previous number of 91.000 % for Sep 2018. United States Labour Force Participation Rate: Male: Age 35 to 39 data is updated monthly, averaging 93.100 % from Jun 1976 (Median) to Oct 2018, with 509 observations. The data reached an all-time high of 96.700 % in Oct 1977 and a record low of 89.700 % in Feb 2015. United States Labour Force Participation Rate: Male: Age 35 to 39 data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G008: Current Population Survey: Labour Force.
The Labour Force Survey collects data on the economically active population or labour force in the country, according to the recommendations of ILO (International Labour Organisation) and the recommendations of the European Statistical Office (Eurostat). The labour force consists of all persons in employment or looking for work in order to earn a livelihood. Therefore, the main categories to examine are: total employment, unemployment, and demographic, geographic, socio-economic and other characteristics of individuals that are in each of these categories.
The main objective of the survey is, based on the results, to determine the basic categories that make up the labour force of the country in a way that allows the use of modern methods of analysis of any scientific field: economics, sociology, psychology, etc. One of the objectives of the survey is to define total employment and unemployment in accordance with international standards so that these categories can be compared with similar occurrences in other countries, especially in European countries.
The procedure for sample selection and the design of the questionnaire are based on the recommendations of the International Labour Organisation and the recommendations of Eurostat.
National
The unit of observation is the household and everyone in it.
Sample survey data [ssd]
The survey is conducted throughout the Republic of Macedonia. The basis for selection of the sample is the Census of Population, Households and Dwellings 2002. The selection of the sample households is conducted in two stages.
The first step is choosing enumeration districts, proportional to the population aged 15-79 years in the eight regions (Skopje, Pelagonia, Vardar, Northeast, Southwest, Southeast, Polog and East regions) and by type of settlement (city or other). In the second stage, 11250 addresses or households living at those addresses are randomly selected from the chosen enumeration districts. Selected households represent about 2% of the total number of households in the country. According to the rotation pattern 2-2-2, each household will be surveyed in two consecutive quarters, left out for the next two quarters, surveyed again in the next two quarters, and then taken out of the sample.
Face-to-face [f2f]
Questionnaire "A - non-response" If people in the household do not want (refuse) to participate in the survey despite the explanation of the interviewer about the purpose of the survey and the need for participation of all selected households, the interviewer should fill in the questionnaire "A - non-response" and specify the reason for not completing the survey with the household on the back of the questionnaire.
Questionnaire "B" Individual Questionnaire The individual questionnaire "B" must be filled in for all household members aged 15 to 79. Particular attention should be paid to people aged 15 and 80, whose dates of birth are exactly at these limits and for which questionnaire "B" may be skipped. Identification data about the reference number of the municipality, the ordinal number of the enumeration district in the municipality and the ordinal number of the respondent are copied from Questionnaire "A" - Household data. For each interviewed person the interviewer fills in the following information: name and surname and place of birth (settlement, municipality, country).
For each question in Questionnaire B it is important to see whether a particular option involves a jump to another question. If there is a jump to another question, it should be followed, i.e. the interview should proceed to the question indicated by an arrow, skipping all previous questions. Also, the interviewer should follow the instructions that indicate what parts of the questionnaire refer to which category of persons.
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Taiwan Labor Cost Index: Industry data was reported at 101.390 2011=100 in Aug 2018. This records a decrease from the previous number of 119.420 2011=100 for Jul 2018. Taiwan Labor Cost Index: Industry data is updated monthly, averaging 115.775 2011=100 from Jan 1982 (Median) to Aug 2018, with 440 observations. The data reached an all-time high of 354.360 2011=100 in Jan 1998 and a record low of 80.310 2011=100 in Mar 2011. Taiwan Labor Cost Index: Industry data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G045: Unit Output Labour Cost Index: 2011=100.
In 2023, around 21.5 percent of the employed population working in the manufacturing sector in Vietnam were trained employees. The share of trained labor has increased significantly since 2021, after having steadily improved in the past few years.
In 2023, Indonesia's labor force participation rate was around **** percent. The labor force participation rate in the country has been slowly increasing over the past few years.