• The dataset is part of Eurostat's collection of population and employment statistics. The code "NAMQ_10_PE" specifically refers to data related to employment and population trends in European countries and likely spans a range of years from 1980 to 2024.

Eurostat provides statistical data on various aspects of the labor market across Europe, including:

• Total Population – The total number of people residing in a particular country or region.
• Labor Force – The portion of the population that is either employed or actively looking for work.
• Employment Rate – The percentage of the working-age population that is employed.
• Unemployment Rate – The percentage of the labor force that is unemployed.
• Youth Employment Rate – The employment rate among young people (typically aged 15-24).

• Sectoral Employment – Employment distribution across various sectors like agriculture, industry, and services.

• **Details of the Dataset **

This dataset would typically cover European Union countries and potentially other European countries (depending on the specific version). The data likely spans multiple years (1980-2024) and provides insights into the demographic and economic changes in these countries over time.

-**Some example insights you might explore:**

Trends in Employment: Analyzing the employment and unemployment rates over time to see how they correlate with major economic events, such as the global financial crisis. Sectoral Shifts: Investigating how the structure of employment has shifted from agriculture and industry to services over the decades. Impact of Population Growth: Exploring how changes in population size relate to changes in employment, labor force participation, and unemployment.

• Link to Eurostat’s Dataset

You can access the Eurostat dataset directly using the following link:

• Eurostat – NAMQ_10_PE Dataset

This link takes you to Eurostat's Labor Force Survey (LFS) data, which includes datasets related to employment, unemployment, and other labor force indicators across EU countries. You can navigate and search for NAMQ_10_PE by using Eurostat’s filtering and search tools. Here, you can download data in various formats such as CSV, Excel, or TSV.

In Europe, Italy and Romania have the highest percentage of economically inactive population. In Italy, more than one third of all people aged 15 to 64 years were inactive during the third quarter of 2024, while in Romania they added up to 32.9 percent. On the other hand, less than 15 percent of the adult population in Iceland was economically inactive. Economic inactivity means they were neither unemployed not employed.

The infra-annual labour statistics dataset contains predominantly monthly and quarterly labour statistics, and associated statistical methodological information, for the OECD member countries and selected other economies. It covers countries that compile labour statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labour market key statistics. In such surveys, information is collected from people living in households through a representative sample and the surveys are based on standard methodology and procedures used internationally.

The subjects available cover: working age population by age; active and inactive labour force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable. The relationship between these several measures are as follow:

• Working age population = Labour force population + Inactive population

• Labour force population = Employed population + Unemployed population

• Employment rate = Employed population / Working age population

• Unemployment rate = Unemployed population / Labour force population

• Labour force participation rate = Labour force population / Working age population

The infra-annual labour statistics compiled for all OECD member countries, are drawn from Labour Force Surveys based on definition provided by the 19th Conference of Labour Statisticians in 2013. The uniform application of these definitions across all OECD member countries results in estimates that are internationally comparable.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Department of Statistics (DOS) carried out four rounds of the 2016 Employment and Unemployment Survey (EUS). The survey rounds covered a sample of about fourty nine thousand households Nation-wide. The sampled households were selected using a stratified multi-stage cluster sampling design.

It is worthy to mention that the DOS employed new technology in data collection and data processing. Data was collected using electronic questionnaire instead of a hard copy, namely a hand held device (PDA).

The survey main objectives are: - To identify the demographic, social and economic characteristics of the population and manpower. - To identify the occupational structure and economic activity of the employed persons, as well as their employment status. - To identify the reasons behind the desire of the employed persons to search for a new or additional job. - To measure the economic activity participation rates (the number of economically active population divided by the population of 15+ years old). - To identify the different characteristics of the unemployed persons. - To measure unemployment rates (the number of unemployed persons divided by the number of economically active population of 15+ years old) according to the various characteristics of the unemployed, and the changes that might take place in this regard. - To identify the most important ways and means used by the unemployed persons to get a job, in addition to measuring durations of unemployment for such persons. - To identify the changes overtime that might take place regarding the above-mentioned variables.

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 sample representative on the national level (Kingdom), governorates, and the three Regions (Central, North and South).

Analysis unit

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

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

----> Raw Data

A tabulation results plan has been set based on the previous Employment and Unemployment Surveys while the required programs were prepared and tested. When all prior data processing steps were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data. The final report was then prepared, containing detailed tabulations as well as the methodology of the survey.

----> 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.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU, the United Kingdom, EFTA and Candidate countries.

The EU-LFS survey follows the definitions and recommendations of the http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:International_Labour_Organization_(ILO)">International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU-LFS (Statistics Explained) webpage.

The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level.

At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However, many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation by territorial typologies, i.e. urban-rural, metropolitan, coastal, mountain, borders and island typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Department of Statistics (DoS) implements the Labor Force Survey through four rounds every year. The survey covers about 16,500 households distributed over all governorates. The households are selected on the basis of scientific criteria in designing the multistage cluster stratified samples. It should be noted that the survey sample represents the Kingdom, governorates, three regions, urban / rural and Jordanians and non-Jordanians.

It is worth mentioning that the Department of Statistics uses the tablet sets in data collection and processing and an electronic questionnaire instead of the paper format.

The survey main objectives are: - To identify the demographic, social and economic characteristics of the population and manpower. - To identify the occupational structure and economic activity of the employed persons, as well as their employment status. - To identify the reasons behind the desire of the employed persons to search for a new or additional job. - To measure the economic activity participation rates (the number of economically active population divided by the population of 15+ years old). - To identify the different characteristics of the unemployed persons. - To measure unemployment rates (the number of unemployed persons divided by the number of economically active population of 15+ years old) according to the various characteristics of the unemployed, and the changes that might take place in this regard. - To identify the most important ways and means used by the unemployed persons to get a job, in addition to measuring durations of unemployment for such persons. - To identify the changes overtime that might take place regarding the above-mentioned variables.

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 sample representative on the national level (Kingdom), governorates, three regions (Central, North and South), urban / rural and Jordanians and non-Jordanians.

Analysis unit

1- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

----> Raw Data

A tabulation results plan has been set based on the previous Employment and Unemployment Surveys while the required programs were prepared and tested. When all prior data processing steps were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data. The final report was then prepared, containing detailed tabulations as well as the methodology of the survey.

----> Harmonized Data

• The STATA software 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 individual level, in STATA and then converted to SPSS, to be disseminated.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU, the United Kingdom, EFTA and Candidate countries.

The EU-LFS survey follows the definitions and recommendations of the http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:International_Labour_Organization_(ILO)">International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU-LFS (Statistics Explained) webpage.

The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level.

At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However, many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation by territorial typologies, i.e. urban-rural, metropolitan, coastal, mountain, borders and island typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Department of Statistics (DoS) implements the Labor Force Survey through four rounds every year. The survey covers about 16,500 households distributed over all governorates. The households are selected on the basis of scientific criteria in designing the multistage cluster stratified samples. It should be noted that the survey sample represents the Kingdom, governorates, three regions, urban / rural and Jordanians and non-Jordanians.

It is worth mentioning that the Department of Statistics uses the tablet sets in data collection and processing and an electronic questionnaire instead of the paper format.

The survey main objectives are: - To identify the demographic, social and economic characteristics of the population and manpower. - To identify the occupational structure and economic activity of the employed persons, as well as their employment status. - To identify the reasons behind the desire of the employed persons to search for a new or additional job. - To measure the economic activity participation rates (the number of economically active population divided by the population of 15+ years old). - To identify the different characteristics of the unemployed persons. - To measure unemployment rates (the number of unemployed persons divided by the number of economically active population of 15+ years old) according to the various characteristics of the unemployed, and the changes that might take place in this regard. - To identify the most important ways and means used by the unemployed persons to get a job, in addition to measuring durations of unemployment for such persons. - To identify the changes overtime that might take place regarding the above-mentioned variables.

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 sample representative on the national level (Kingdom), governorates, three regions (Central, North and South), urban / rural and Jordanians and non-Jordanians.

Analysis unit

1- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

----> Raw Data

A tabulation results plan has been set based on the previous Employment and Unemployment Surveys while the required programs were prepared and tested. When all prior data processing steps were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data. The final report was then prepared, containing detailed tabulations as well as the methodology of the survey.

----> Harmonized Data

• The STATA software 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 individual level, in STATA and then converted to SPSS, to be disseminated.

Abstract

Statistical information on all aspects of socio-economic activities is essential for the designing, monitoring evaluation of development plans and policies for gagging the growth of investment. Labour force surveys are one of the important sources of data for assessing the role of the population of the country in the economic and social development process. These surveys provide data on the main characteristics of the work force engaged or available to be engaged in productive activities during a given period and also its distribution in the various sectors of the economy. It is also useful to indicate the extent of available and unutilized human recourses that must be absorbed by the national economy to ensure full employment and economic well being of the population. Furthermore, the information obtained from such surveys is useful for the purpose of macro-economic monitoring and evaluation human resource development planning. The other broad objective of statistics on the labour force is for the measurement of relationship between employment, income and other social and economic characteristics of the economically active population for the purpose of formulating, monitoring and evaluation of employment policy and programs. Seasonal and other variations and changes over time in the size and characteristics of the employment and unemployment can be monitored using up-to-date information from labour force survey.

CSA has been providing labour force and related data at different levels and with varying details in their content. These include the 1976 Addis Ababa Man Power and Housing Sample Survey the 1978 Survey on Population and Housing Characteristics of Seventeen Major Towns, the 1980/81 and 1987/88 Rural Labour Force Surveys, and the 1984 & 1994 Population and Housing Census. The 1996 and 2002 Surveys of Informal Sector and most of the household surveys also provide limited data on the area. Some information can also be derived from small, large and medium scale establishment surveys. Till the 1999 survey there hasn't been a comprehensive national labour force survey representing both urban and rural areas.

The latest data in the subject had been collected before four years and can be considered relatively outdated as the sector is dynamic and sensitive to economic and social changes. Moreover, it lacks data for trend and comparable analysis. Thus, to fill-in the data gap in this area, a series of current and continuous labour force survey need to be undertaken. Recognizing this fact and in response to request from different data users, the CSA has launched a biannual employment-unemployment survey program starting October, 2003 G.C

This survey is the first in the series and will serve as a baseline data for tracing changes. This program covers only urban areas of all regions. Rural areas will be included in the future as necessary. The survey is planned to be conducted twice every year, one in October and another in April. October and April in Ethiopia represent peak and slack agricultural periods.

Objectives of the survey: The bi-annual employment and unemployment survey program was designed to provide statistical data on the size and characteristics of the economically active and the non-active population of the country on continuous basis. The data will be useful for policy makers, planners, researchers, and other institutions and individuals engaged in the design, implementation and monitoring of human resource development projects and the performance of the economy.

The specific objectives of the survey are to: - Generate data on the size of work force that is available to participate in production process; - Determine the status and rate of economic participation of different sub-groups of the population; - Identify those who are actually contributing to the economic development (employed) and those out of the sphere; - Determine the size and rate of unemployed population; - Provide data on the structure of the working population; - Obtain information about earnings from paid employment; - Identify the distribution of employed population in the formal/informal sector of the economy; - Generate baseline data to trace changes over time in the future.

Geographic coverage

The 2003 Urban Bi Annual Employment and Unemployment survey covered only urban parts of the country. Except three zones of Afar and six zones of Somali regions, where the residents are pastoralists, all urban centers of the country were considered in this survey.

Analysis unit

• Household
• Individual aged 10 years and above

Universe

All households in the selected samples, except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design and Sample Size: Information from the listing of the 1994 Population and Housing Census was utilized to develop the sampling frame for the 2003 Urban Bi Annual Employment and Unemployment Survey. It was by taking into account of cost and precision of major variables that determination of sample size was achieved. Moreover, in order to judge precisions of major variables, the 1999 Labor Force Survey result was the main source of information that was taken into consideration.

Except Harari, Addis Ababa and Dire Dawa, where all urban centers of the domain were incorporated in the survey, in other domains a three stage stratified cluster sample design was adopted to select the samples from each domain. The primary sampling units (PSU's) were urban centers selected systematically using probability proportional to size; size being number of households obtained from the 1994 Population and Housing Census. From each selected urban centers enumeration areas (EA's) were selected as a second stage sampling unit (SSU). The selection of the SSU's was also done using probability proportional to size; size being number of households obtained from the 1994 Population and Housing Census. For each sampled EA a fresh list of households was prepared at the beginning of the survey. Thirty households from each sample EA were selected at the third stage. The survey questionnaire was finally administered to those thirty households selected at the last stage. The selection scheme for Harari, Addis Ababa and Dire Dawa was similar to the case explained above. However, in these three domains instead of a three-stage design a two-stage stratified cluster sample design with enumeration areas as PSU and households (from the fresh list) as secondary sampling unit was used.

Note: Distribution of sampling units (planned and covered) by domain (reporting level) is given in Summary Table 2.1 of the 2003 Urban Bi-annual Employment Unemployment Survey Round 1 report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey has used a structured questionnaire to solicit the required data. Before taking its final shape, the draft questionnaire was tested by undertaking a pre-test. The pre-test was conducted in Addis Ababa, Debreziet and Sendafa. Based on the findings of the pre-test, the content, layout and presentation of the questionnaire was amended. Comments and inputs on the draft contents of the survey questionnaire obtained from user-producer forum were also incorporated in the final questionnaire.

The questionnaire is organized in to five sections; Section - 1: Area identification of the selected household: this section dealt with area identification of respondents such as region, zone, wereda, etc., Section - 2: Demographic characteristics of household: it consisted of the general socio-demographic characteristics of the population such as age, sex, education, states & types of training and marital status. Section - 3: Economic activity during the last six months: this section covered the usual economic activity status, number of weeks of Employment /Unemployment and reasons for not usually working. Section - 4: Productive activities during the last seven days: this section dealt with the status and characteristics of employed persons such as hours of work occupation, industry, employment status, and Earnings from employment. Section - 5: Unemployment and characteristics of unemployed persons: the section focused on the size and characteristics of the unemployed population.

Note: The questionnaires are provided as external resource.

Cleaning operations

Data Editing, Coding and Verification: The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors, Statisticians and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry. After the data was entered, it was again verified using the computer.

Data Entry, Cleaning and Tabulation: Using the computer edit specification prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on tabulation results. Computer programs was developed by data processing department for data entry, data cleaning and tabulation using Integrated Microcomputer Processing System (IMPS) software.

Response

Abstract

Statistical information on all aspects of the population is vital for the design, implementation and evaluation of economic and social development plan and policy issues. Labour force survey is one of the most important sources of data for assessing the role of the population of the country in the economic and social development process. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic well being of the population. It is also an input for assessing the meeting of the Millennium Development Goals (MDGs) and the country's poverty reduction strategy framework for PASDEP (Plan for Accelerated and Sustained Development to End Poverty). Statistics on the labour force further deals with the measurement and the relationship between employment, income and other social and economic characteristics of the economically active and non active population. Seasonal and other variations as well as changes over time in the size and characteristics of the employment and unemployment can be monitored using up-to-date information from labour force surveys.

Thus, data on economic activity together with other labour force data would be of a springboard for a clear formulation, monitoring and evaluation of employment policies, programs and strategies on human resource development and various socio-economic plans at different levels in the country. This survey results provide data on the main characteristics of the work force engaged or available to be engaged in the production of economic goods and services and its distribution in the various sectors of the economy during a given reference period. Statistical information on all aspects of the population is vital for the design, implementation and evaluation of economic and social development plan and policy issues. Labour force survey is one of the most important sources of data for assessing the role of the population of the country in the economic and social development process. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic well being of the population. It is also an input for assessing the meeting of the Millennium Development Goals (MDGs) and the country's poverty reduction strategy framework for PASDEP (Plan for Accelerated and Sustained Development to End Poverty). Statistics on the labour force further deals with the measurement and the relationship between employment, income and other social and economic characteristics of the economically active and non active population. Seasonal and other variations as well as changes over time in the size and characteristics of the employment and unemployment can be monitored using up-to-date information from labour force surveys.

Thus, data on economic activity together with other labour force data would be of a springboard for a clear formulation, monitoring and evaluation of employment policies, programs and strategies on human resource development and various socio-economic plans at different levels in the country. This survey results provide data on the main characteristics of the work force engaged or available to be engaged in the production of economic goods and services and its distribution in the various sectors of the economy during a given reference period.

Objectives of the Survey: The 2009 Urban Employment and Unemployment Survey program was designed to provide statistical data on the characteristics and size of the economic activity status i.e. employed, unemployed and the non-active population of the country at urban levels on annual basis. The data obtained from this survey will be useful for policy makers, planners, researchers, and other institutions and individuals engaged in the design, implementation and monitoring of human resource development projects and to assess and understand the performance of the economy.

The specific objectives of the 2009 Urban Employment and Unemployment Survey are: - collect statistical data on the potential manpower and those who are available to take part in various socio-economic activities; - up date the data and determine the size and distribution of the labour force participation and the status of economic activity for different sub-groups of the population; and also to study the socio-economic and demographic characteristics of these groups; - identify those who are actually contributing to the economic development (working population) and those out of the sphere the economy; - identify the size, distribution and characteristics of employed population i.e. working in the formal or informal employment sector of the economy and earnings for paid employees, type of occupation and Industry...etc; - provide data that can be used to assess the situation of women's employment or the participation of women in the labour force; - provide data on the size, characteristics and distribution of unemployed population and rate of unemployment; - identify the size and characteristics of children aged 5-17 years that were engaged in economic activities; - provide the generated time series data to trace changes over time

Geographic coverage

The 2009 Urban Employment and Unemployment Survey (UEUS) covered only urban parts of the country. Except three zones of Afar, six zones of Somali, where the residents are pastoralists all urban centers of the country were considered in this survey.

Analysis unit

• Household
• Individual aged 10 years and above

Universe

This survey follows household approach and covers households residing in conventional households and thus, population residing in the collective quarters such as universities/colleges, hotel/hostel, monasteries and homeless population etc., are not covered by this survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The list of households obtained from the 2007 Population and Housing Census is used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame in order to select households from sample EAs.

Sample Design: For the purpose of the survey the country was divided into two broad categories. That is major urban center and other urban center categories. Category I:- Major urban centers:- In this category all regional capitals and four other major urban centers that have a high population size as compared to others were included. Each urban center in this category was considered as a reporting level. The category has a total of 15 reporting levels. In this category, in order to select the sample, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs of each reporting level. Then from each sample EA 30 households were selected as a Second Stage Unit (SSU).

Category II: - Other urban centers: Urban centers in the country other than those under category I were grouped into this category. A domain of other urban centers is formed for each region. Consequently 8 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other the one previously that grouped in category I. Hence, no domain was formed for these regions under this category.

A stratified three stage cluster sample design was adopted to select samples from this category II. The primary sampling units were other urban centers and the second stage sampling units were EAs. From each EA 30 households were finally selected at the third stage and the survey questionnaires administered to all of them.

Sample Size and Selection Scheme Category I:- In this category 371 EAs and 11,130 households were selected. Sample EAs from each reporting level in this category were selected using probability proportional to size systematic sampling; size being number of households obtained from the 2007 population and housing census. From the fresh list of households prepared at the beginning of the survey, 30 households per EA were systematically selected and covered by the study.

Category II:- 82 urban centers, 270 EAs and 8,100 households were selected in this category. Urban centers from each domain and EAs from each urban center were selected using probability proportional to size systematic method; size being number of households obtained from the 2007 Population and housing census. From the listing of each EA then 30 households were systematically selected and the study performed on the 30 households ultimately selected.

The distribution of planned and covered EAs and households and the Estimation procedures are given in the appendix in the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is organized into six sections; Section - 1: Area identification of the selected household: this section deals with area identification of respondents such as region, zone, wereda, etc. Section - 2: Particulars of household members: it consists of the general socio-demographic characteristics of the population such as age, sex, educational status, types of training and marital status. Section - 3: Economic activity during the last seven days: this section deal with whether persons were engaged in productive activities or not during the last seven days prior to date of interview, the status and characteristics of employed persons such as occupation, industry, employment status, hours of work, employment sector /formal and informal employment/ and earnings from paid employment. Section - 4: Unemployment rate and characteristics

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Department of Statistics (DOS) carried out four rounds of the 2009 Employment and Unemployment Survey (EUS) during February, May, August and November 2009. The survey rounds covered a total sample of about fifty three thousand households Nation-wide. The sampled households were selected using a stratified multi-stage cluster sampling design. It is noteworthy that the sample represents the national level (Kingdom), governorates, the three Regions (Central, North and South), and the urban/rural areas.

The importance of this survey lies in that it provides a comprehensive data base on employment and unemployment that serves decision makers, researchers as well as other parties concerned with policies related to the organization of the Jordanian labor market.

It is worthy to mention that the DOS employed new technology in data collection and data processing. Data was collected using electronic questionnaire instead of a hard copy, namely a hand held device (PDA).

The survey main objectives are:

• To identify the demographic, social and economic characteristics of the population and manpower.
• To identify the occupational structure and economic activity of the employed persons, as well as their employment status.
• To identify the reasons behind the desire of the employed persons to search for a new or additional job.
• To measure the economic activity participation rates (the number of economically active population divided by the population of 15+ years old).
• To identify the different characteristics of the unemployed persons.
• To measure unemployment rates (the number of unemployed persons divided by the number of economically active population of 15+ years old) according to the various characteristics of the unemployed, and the changes that might take place in this regard.
• To identify the most important ways and means used by the unemployed persons to get a job, in addition to measuring durations of unemployment for such persons.
• To identify the changes overtime that might take place regarding the above-mentioned variables.

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 sample representative on the national level (Kingdom), governorates, the three Regions (Central, North and South), and the urban/rural areas.

Analysis unit

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

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Survey Frame

The sample of this survey is based on the frame provided by the data of the Population and Housing Census, 2004. The Kingdom was divided into strata, where each city with a population of 100,000 persons or more was considered as a large city. The total number of these cities is 6. Each governorate (except for the 6 large cities) was divided into rural and urban areas. The rest of the urban areas in each governorate was considered as an independent stratum. The same was applied to rural areas where it was considered as an independent stratum. The total number of strata was 30.

In view of the existing significant variation in the socio-economic characteristics in large cities in particular and in urban in general, each stratum of the large cities and urban strata was divided into four sub-stratum according to the socio- economic characteristics provided by the population and housing census with the purpose of providing homogeneous strata.

The frame excludes the population living in remote areas (most of whom are nomads). In addition to that, the frame does not include collective dwellings, such as hotels, hospitals, work camps, prisons and alike.

Sample Design

The sample of this survey was designed, using the two-stage cluster stratified sampling method. The main sample was designed in 2009 based on the data of the population and housing census 2004 for carrying out household surveys. The sample is representative on the Kingdom, rural-urban regions and governorates levels. The total sample size for each round was 1336 Primary Sampling Units (PSUs) (clusters). These units were distributed to urban and rural regions in the governorates, in addition to the large cities in each governorate according to the weight of persons and households, and according to the variance within each stratum. Slight modifications regarding the number of these units were made to cope with the multiple of 8, the number of clusters for four rounds was 5344.

The main sample consists of 40 replicates, each replicate consists of 167 PSUs. For the purpose of each round, eight replicates of the main sample were used. The PSUs were ordered within each stratum according to geographic characteristics and then according to socio-economic characteristics in order to ensure good spread of the sample. Then, the sample was selected on two stages. In the first stage, the PSUs were selected using the Probability Proportionate to Size with systematic selection procedure. The number of households in each PSU served as its weight or size. In the second stage, the blocks of the PSUs (cluster) which were selected in the first stage have been updated. Then a constant number of households (10 households) was selected, using the random systematic sampling method as final PSUs from each PSU (cluster).

More information on the distribution of the number of PSUs, and the number of households by regions and governorates is available in Table 1 (Page 3) of the survey report provided among the disseminated survey materials under a file named "Jordan 2009- EUS Report (English).pdf".

Sampling notes

It is noteworthy that the sample of the present survey does not represent the non-Jordanian population, due to the fact that it is based on households living in conventional dwellings. In other words, it does not cover the collective households living in collective dwellings. Therefore, the non-Jordanian households covered in the present survey are either private households or collective households living in conventional dwellings. In Jordan, it is well known that a large number of non-Jordanian workers live as groups and spend most of their time at their work places. Hence, it is more unlikely to find them at their residences during daytime (i.e. the time when the data of the survey is collected). Furthermore, most of them live in their work places, such as: workshops, sales stores, guard places, or under construction building's sites. Such places are not classified as occupied dwellings for household sampling purposes. Due to all of the above, the coverage of such population would not be complete in household surveys.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed electronically on the PDA and revised by the DOS technical staff. It was finalized upon completion of the training program. The questionnaire is divided into main topics, each containing a clear and consistent group of questions, and designed in a way that facilitates the electronic data entry and verification. The questionnaire includes the characteristics of household members in addition to the identification information, which reflects the administrative as well as the statistical divisions of the Kingdom.

Cleaning operations

Raw Data

120 PDA were used to input and transfer data from the interviewees to the database. The plan of the tabulation of survey results was guided by former Employment and Unemployment Surveys which were previously prepared and tested. When all data processing procedures were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data such as titles, inputs, concepts, as well as the figures. The final survey report was then prepared to include all detailed tabulations as well as the methodology of the survey.

Harmonized Data

• STATA 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 STATA and then converted to SPSS, to be disseminated.

Response rate

Sample Coverage

The results of the fieldwork indicated that all sampled households were visited. The

Context

Time use can vary greatly by country and between genders, be it by it's location, cultural differences, or economic situation. The data provided is by no means exhaustive but contains some interesting information on leisure time by gender, as well as historic data (1950-2017) on Avg. work hours and GDP in different countries and continents.

Content

Datasets from two sources are provided: 1. OECD Time use country statistics: Based on a collection of different questionnaires for different countries, it provides a distribution for time spent on different activities for both men and women in different countries. 2. Penn World Table (PWT) with information on RGDPO (in mil. 2017US$), work hours and population (in millions) actively working. Covering 183 countries between 1950 and 2019.

*RGDPO: Output-side real GDP at chained PPPs, to compare relative productive capacity across countries and over time. Example: Productive capacity of China today compared to the US at some point in the past.

If you'd like, you can see an exploration of the data on my notebook: Data exploration

Acknowledgements

These databases provide additional indicators and may be of interest: - https://stats.oecd.org/Index.aspx?DataSetCode=TIME_USE - https://www.rug.nl/ggdc/productivity/pwt/

Inspiration

It is an interesting, easy to handle dataset which provides a great opportunity for interesting visuals and identifying relationships or trends between indicators.

Some questions to answer: - How to annual working hours relate to GDP per capita. - Is there a specific trend in working hours vs GDP per capita % change? Is it different for any specific region? - Is there any relationship between leisure time use and location, GDP or religion? - Is there a time use discrepancy by gender?

In 2023, South Africa had the highest unemployment rate in the world, at 32.1 percent. Of the 10 countries with the highest unemployment rates, six were in Sub-Saharan Africa. What exactly is unemployment? The unemployment rate is the number of people in the workforce currently looking for jobs but not working. This number does not include students and retirees, as they are not looking for work, nor does it include people who have given up on finding a job (known as discouraged workers). Comparing international unemployment rates can be problematic, however, as different countries use different methodologies when classifying unemployment. For example, Niger records the third lowest unemployment rate in the world, despite often being listed as the least developed country worldwide - this is because the majority of the population engage in subsistence farming, with very little opportunity for paid employment. Causes of unemployment in less developed countries A major driver in unemployment in these countries is conflict. In particular, internally displaced persons (IDPs) want to work, but moving to another part of the country disrupts their business network and moves them into a local economy with different labor demand. Countries with low levels of economic development, as roughly indicated by a low GDP per capita, often have fewer labor market opportunities, leading to high unemployment rates.

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Data Source: This dataset was compiled from multiple data sources

If this was helpful, a vote is appreciated ❤️ Thank you 🙂

Abstract

The Urban Employment and Unemployment Survey program was designed to provide statistical data on the size and characteristics of the economically active and the inactive population of the country on continuous basis. The variables collected in the survey: socio-demographic characteristics of household members; economic activity during the last seven days and six months; including characteristics of employed persons such as hours of work, occupation, industry, employment status, and earnings from paid employment; unemployment and characteristics of unemployed persons.

The general objective of the 2014 Urban Employment and Unemployment Survey is to provide statistical data on the characteristics and size of the economic activity status i.e. employed, unemployed population of the country at urban levels on annual basis. The specific objectives of the survey are to: • collect statistical data on the potential manpower and those who are available to take part in various socio-economic activities; • update the data and determine the size and distribution of the labour force participation and the status of economic activity for different sub-groups of the population at different levels of the country; and also to study the socioeconomic and demographic characteristics of these groups; • identify the size, distribution and characteristics of employed population i.e. working in the formal or informal employment sector of the economy and earnings from paid employees and its distribution by occupation and Industry...etc; • provide data on the size, characteristics and distribution of unemployed population and rate of unemployment; • provide data that can be used to assess the situation of women’s employment or the participation of women in the labour force; and • generated time series data to trace changes over time;

Geographic coverage

The survey covered all urban parts of the country except three zones of Afar and six zones of Somali, where the residents are pastoralists.

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2007 Population and Housing Census was used as frame to select 30 households from the sample enumeration areas.

The country was divided into two broad categories. 1) Major urban centers: All regional capitals and five other major urban centers were included in this category. This category had a total of 16 reporting levels. A stratified two-stage cluster sample design was implemented to select the samples. The primary sampling units were EAs, from each EA 30 households were selected as a second stage unit.

2) Other urban centers: In this category, all other urban centers were included. This category had a total of 8 reporting levels. A stratified three stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. From each EA 30 households were selected at the third stage.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire that was used to collect the data had six sections:

Section - 1: Area identification of the selected household: this section dealt with area identification of the respondents such as region, zone, wereda, etc.

Section - 2: Socio- demographic characteristics of households: it consisted of the general socio-demographic characteristics of the population such as age, sex, education, status and type of migration, disability, literacy status, educational Attainment, types of training and marital status.

Section – 3: Economic activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, status in employment, earnings from employment, job mobility, service year for paid employees employment in the formal and informal sector and time related under employment.

Section – 4: Unemployment and characteristics of unemployed persons: this section focused on the size, rate and characteristics of the unemployed population.

Section – 5: Economic activities during the last twelve months: this section consists of the usual economic activity status refereeing to the long reference period i.e. engaged in productive activities during most of the last twelve months, reason for not being active, status in employment, main occupation and industry with two digit codes.

Section – 6: Economic activities of children age 5-17 years: this section comprises information on the participation of children age 5-17 years in the economic activities, whether attending education, reason for not attending education, whether they were working during the last seven days, reason for working, for whom they are working, types of injury at work place, whether using protective wear while working and frequency of working periods, and orphan hood status.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork, field supervisors and statisticians of the head and branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation to maintain the quality of the data. Consistency checks and rechecks were also made based on frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject matter experts from Manpower Statistics Team of the CSA.

Response rate

Response rate of the survey was 99.8%

Sampling error estimates

Estimation procedures, estimates, and CV's for selected tables are provided in the Annex II and III of the survey final report.

Abstract

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.

Geographic coverage

National

Universe

The unit of observation is the household and everyone in it.

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

Mode of data collection

Face-to-face [f2f]

Research instrument

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.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Department of Statistics (DOS) carried out four rounds of the 2009 Employment and Unemployment Survey (EUS) during February, May, August and November 2009. The survey rounds covered a total sample of about fifty three thousand households Nation-wide. The sampled households were selected using a stratified multi-stage cluster sampling design. It is noteworthy that the sample represents the national level (Kingdom), governorates, the three Regions (Central, North and South), and the urban/rural areas.

The importance of this survey lies in that it provides a comprehensive data base on employment and unemployment that serves decision makers, researchers as well as other parties concerned with policies related to the organization of the Jordanian labor market.

It is worthy to mention that the DOS employed new technology in data collection and data processing. Data was collected using electronic questionnaire instead of a hard copy, namely a hand held device (PDA).

The survey main objectives are:

• To identify the demographic, social and economic characteristics of the population and manpower.
• To identify the occupational structure and economic activity of the employed persons, as well as their employment status.
• To identify the reasons behind the desire of the employed persons to search for a new or additional job.
• To measure the economic activity participation rates (the number of economically active population divided by the population of 15+ years old).
• To identify the different characteristics of the unemployed persons.
• To measure unemployment rates (the number of unemployed persons divided by the number of economically active population of 15+ years old) according to the various characteristics of the unemployed, and the changes that might take place in this regard.
• To identify the most important ways and means used by the unemployed persons to get a job, in addition to measuring durations of unemployment for such persons.
• To identify the changes overtime that might take place regarding the above-mentioned variables.

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 sample representative on the national level (Kingdom), governorates, the three Regions (Central, North and South), and the urban/rural areas.

Analysis unit

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

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

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 DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Survey Frame

The sample of this survey is based on the frame provided by the data of the Population and Housing Census, 2004. The Kingdom was divided into strata, where each city with a population of 100,000 persons or more was considered as a large city. The total number of these cities is 6. Each governorate (except for the 6 large cities) was divided into rural and urban areas. The rest of the urban areas in each governorate was considered as an independent stratum. The same was applied to rural areas where it was considered as an independent stratum. The total number of strata was 30.

In view of the existing significant variation in the socio-economic characteristics in large cities in particular and in urban in general, each stratum of the large cities and urban strata was divided into four sub-stratum according to the socio- economic characteristics provided by the population and housing census with the purpose of providing homogeneous strata.

The frame excludes the population living in remote areas (most of whom are nomads). In addition to that, the frame does not include collective dwellings, such as hotels, hospitals, work camps, prisons and alike.

Sample Design

The sample of this survey was designed, using the two-stage cluster stratified sampling method. The main sample was designed in 2009 based on the data of the population and housing census 2004 for carrying out household surveys. The sample is representative on the Kingdom, rural-urban regions and governorates levels. The total sample size for each round was 1336 Primary Sampling Units (PSUs) (clusters). These units were distributed to urban and rural regions in the governorates, in addition to the large cities in each governorate according to the weight of persons and households, and according to the variance within each stratum. Slight modifications regarding the number of these units were made to cope with the multiple of 8, the number of clusters for four rounds was 5344.

The main sample consists of 40 replicates, each replicate consists of 167 PSUs. For the purpose of each round, eight replicates of the main sample were used. The PSUs were ordered within each stratum according to geographic characteristics and then according to socio-economic characteristics in order to ensure good spread of the sample. Then, the sample was selected on two stages. In the first stage, the PSUs were selected using the Probability Proportionate to Size with systematic selection procedure. The number of households in each PSU served as its weight or size. In the second stage, the blocks of the PSUs (cluster) which were selected in the first stage have been updated. Then a constant number of households (10 households) was selected, using the random systematic sampling method as final PSUs from each PSU (cluster).

More information on the distribution of the number of PSUs, and the number of households by regions and governorates is available in Table 1 (Page 3) of the survey report provided among the disseminated survey materials under a file named "Jordan 2009- EUS Report (English).pdf".

Sampling notes

It is noteworthy that the sample of the present survey does not represent the non-Jordanian population, due to the fact that it is based on households living in conventional dwellings. In other words, it does not cover the collective households living in collective dwellings. Therefore, the non-Jordanian households covered in the present survey are either private households or collective households living in conventional dwellings. In Jordan, it is well known that a large number of non-Jordanian workers live as groups and spend most of their time at their work places. Hence, it is more unlikely to find them at their residences during daytime (i.e. the time when the data of the survey is collected). Furthermore, most of them live in their work places, such as: workshops, sales stores, guard places, or under construction building's sites. Such places are not classified as occupied dwellings for household sampling purposes. Due to all of the above, the coverage of such population would not be complete in household surveys.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed electronically on the PDA and revised by the DOS technical staff. It was finalized upon completion of the training program. The questionnaire is divided into main topics, each containing a clear and consistent group of questions, and designed in a way that facilitates the electronic data entry and verification. The questionnaire includes the characteristics of household members in addition to the identification information, which reflects the administrative as well as the statistical divisions of the Kingdom.

Cleaning operations

Raw Data

120 PDA were used to input and transfer data from the interviewees to the database. The plan of the tabulation of survey results was guided by former Employment and Unemployment Surveys which were previously prepared and tested. When all data processing procedures were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data such as titles, inputs, concepts, as well as the figures. The final survey report was then prepared to include all detailed tabulations as well as the methodology of the survey.

Harmonized Data

• STATA 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 STATA and then converted to SPSS, to be disseminated.

Response rate

Sample Coverage

The results of the fieldwork indicated that all sampled households were visited. The number of successfully completed interviews was 49,231, representing 92.1 percent of

This collection provides users with data about R&D expenditure and R&D personnel broken down by the following institutional sectors: business enterprise (BES); government (GOV); higher education (HES); private non-profit (PNP), total of all sectors.

The R&D expenditure is broken down by source of funds; sector of performance; type of costs; type of R&D; fields of research and development (FORD); https://circabc.europa.eu/ui/group/c1b49c83-24a7-4ff2-951c-621ac0a89fd8/library/b4b841e5-d200-41bc-8f23-d0b1e034f689?p=1&n=10&sort=modified_DESC">socio-economic objectives (NABS 2007) and by regions (https://showvoc.op.europa.eu/#/datasets/ESTAT_Nomenclature_of_Territorial_Units_for_Statistics/data">NUTS 2 level). The business enterprise sector is further broken down by economic activity (https://showvoc.op.europa.eu/#/datasets/ESTAT_Statistical_Classification_of_Economic_Activities_in_the_European_Community_Rev._2/data">NACE Rev.2); size class; industry orientation.

R&D personnel data are broken down by professional position; sector of performance; educational attainment level; sex; field of research and development (https://www.oecd.org/innovation/frascati-manual-2015-9789264239012-en.htm">FORD); regions (https://showvoc.op.europa.eu/#/datasets/ESTAT_Nomenclature_of_Territorial_Units_for_Statistics/data">NUTS 2 level); for the business enterprise sector is further broken down in size class and economic activity (NACE Rev.2). Researchers are further broken down by age class and citizenship.

The periodicity of R&D data are every two years, except for the key R&D indicators (R&D expenditure, R&D personnel (in Full Time Equivalent - FTE) and Researchers (in FTE) by sectors of performance) which are transmitted annually by the EU Member States (from 2003 onwards based on a legal obligation). Some other breakdowns of the data may appear on an annual basis based on voluntary data provisions.

The data are collected through sample or census surveys, from administrative registers or through a combination of sources.

R&D data are available for following countries and country groups:

• All EU Member States; Candidate Countries; EFTA Countries; The Organisation for Economic Cooperation and Development (OECD) is data provider for the United States of America, Japan, South Korea and China.
• Country groups: EU Member States, Euro Area States.

R&D data are compiled in accordance to the guidelines laid down in OECD (2015), https://www.oecd.org/publications/frascati-manual-2015-9789264239012-en.htm">Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities and the European business statistics methodological manual for R&D statistics – 2023 edition - Manuals and guidelines - Eurostat

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU, the United Kingdom, EFTA and Candidate countries.

The EU-LFS survey follows the definitions and recommendations of the http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:International_Labour_Organization_(ILO)">International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU-LFS (Statistics Explained) webpage.

The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level.

At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However, many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation by territorial typologies, i.e. urban-rural, metropolitan, coastal, mountain, borders and island typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.