The statistic shows the distribution of employment in Hungary by economic sector from 2013 to 2023. In 2023, 4.43 percent of the employees in Hungary were active in the agricultural sector, 31.15 percent in industry and 64.42 percent in the service sector.

Hungary HU: Labour Fource data was reported at 4,742.881 Person th in 2022. This records an increase from the previous number of 4,700.598 Person th for 2021. Hungary HU: Labour Fource data is updated yearly, averaging 4,214.100 Person th from Dec 1992 (Median) to 2022, with 31 observations. The data reached an all-time high of 4,742.881 Person th in 2022 and a record low of 3,995.000 Person th in 1997. Hungary HU: Labour Fource data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Hungary – Table HU.OECD.MSTI: Population, Labour Force and Employment: OECD Member: Annual. In Hungary, capital R&D expenditures include intangible assets from reference year 2018. Data on funds from the higher education sector are available from reference year 2018. Beginning in 2006, government-financed R&D, some of which was not allocated to the appropriate sector, is now allocated, in particular to the Business enterprise sector. Prior to 2004, only defence R&D performed in the civil sector is covered. Up until 1993, Business Enterprise expenditure includes purchases of licenses and know-how. As of 1994, the Central Technology Fund has been reclassified from the Business Enterprise sector to the Government sector. 2013 GBARD data include multi-annual R&D projects which are not allocated to the year in which they were budgeted.

Graph and download economic data for Infra-Annual Registered Unemployment and Job Vacancies: Total Economy: Unfilled Vacancies for Hungary (LMJVTTUVHUM647S) from Jan 1992 to Jan 2024 about Hungary, job openings, vacancy, and jobs.

Employment placement agencies in Europe’s revenue is anticipated to contract at a compound annual rate of 9% over the five years through 2025 to €65.4 billion. The COVID-19 outbreak tanked business confidence and expansion plans because of economic uncertainty after months of global lockdowns, forcing hiring freezes in a tricky time for employment agencies. 2022 marked a resurgence for agencies, with companies entering a hiring frenzy post-pandemic. The labour market is cooling in 2025 amid greater global uncertainty with US tariffs impacting business confidence. Still, employment across Europe remains high. According to Eurostat data, employment in the EU reached a record peak of 75.8% in 2024. Companies enjoyed a post-COVID-19 boom in hiring, as the economy reopened and companies began to look to expand thanks to improved business confidence, which kept employment agencies busy. The labour market has proved resilient against the economic background of high interest rates and high inflation in recent years, but remains tight with several unfilled vacancies. Vacancies have dipped from the sharp rise post-COVID-19 when companies unfroze hiring decisions. Available vacancies are proving difficult to fill in 2025, indicating a skills mismatch between job seekers and roles that agencies are struggling to negotiate. Several countries attempt to address long-standing labour shortages to ameliorate professional mobility and offer training courses for in-demand skills through agencies. France, for example, is addressing youth unemployment through upskilling training programmes. Public sector hiring in Germany and Spain in health and education also pushes revenue growth for agencies compared to stunted private sector demand. Revenue is expected to rise by 8.7% in 2025 amid job cuts in the technology sector. Revenue is projected to swell at a compound annual rate of 13.2% over the five years through 2030 to reach €121.6 billion. Agencies will continue to target revenue growth by elevating their online presence, specialising their services towards more niche sectors and targeting executives and upper management positions. Technological developments remain a threat to recruiters, with HR AI systems like Paradox able to scan networking platforms such as LinkedIn for candidates. Companies’ in-house HR teams are expanding too. The sustainability sector looks to be a hot property job market to target, but potential shortages in both high and low-skilled occupations driven by employment growth in STEM professions and healthcare will create hurdles in the hiring process in other sectors.

Abstract

Objectives: The main objectives of the survey were to identify longstanding health problems, diseases, bodily or sensory, or mental disabilities in the population aged 15 to 64 as well as its influence on their work performance and to find out the measures to be taken or necessary for integration of disabled persons in the labour market. Essentially, the ad hoc module coordinated by Eurostat was designed to measure the practical implementation, ensuring the rights and equal chances for persons with disabilities or longstanding health problems, and to find out to what extent the goals set in the action plan have been met.

Reference Period: Week

Periodicity of Data Collection: Ad hoc module

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: Persons who are members of households, persons in age group 15 and over

Total population covered: Na

Economic activities: All economic activities

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers, contributing family workers, members of producers' cooperatives

Establishments: NR

Other limitations: Excludes people in jails and other correctional institutions

Classifications: Sex, age, other personal characteristics, type of living arrangements, status in employment, occupation, economic activity, type of disability

Cross-classification: All kind of cross-classifications with all the variables above

Kind of data

Sample survey data [ssd]

Frequency of data collection

Periodicity of Data collection: Ad hoc module

In 2023, the hours worked by employees on the main job in Hungary did not change in comparison to the previous year. The hours worked by employees remained at 39.38 hours per week per person. Find more key insights for the hours worked by employees in countries like Czechia, Poland, and Slovak Republic.

Abstract

This research was conducted in Hungary in February-March 2010 as part of the second round of The Financial Crisis Survey. Data from 152 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Hungary.

Researchers revisited establishments interviewed in Hungary Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study was the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors were the primary business sectors of interest. This corresponded to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies were targeted for interviews. Services firms included construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government ownership were excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

291 establishments that participated in Hungary Enterprise Survey 2009 were contacted for The Financial Crisis Survey. The implementing contractor received directions that the final achieved sample should include at least 150 establishments.

For Hungary Enterprise Survey 2009, the sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into 23 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. Each sector had a target of 90 interviews.

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

Regional stratification was defined in three regions. These regions are Central Hungary, West Hungary and East Hungary.

Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

For most countries covered in 2008-2009 BEEPS, two sample frames were used. The first was supplied by the World Bank and consisted of enterprises interviewed in BEEPS 2005. The World Bank required that attempts should be made to re-interview establishments responding to the BEEPS 2005 survey where they were within the selected geographical regions and met eligibility criteria. That sample is referred to as the Panel. The second frame for Hungary was the Dun & Bradstreet database, which was considered the most reliable for the country. That frame was sent to the TNS statistical team in London to select the establishments for interviews.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 4.6% (29 out of 630 establishments).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The following survey instrument is available: - Financial Crisis Survey Questionnaire

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks and callbacks.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

The number of job vacancies in Hungary decreased by 6,529 vacancies (-7.3 percent) since the previous quarter. Nevertheless, the last two quarters recorded a significant higher number of job vacancies than the preceding quarters.According to Eurostat, a job vacancy is defined as a paid post that is newly created, unoccupied, or about to become vacant.Find more key insights for the number of job vacancies in countries like Czechia, Slovenia, and Slovakia.

Abstract

This research was conducted in Hungary in June-July 2010 as part of the third round of The Financial Crisis Survey. Data from 151 establishments from private nonagricultural formal sector was analyzed to quantify the effect of the 2008 global financial crisis on companies in Hungary.

Researchers revisited establishments interviewed in Hungary Enterprise Survey 2009. Efforts were made to contact all respondents of the baseline survey to determine which of the companies were still operating and which were not. From the information collected during telephone interviews, indicators were computed to measure the effects of the financial crisis on key elements of the private economy: sales, employment, finances, and expectations of the future.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study was the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors were the primary business sectors of interest. This corresponded to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies were targeted for interviews. Services firms included construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government ownership were excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

291 establishments that participated in Hungary Enterprise Survey 2009 were contacted for The Financial Crisis Survey. The implementing contractor received directions that the final achieved sample should include at least 150 establishments.

For Hungary Enterprise Survey 2009, the sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into 23 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. Each sector had a target of 90 interviews.

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

Regional stratification was defined in three regions. These regions are Central Hungary, West Hungary and East Hungary.

Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

For most countries covered in 2008-2009 BEEPS, two sample frames were used. The first was supplied by the World Bank and consisted of enterprises interviewed in BEEPS 2005. The World Bank required that attempts should be made to re-interview establishments responding to the BEEPS 2005 survey where they were within the selected geographical regions and met eligibility criteria. That sample is referred to as the Panel. The second frame for Hungary was the Dun & Bradstreet database, which was considered the most reliable for the country. That frame was sent to the TNS statistical team in London to select the establishments for interviews.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 4.6% (29 out of 630 establishments).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The following survey instrument is available: - Financial Crisis Survey Questionnaire

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks and callbacks.

Abstract

The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with International Standard Industrial Classification of All Economic Activities (ISIC) codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Hungary was selected using stratified random sampling. hree levels of stratification were used in this country: industry, establishment size, and oblast (region).

Industry stratification was designed in the way that follows: the universe was stratified into 23 manufacturing industries, 2 services industries -retail and IT-, and one residual sector. Each sector had a target of 90 interviews.

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

Regional stratification was defined in three regions. These regions are Central Hungary, West Hungary and East Hungary.

Given the stratified design, sample frames containing a complete and updated list of establishments for the selected regions were required. Great efforts were made to obtain the best source for these listings. However, the quality of the sample frames was not optimal and, therefore, some adjustments were needed to correct for the presence of ineligible units. These adjustments are reflected in the weights computation.

For most countries covered in BEEPS IV, two sample frames were used. The first was supplied by the World Bank and consisted of enterprises interviewed in BEEPS 2005. The World Bank required that attempts should be made to re-interview establishments responding to the BEEPS 2005 survey where they were within the selected geographical regions and met eligibility criteria. That sample is referred to as the Panel. The second frame for Hungary was the Dun & Bradstreet database, which was considered the most reliable for the country. That frame was sent to the TNS statistical team in London to select the establishments for interviews.

The quality of the frame was assessed at the onset of the project. The frame proved to be useful though it showed positive rates of non-eligibility, repetition, non-existent units, etc. These problems are typical of establishment surveys, but given the impact these inaccuracies may have on the results, adjustments were needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of contacts to complete the survey was 4.6% (29 out of 630 establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Screener Questionnaire

The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments- the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in the document "Description of Hungary Implementation 2009.pdf"

Abstract copyright UK Data Service and data collection copyright owner. Carried out every four years, the European Quality of Life Survey (EQLS) examines both the objective circumstances of European citizens' lives and how they feel about those circumstances and their lives in general. It collects data on a range of issues, such as employment, income, education, housing, family, health and work-life balance. It also looks at subjective topics, such as people's levels of happiness, life satisfaction, and perceived quality of society. By running the survey regularly, it has also become possible to track key trends in the quality of people's lives over time. Previous surveys have shown, for instance, that people are having greater difficulty making ends meet since the economic crisis began. In many countries, they also feel that there is now more tension between people from different ethnic groups. And across Europe, people now trust their governments less than they did before. However, people still continue to get the greatest satisfaction from their family life and personal relationships. Over the years, the EQLS has developed into a valuable set of indicators which complements traditional indicators of economic growth and living standard such as GDP or income. The EQLS indicators are more inclusive of environmental and social aspects of progress and therefore are easily integrated into the decision-making process and taken up by public debate at EU and national levels in the European Union. In each wave a sample of adult population has been selected randomly for a face to face interview. In view of the prospective European enlargements the geographical coverage of the survey has expanded over time from 28 countries in 2003 to 34 countries in 2011-12. Further information about the survey can be found on the European Foundation for the Improvement of Living and Working Conditions (Eurofound) EQLS web pages. Main Topics: The survey examines a range of issues, such as employment, income, education, housing, family, health, work-life balance, life satisfaction and perceived quality of society. Multi-stage stratified random sample See documentation for details Face-to-face interview 2003 AGE AGRICULTURE ATTITUDES Austria BASIC NEEDS Belgium Bulgaria CARE OF DEPENDANTS CAREER DEVELOPMENT CHARITABLE ORGANIZA... CHIEF INCOME EARNERS CHILD CARE CHILDREN COMMUTING COMPUTERS CONSUMER GOODS Cyprus Czech Republic DEBILITATIVE ILLNESS DEBTS DECISION MAKING DISABILITIES DISADVANTAGED GROUPS DOMESTIC RESPONSIBI... Denmark ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EMPLOYMENT EMPLOYMENT HISTORY ENGLISH LANGUAGE EVERYDAY LIFE EXPECTATION EXPOSURE TO NOISE Estonia European Union Coun... FAMILY LIFE FINANCIAL RESOURCES FOOD AND NUTRITION FURNITURE Finland France GENDER GENERAL PRACTITIONERS Germany October 1990 Greece HEALTH CONSULTATIONS HEALTH SERVICES HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSEWORK HOUSING CONDITIONS Hungary INCOME INTERGROUP CONFLICT Ireland Italy JOB SATISFACTION LABOUR FORCE LABOUR RELATIONS LAND OWNERSHIP LEISURE GOODS LIFE SATISFACTION LIFE STYLES LIVING CONDITIONS LOCAL COMMUNITY FAC... LUCK Latvia Lithuania Luxembourg MEALS MOTOR VEHICLES Malta NEIGHBOURHOODS Netherlands OCCUPATIONAL SAFETY OCCUPATIONAL STATUS OCCUPATIONS PARENTS PERSONAL CONTACT POLITICAL PARTICIPA... POLLUTION POVERTY Poland Portugal QUALIFICATIONS QUALITY OF LIFE RECREATIONAL FACILI... RELIGIOUS ATTENDANCE ROOMS RURAL AREAS Romania SATISFACTION SOCIAL ATTITUDES SOCIAL EXCLUSION SOCIAL INDICATORS SOCIAL LIFE SOCIAL SECURITY BEN... SOCIAL SUPPORT STANDARD OF LIVING STATE RETIREMENT PE... STRESS PSYCHOLOGICAL SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS Slovakia Slovenia Social behaviour an... Social conditions a... Sweden TERMINATION OF SERVICE TRAINING TRUST Turkey URBAN AREAS United Kingdom VOLUNTARY WORK WAGES WATER PROPERTIES WORK ATTITUDE WORKING CONDITIONS

Over the course of the 20th century, the structure of the labor forces in Central and Eastern Europe changed drastically. In 1900, almost 70 percent of the workforce in Hungary, one of the more industrialized regions in Central and Eastern Europe at the time, still worked in agriculture; in Russia, the largest economic power in the region, it was roughly three-quarters. Russia then began to industrialize following the revolution in 1917, as too did Central European countries, but it was not until after the Second World War when this would take off in the Balkans after the adoption of socialist economic structures.

By the mid-1900s, there was a fairly broad spread of the workforce between the three major sectors of the economy. At the end of the century, after the dissolution of the Soviet Union and collapse of the communist system in Eastern Europe, over half of the workforce in Eastern Europe employed in the service sector, while agricultural industries then employed fewer than one fifth. Although this was a substantial decrease since the beginning of the century, it was still roughly double the share of the workforce employed in agriculture in Southern Europe, and six times larger than that of Western Europe.

The share of hospitality and accommodation services employees in the Hungarian workforce decreased over the observed years. By 2020, as a consequence of the coronavirus (COVID-19) pandemic, employees from this sector accounted for only *** percent of the total workforce.