Unemployment Rate in China decreased to 5.10 percent in April from 5.20 percent in March of 2025. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

World unemployment rate for 2023 was 4.96%, a 0.3% decline from 2022.

<ul style='margin-top:20px;'>

<li>World unemployment rate for 2022 was <strong>5.26%</strong>, a <strong>0.77% decline</strong> from 2021.</li>
<li>World unemployment rate for 2021 was <strong>6.03%</strong>, a <strong>0.55% decline</strong> from 2020.</li>
<li>World unemployment rate for 2020 was <strong>6.59%</strong>, a <strong>1% increase</strong> from 2019.</li>
</ul>Unemployment refers to the share of the labor force that is without work but available for and seeking employment.

Unemployment Rate in Japan remained unchanged at 2.50 percent in April. This dataset provides the latest reported value for - Japan Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Data Series: Unemployment rate, by sex and age Indicator: I.8 - Unemployment rate, by sex, age and persons with disabilities Source year: 2023 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Economic structures, participation in productive activities and access to resources

Description:

This dataset provides key economic indicators from various countries between 2010 and 2023. The dataset includes monthly data on inflation rates, GDP growth rates, unemployment rates, interest rates, and stock market index values. The data has been sourced from reputable global financial institutions and is suitable for economic analysis, machine learning models, and forecasting economic trends.

Data Sources:

The data has been generated to simulate real-world economic conditions, mimicking information from trusted sources like: - World Bank for GDP growth and inflation data - International Monetary Fund (IMF) for macroeconomic data - OECD for labor market statistics - National Stock Exchanges for stock market index values

Columns:

1. Date: The specific date (in Year/Month/Day format) representing when the data was collected.
2. Country: The country the data pertains to (e.g., USA, Germany, Japan).
3. Inflation Rate (%): The rate of inflation for that country, showing how fast prices for goods and services are increasing.
4. GDP Growth Rate (%): The percentage growth of the country’s Gross Domestic Product (GDP), indicating economic expansion or contraction.
5. Unemployment Rate (%): The percentage of the working-age population that is unemployed.
6. Interest Rate (%): The central bank's interest rate, used to control inflation and influence the economy.
7. Stock Index Value: The value of the country’s main stock market index, reflecting the performance of the stock market.

Potential Uses: - Economic Analysis: Researchers and analysts can use this dataset to study trends in inflation, GDP growth, unemployment, and other economic factors. - Machine Learning: This dataset can be used to train models for predicting economic trends or market performance. Financial Forecasting: Investors and economists can leverage this data for forecasting market movements based on economic conditions. - Comparative Studies: The dataset allows comparisons across countries and regions, offering insights into global economic performance.

In 2023, the estimated youth unemployment rate in India was at 15.67 percent. According to the source, the data are ILO estimates. For the past decade, India’s youth unemployment rate has been hovering around the 22 percent mark. What is the youth unemployment rate?The youth unemployment rate refers to those in the workforce who are aged 15 to 24 years and without a job, but actively seeking one. Generally, youth unemployment rates are higher than the adult unemployment rates, and India is no exception: youth unemployment in India is significantly higher than the national unemployment rate. The Indian workforce, young and oldIndia’s unemployment rate in general is not remarkably high when compared to those of other countries. Both India’s unemployment rate and youth unemployment rate are below their global equivalents. In a comparison of the Asia-Pacific region countries, India ranks somewhere in the middle, with Cambodia’s unemployment rate being estimated to be below one percent, and Afghanistan’s the highest at 8.8 percent.

Nigeria unemployment rate for 2023 was 3.07%, a 0.75% decline from 2022.

<ul style='margin-top:20px;'>

<li>Nigeria unemployment rate for 2022 was <strong>3.83%</strong>, a <strong>1.57% decline</strong> from 2021.</li>
<li>Nigeria unemployment rate for 2021 was <strong>5.39%</strong>, a <strong>0.32% decline</strong> from 2020.</li>
<li>Nigeria unemployment rate for 2020 was <strong>5.71%</strong>, a <strong>0.51% increase</strong> from 2019.</li>
</ul>Unemployment refers to the share of the labor force that is without work but available for and seeking employment.

Germany DE: Unemployment: National Estimate: Youth: % of Total Labour Force Aged 15-24 data was reported at 5.927 % in 2023. This records a decrease from the previous number of 6.028 % for 2022. Germany DE: Unemployment: National Estimate: Youth: % of Total Labour Force Aged 15-24 data is updated yearly, averaging 8.129 % from Dec 1983 (Median) to 2023, with 41 observations. The data reached an all-time high of 15.461 % in 2005 and a record low of 4.576 % in 1990. Germany DE: Unemployment: National Estimate: Youth: % of Total Labour Force Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Employment and Unemployment. Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.;International Labour Organization. “Labour Force Statistics database (LFS)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

This dataset shows Cambodia's unemployment rate as a percentage of the total labor force from 1991 to 2023, based on modeled estimates from the International Labour Organization (ILO).

Unemployment Rate in Egypt decreased to 6.30 percent in the first quarter of 2025 from 6.40 percent in the fourth quarter of 2024. This dataset provides - Egypt Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Thailand Unemployment Rate: Whole Kingdom data was reported at 1.000 % in 2024. This records an increase from the previous number of 0.980 % for 2023. Thailand Unemployment Rate: Whole Kingdom data is updated yearly, averaging 0.985 % from Dec 2011 (Median) to 2024, with 14 observations. The data reached an all-time high of 1.930 % in 2021 and a record low of 0.660 % in 2012. Thailand Unemployment Rate: Whole Kingdom data remains active status in CEIC and is reported by Bank of Thailand. The data is categorized under Global Database’s Thailand – Table TH.G024: Labour Force Survey: Age 15 and Over: Labour Force Status and Unemployment Rate: Annual.

South Africa is expected to register the highest unemployment rate in Africa in 2024, with around 30 percent of the country's labor force being unemployed. Djibouti and Eswatini followed, with unemployment reaching roughly 28 percent and 25 percent, respectively. On the other hand, the lowest unemployment rates in Africa were in Niger and Burundi. The continent’s average stood at roughly seven percent in the same year.

Large shares of youth among the unemployed

Due to several educational, socio-demographic, and economic factors, the young population is more likely to face unemployment in most regions of the world. In 2024, the youth unemployment rate in Africa was projected at around 11 percent. The situation was particularly critical in certain countries. In 2022, Djibouti recorded a youth unemployment rate of almost 80 percent, the highest rate on the continent. South Africa followed, with around 52 percent of the young labor force being unemployed.

Wide disparities in female unemployment

Women are another demographic group often facing high unemployment. In Africa, the female unemployment rate stood at roughly eight percent in 2023, compared to 6.6 percent among men. The average female unemployment on the continent was not particularly high. However, there were significant disparities among African countries. Djibouti and South Africa topped the ranking once again in 2022, with female unemployment rates of around 38 percent and 31 percent, respectively. In contrast, Niger, Burundi, and Chad were far below Africa’s average, as only roughly one percent or lower of the women in the labor force were unemployed.

The statistic shows the unemployment rate in India from 1999 to 2023. In 2023, the unemployment rate in India was estimated to be 4.17 percent. India's economy in comparison to other BRIC states India possesses one of the fastest-growing economies in the world and as a result, India is recognized as one of the G-20 major economies as well as a member of the BRIC countries, an association that is made up of rapidly growing economies. As well as India, three other countries, namely Brazil, Russia and China, are BRIC members. India’s manufacturing industry plays a large part in the development of its economy; however its services industry is the most significant economical factor. The majority of the population of India works in this sector. India’s notable economic boost can be attributed to significant gains over the past decade in regards to the efficiency of the production of goods as well as maintaining relatively low debt, particularly when compared to the total amount earned from goods and services produced throughout the years. When considering individual development as a country, India progressed significantly over the years. However, in comparison to the other emerging countries in the BRIC group, India’s progress was rather minimal. While China experienced the most apparent growth, India’s efficiency and productivity remained somewhat stagnant over the course of 3 or 4 years. India also reported a rather large trade deficit over the past decade, implying that its total imports exceeded its total amount of exports, essentially forcing the country to borrow money in order to finance the nation. Most economists consider trade deficits a negative factor, especially in the long run and for developing or emerging countries.

United States Unemployment Rate: HL: Mexican data was reported at 5.000 % in Apr 2025. This records a decrease from the previous number of 5.300 % for Mar 2025. United States Unemployment Rate: HL: Mexican data is updated monthly, averaging 6.500 % from Jan 2003 (Median) to Apr 2025, with 268 observations. The data reached an all-time high of 18.000 % in Apr 2020 and a record low of 3.400 % in May 2023. United States Unemployment Rate: HL: Mexican data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment Rate.

United States Unemployment Rate: PW: NA: OS: excl PH: Personal & Laundry data was reported at 3.800 % in Mar 2025. This records a decrease from the previous number of 4.800 % for Feb 2025. United States Unemployment Rate: PW: NA: OS: excl PH: Personal & Laundry data is updated monthly, averaging 3.400 % from Jan 2000 (Median) to Mar 2025, with 303 observations. The data reached an all-time high of 9.800 % in Apr 2020 and a record low of 0.900 % in Jul 2023. United States Unemployment Rate: PW: NA: OS: excl PH: Personal & Laundry data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G037: Current Population Survey: Unemployment Rate.

United States Unemployment Rate: Black or African American data was reported at 6.100 % in Feb 2025. This records a decrease from the previous number of 6.400 % for Jan 2025. United States Unemployment Rate: Black or African American data is updated monthly, averaging 11.100 % from Jan 1972 (Median) to Feb 2025, with 638 observations. The data reached an all-time high of 21.700 % in Jun 1983 and a record low of 4.400 % in Apr 2023. United States Unemployment Rate: Black or African American data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G037: Current Population Survey: Unemployment Rate.

Statistical open data on LAU regions of Slovakia, Czech Republic, Poland, Hungary (and other countries in the future). LAU1 regions are called counties, okres, okresy, powiat, járás, járási, NUTS4, LAU, Local Administrative Units, ... and there are 733 of them in this V4 dataset. Overall, we cover 733 regions which are described by 137.828 observations (panel data rows) and more than 1.760.229 data points.

This LAU dataset contains panel data on population, on age structure of inhabitants, on number and on structure of registered unemployed. Dataset prepared by Michal Páleník. Output files are in json, shapefiles, xls, ods, json, topojson or CSV formats. Downloadable at zenodo.org.

This dataset consists of:

data on unemployment (by gender, education and duration of unemployment),

data on vacancies,

open data on population in Visegrad counties (by age and gender),

data on unemployment share.

Combined latest dataset

dataset of the latest available data on unemployment, vacancies and population

dataset includes map contours (shp, topojson or geojson format), relation id in OpenStreetMap, wikidata entry code,

it also includes NUTS4 code, LAU1 code used by national statistical office and abbreviation of the region (usually license plate),

source of map contours is OpenStreetMap, licensed under ODbL

no time series, only most recent data on population and unemployment combined in one output file

columns: period, lau, name, registered_unemployed, registered_unemployed_females, disponible_unemployed, low_educated, long_term, unemployment_inflow, unemployment_outflow, below_25, over_55, vacancies, pop_period, TOTAL, Y15-64, Y15-64-females, local_lau, osm_id, abbr, wikidata, population_density, area_square_km, way

Slovakia – SK: 79 LAU1 regions, data for 2024-10-01, 1.659 data,

Czech Republic – CZ: 77 LAU1 regions, data for 2024-10-01, 1.617 data,

Poland – PL: 380 LAU1 regions, data for 2024-09-01, 6.840 data,

Hungary – HU: 197 LAU1 regions, data for 2024-10-01, 2.955 data,

13.071 data in total.

column/number of observations description SK CZ PL HU

period period (month and year) the data is for 79 77 380 197

lau LAU code of the region 79 77 380 197

name name of the region in local language 79 77 380 197

registered_unemployed number of unemployed registered at labour offices 79 77 380 197

registered_unemployed_females number of unemployed women 79 77 380 197

disponible_unemployed unemployed able to accept job offer 79 77 0 0

low_educated unmployed without secondary school (ISCED 0 and 1) 79 77 380 197

long_term unemployed for longer than 1 year 79 77 380 0

unemployment_inflow inflow into unemployment 79 77 0 0

unemployment_outflow outflow from unemployment 79 77 0 0

below_25 number of unemployed below 25 years of age 79 77 380 197

over_55 unemployed older than 55 years 79 77 380 197

vacancies number of vacancies reported by labour offices 79 77 380 0

pop_period date of population data 79 77 380 197

TOTAL total population 79 77 380 197

Y15-64 number of people between 15 and 64 years of age, population in economically active age 79 77 380 197

Y15-64-females number of women between 15 and 64 years of age 79 77 380 197

local_lau region's code used by local labour offices 79 77 380 197

osm_id relation id in OpenStreetMap database 79 77 380 197

abbr abbreviation used for this region 79 77 380 0

wikidata wikidata identification code 79 77 380 197

population_density population density 79 77 380 197

area_square_km area of the region in square kilometres 79 77 380 197

way geometry, polygon of given region 79 77 380 197

Unemployment dataset

time series of unemployment data in Visegrad regions

by gender, duration of unemployment, education level, age groups, vacancies,

columns: period, lau, name, registered_unemployed, registered_unemployed_females, disponible_unemployed, low_educated, long_term, unemployment_inflow, unemployment_outflow, below_25, over_55, vacancies

Slovakia – SK: 79 LAU1 regions, data for 334 periods (1997-01-01 ... 2024-10-01), 202.082 data,

Czech Republic – CZ: 77 LAU1 regions, data for 244 periods (2004-07-01 ... 2024-10-01), 147.528 data,

Poland – PL: 380 LAU1 regions, data for 189 periods (2005-03-01 ... 2024-09-01), 314.100 data,

Hungary – HU: 197 LAU1 regions, data for 106 periods (2016-01-01 ... 2024-10-01), 104.408 data,

768.118 data in total.

column/number of observations description SK CZ PL HU

period period (month and year) the data is for 26 386 18 788 71 772 20 882

lau LAU code of the region 26 386 18 788 71 772 20 882

name name of the region in local language 26 386 18 788 71 772 20 882

registered_unemployed number of unemployed registered at labour offices 26 386 18 788 71 772 20 882

registered_unemployed_females number of unemployed women 26 386 18 788 62 676 20 882

disponible_unemployed unemployed able to accept job offer 25 438 18 788 0 0

low_educated unmployed without secondary school (ISCED 0 and 1) 11 771 9855 41 388 20 881

long_term unemployed for longer than 1 year 24 253 9855 41 388 0

unemployment_inflow inflow into unemployment 26 149 16 478 0 0

unemployment_outflow outflow from unemployment 26 149 16 478 0 0

below_25 number of unemployed below 25 years of age 11 929 9855 17 100 20 881

over_55 unemployed older than 55 years 11 929 9855 17 100 20 882

vacancies number of vacancies reported by labour offices 11 692 18 788 62 676 0

Population dataset

time series on population by gender and 5 year age groups in V4 counties

columns: period, lau, name, gender, TOTAL, Y00-04, Y05-09, Y10-14, Y15-19, Y20-24, Y25-29, Y30-34, Y35-39, Y40-44, Y45-49, Y50-54, Y55-59, Y60-64, Y65-69, Y70-74, Y75-79, Y80-84, Y85-89, Y90-94, Y_GE95, Y15-64

Slovakia – SK: 79 LAU1 regions, data for 28 periods (1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 152.628 data,

Czech Republic – CZ: 78 LAU1 regions, data for 24 periods (2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 125.862 data,

Poland – PL: 382 LAU1 regions, data for 29 periods (1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 626.941 data,

Hungary – HU: 197 LAU1 regions, data for 11 periods (2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023), 86.680 data,

992.111 data in total.

column/number of observations description SK CZ PL HU

period period (month and year) the data is for 6636 5574 32 883 4334

lau LAU code of the region 6636 5574 32 883 4334

name name of the region in local language 6636 5574 32 883 4334

gender gender (male or female) 6636 5574 32 883 4334

TOTAL total population 6636 5574 32 503 4334

Y00-04 inhabitants between 00 to 04 years inclusive 6636 5574 32 503 4334

Y05-09 number of inhabitants between 05 to 09 years of age 6636 5574 32 503 4334

Y10-14 number of people between 10 to 14 years inclusive 6636 5574 32 503 4334

Y15-19 number of inhabitants between 15 to 19 years of age 6636 5574 32 503 4334

Y20-24 number of people between 20 to 24 years inclusive 6636 5574 32 503 4334

Y25-29 number of inhabitants between 25 to 29 years of age 6636 5574 32 503 4334

Y30-34 inhabitants between 30 to 34 years inclusive 6636 5574 32 503 4334

Y35-39 number of inhabitants between 35 to 39 years of age 6636 5574 32 503 4334

Y40-44 inhabitants between 40 to 44 years inclusive 6636 5574 32 503 4334

Y45-49 number of inhabitants younger than 49 and older than 45 years 6636 5574 32 503 4334

Y50-54 inhabitants between 50 to 54 years inclusive 6636 5574 32 503 4334

Y55-59 number of inhabitants between 55 to 59 years of age 6636 5574 32 503 4334

Y60-64 inhabitants between 60 to 64 years inclusive 6636 5574 32 503 4334

Y65-69 number of inhabitants younger than 69 and older than 65 years 6636 5574 32 503 4334

Y70-74 inhabitants between 70 to 74 years inclusive 6636 5574 24 670 4334

Y75-79 number of inhabitants between 75 to 79 years of age 6636 5574 24 670 4334

Y80-84 number of people between 80 to 84 years inclusive 6636 5574 24 670 4334

Y85-89 number of inhabitants younger than 89 and older than 85 years 6636 5574 0 0

Y90-94 inhabitants between 90 to 94 years inclusive 6636 5574 0 0

Y_GE95 number of people 95 years or older 6636 3234 0 0

Y15-64 number of people between 15 and 64 years of age, population in economically active age 6636 5574 32 503 4334

Notes

more examples at www.iz.sk

NUTS4 / LAU1 / LAU codes for HU and PL are created by me, so they can (and will) change in the future; CZ and SK NUTS4 codes are used by local statistical offices, so they should be more stable

NUTS4 codes are consistent with NUTS3 codes used by Eurostat

local_lau variable is an identifier used by local statistical office

abbr is abbreviation of region's name, used for map purposes (usually cars' license plate code; except for Hungary)

wikidata is code used by wikidata

osm_id is region's relation number in the OpenStreetMap database

Example outputs

you can download data in CSV, xml, ods, xlsx, shp, SQL, postgis, topojson, geojson or json format at 📥 doi:10.5281/zenodo.6165135

Counties of Slovakia – unemployment rate in Slovak LAU1 regions

Regions of the Slovak Republic

Unemployment of Czechia and Slovakia – unemployment share in LAU1 regions of Slovakia and Czechia

interactive map on unemployment in Slovakia

Slovakia – SK, Czech Republic – CZ, Hungary – HU, Poland – PL, NUTS3 regions of Slovakia

download at 📥 doi:10.5281/zenodo.6165135

suggested citation: Páleník, M. (2024). LAU1 dataset [Data set]. IZ Bratislava. https://doi.org/10.5281/zenodo.6165135

Unemployment Rate in India decreased to 7.90 percent in February from 8.20 percent in January of 2025. This dataset provides - India Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The dataset obtained consists of details of countries from year 2012-2023. The dataset consists of crime index, safety index, quality of life index, purchasing power index, cost of living index and unemployment rate in each country. Unemployment rate is based on age group 15+, 15-25+ and 25+ attributes.

The dataset is obtained by web scraping and the authenticity of data is not confirmed by the source.

Code used for web scraping: https://www.kaggle.com/code/mrudular/web-scraping-world-indices.

Data sources: 1. https://www.numbeo.com/cost-of-living/ 2. International Labour Organization. ILO modelled estimates database, ILOSTAT. https://ilostat.ilo.org/data/. Accessed 07-09-2023.

Malaysia unemployment rate for 2023 was 3.86%, a 0.08% decline from 2022.

<ul style='margin-top:20px;'>

<li>Malaysia unemployment rate for 2022 was <strong>3.93%</strong>, a <strong>0.71% decline</strong> from 2021.</li>
<li>Malaysia unemployment rate for 2021 was <strong>4.64%</strong>, a <strong>0.1% increase</strong> from 2020.</li>
<li>Malaysia unemployment rate for 2020 was <strong>4.54%</strong>, a <strong>1.28% increase</strong> from 2019.</li>
</ul>Unemployment refers to the share of the labor force that is without work but available for and seeking employment.