The employment and unemployment indicator shows several data points. The first figure is the number of people in the labor force, which includes the number of people who are either working or looking for work. The second two figures, the number of people who are employed and the number of people who are unemployed, are the two subcategories of the labor force. The unemployment rate is a calculation of the number of people who are in the labor force and unemployed as a percentage of the total number of people in the labor force.

The unemployment rate does not include people who are not employed and not in the labor force. This includes adults who are neither working nor looking for work. For example, full-time students may choose not to seek any employment during their college career, and are thus not considered in the unemployment rate. Stay-at-home parents and other caregivers are also considered outside of the labor force, and therefore outside the scope of the unemployment rate.

The unemployment rate is a key economic indicator, and is illustrative of economic conditions in the county at the individual scale.

There are additional considerations to the unemployment rate. Because it does not count those who are outside the labor force, it can exclude individuals who were looking for a job previously, but have since given up. The impact of this on the overall unemployment rate is difficult to quantify, but it is important to note because it shows that no statistic is perfect.

The unemployment rates for Champaign County, the City of Champaign, and the City of Urbana are extremely similar between 2000 and 2023.

All three areas saw a dramatic increase in the unemployment rate between 2006 and 2009. The unemployment rates for all three areas decreased overall between 2010 and 2019. However, the unemployment rate in all three areas rose sharply in 2020 due to the effects of the COVID-19 pandemic. The unemployment rate in all three areas dropped again in 2021 as pandemic restrictions were removed, and were almost back to 2019 rates in 2022. However, the unemployment rate in all three areas rose slightly from 2022 to 2023.

This data is sourced from the Illinois Department of Employment Security’s Local Area Unemployment Statistics (LAUS), and from the U.S. Bureau of Labor Statistics.

Sources: Illinois Department of Employment Security, Local Area Unemployment Statistics (LAUS); U.S. Bureau of Labor Statistics.

Unemployment Rate in China decreased to 5 percent in May from 5.10 percent in April of 2025. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

VITAL SIGNS INDICATOR Unemployment (EC3)

FULL MEASURE NAME Unemployment rate by residential location

LAST UPDATED July 2019

DESCRIPTION Unemployment refers to the share of the labor force – by place of residence – that is not currently employed full-time or part-time. The unemployment rate reflects the strength of the overall employment market.

DATA SOURCE California Employment Development Department: Historical Unemployment Rates 1990-2018 https://data.edd.ca.gov/Labor-Force-and-Unemployment-Rates/Local-Area-Unemployment-Statistics-LAUS-Annual-Ave/7jbb-3rb8

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Unemployment rates produced by EDD for the region and county levels are not adjusted for seasonality (as they reflect annual data) and are final data (i.e., not preliminary). Unemployment rates produced by BLS for the metro regions are adjusted for seasonality; they reflect the primary MSA for the named region, except for the San Francisco Bay Area which uses the nine-county region. The unemployment rate is calculated based on the number of unemployed persons divided by the total labor force. Note that the unemployment rate can decline or increase as a result of changes in either variable.

The unemployment rate is the number of unemployed persons as a percentage of the labour force based on International Labour Office (ILO) definition. The labour force is the total number of people employed and unemployed. The MIP scoreboard indicator considers unemployed persons comprise persons aged 15 to 74 who:

- are without work during the reference week;

- are available to start work within the next two weeks;

- and have been actively seeking work in the past four weeks or had already found a job to start within the next three months.

Unit: rate. The indicative threshold of the indicator is 10%. In the table, values are also calculated by considering unemployed persons aged 15 to 24 and those aged 25 to 74.

Unemployment Rate in Germany remained unchanged at 6.30 percent in May. This dataset provides the latest reported value for - Germany Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Unemployment Rate in Mexico increased to 2.70 percent in May from 2.50 percent in April of 2025. This dataset provides the latest reported value for - Mexico Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The share of the category of unemployed (here men) of the total unemployed is shown. The annual average values were used for the calculation.

Unemployed persons are persons who are temporarily not in an employment relationship or who only work for less than 15 hours per week (unemployment);

seek employment that is subject to insurance at least 15 hours per week (own efforts);

are available to the placement efforts of the Employment Agency or the Job Centre, i.e. to be able to work, be able to work and be ready for work (availability);

living in the Federal Republic of Germany,

are not younger than 15 years and have not yet reached the retirement age limit; and

have personally registered with an agency for work or a job centre without work.

For persons in need of assistance under the SGB II, the definition of unemployment in Paragraph 16 of the SGB III applies mutatis mutandis under Paragraph 53a(1) of the SGB II.

Analysis of ‘Recorded unemployment, January 2021 ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/e0526164-80a3-498e-bd03-5f4e9e7123e6 on 18 January 2022.

--- Dataset description provided by original source is as follows ---

ANOFM calculates and publishes statistical indicators on registered unemployment, as required by the law. Registered unemployed persons represent both the unemployed paid (unemployed jobseekers with work experience benefits and SOMERI recipients of unemployment benefits without work experience/education graduates) as well as the unemployed (without receiving unemployment benefits) and are squeezed on the basis of data from the primary documents and records in the database of territorial employment agencies. Is the stock at the end of the reference month. The unemployment rate recorded is determined as the ratio between the number of unemployed persons registered with the county and Bucharest employment agencies (paid and unpaid) at the end of the reference month and the active civilian population. The civilian active population represents the potential labour supply and employment of the civilian and registered unemployed population. The indicator is determined annually by the National Institute of Statistics by means of the balance of labour at country, development region and county level. The rate of summons is calculated with the population of civil activity on 1 January 2017. The total number of registered SOMERI is structured on: Gender (women, Barbate), Type of compensation (indemnities, non-indemnities); Level of education (without education, primary education, secondary education, upper secondary education, postgraduate education, professional education/arts and trades, university education); Age groups (under 25, 25-29, 30-39, 40-49, 50-55 years, over 55 years). Average residency (urban, rural).The ANOFM calculates and publishes statistics on registered unemployment in accordance with the legal provisions. Registered unemployed persons represent both the unemployed paid (unemployed jobseekers with work experience benefits and SOMERI recipients of unemployment benefits without work experience/education graduates) as well as the unemployed (without receiving unemployment benefits) and are squeezed on the basis of data from the primary documents and records in the database of territorial employment agencies. Is the stock at the end of the reference month. The unemployment rate recorded is determined as the ratio between the number of unemployed persons registered with the county and Bucharest employment agencies (paid and unpaid) at the end of the reference month and the active civilian population. The civilian active population represents the potential labour supply and employment of the civilian and registered unemployed population. The indicator is determined annually by the National Institute of Statistics by means of the balance of labour at country, development region and county level. The rate of summons is calculated with the population of civil activity on 1 January 2017. The total number of registered SOMERI is structured on: Gender (women, Barbate), Type of compensation (indemnities, non-indemnities); Level of education (without education, primary education, secondary education, upper secondary education, postgraduate education, professional education/arts and trades, university education); Age groups (under 25, 25-29, 30-39, 40-49, 50-55 years, over 55 years). Residential environments (urban, rural).

--- Original source retains full ownership of the source dataset ---

****Dataset Overview**** This dataset contains historical macroeconomic data, featuring key economic indicators in the United States. It includes important metrics such as the Consumer Price Index (CPI), Retail Sales, Unemployment Rate, Industrial Production, Money Supply (M2), and more. The dataset spans from 1993 to the present and includes monthly data on various economic indicators, processed to show their rate of change (either percentage or absolute difference, depending on the indicator).

provenance

The data in this dataset is sourced from the Federal Reserve Economic Data (FRED) database, hosted by the Federal Reserve Bank of St. Louis. FRED provides access to a wide range of economic data, including key macroeconomic indicators for the United States. My work involved calculating the rate of change (ROC) for each indicator and reorganizing the data into a more usable format for analysis. For more information and access to the full database, visit FRED's website.

Purpose and Use for the Kaggle Community:

This dataset is a valuable resource for data scientists, economists, and analysts interested in understanding macroeconomic trends, performing time series analysis, or building predictive models. With the rate of change included, users can quickly assess the growth or contraction in these indicators month-over-month. This dataset can be used for:

• Exploratory Data Analysis (EDA): Understanding historical economic trends. -Time Series Forecasting: Building models to predict future economic conditions. -Macroeconomic Analysis: Analyzing the relationship between various economic indicators. -Machine Learning Projects: Using the data as features to predict financial or economic outcomes. -By utilizing this dataset, users can perform in-depth analysis on the impact of macroeconomic changes, compare the historical performance of various indicators, and experiment with different time series forecasting techniques.

****Column Descriptions****

Year: The year of the observation.

Month: The month of the observation (1-12).

Industrial Production: Monthly data on the total output of US factories, mines, and utilities.

Manufacturers' New Orders: Durable Goods: Measures the value of new orders placed with manufacturers for durable goods, indicating future production activity.

Consumer Price Index (CPIAUCSL): A measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services.

Unemployment Rate: The percentage of the total labor force that is unemployed but actively seeking employment.

Retail Sales: The total receipts of retail stores, indicating consumer spending and economic activity.

Producer Price Index: Measures the average change over time in the selling prices received by domestic producers for their output.

Personal Consumption Expenditures (PCE): A measure of the prices paid by consumers for goods and services, used in calculating inflation.

National Home Price Index: A measure of changes in residential real estate prices across the country.

All Employees, Total Nonfarm: The number of nonfarm payroll employees, an important indicator of the labor market.

Labor Force Participation Rate: The percentage of the working-age population that is either employed or actively looking for work.

Federal Funds Effective Rate: The interest rate at which depository institutions lend reserve balances to other depository institutions overnight.

Building Permits: The number of building permits issued for residential and non-residential buildings, a leading indicator of construction activity.

Money Supply (M2): The total money supply, including cash, checking deposits, and easily convertible near money.

Personal Income: The total income received by individuals from all sources, including wages, investments, and government transfers.

Trade Balance: The difference between a country's imports and exports, indicating the net trade flow.

Consumer Sentiment: The index reflecting consumer sentiment and expectations for the future economic outlook.

Consumer Confidence: A measure of how optimistic or pessimistic consumers are regarding their expected financial situation and the economy.

Notes on Interest Rates Please note that for the Federal Funds Effective Rate (FEDFUNDS), the dataset includes the absolute change in basis points (bps), not the rate of change. This means that the dataset reflects the direct change in the interest rate rather than the percentage change month-over-month. The change is represented in basis points, where 1 basis point equals 0.01%.

Civilian labor force data consists of the number of employed persons, the number of unemployed persons, an unemployment rate and the total count of both employed and unemployed persons (total civilian labor force). Labor force refers to an estimate of the number of persons, 16 years of age and older, classified as employed or unemployed. The civilian labor force, which is presented in these data tables, excludes the Armed Forces, i.e., the civilian labor force equals employed civilians plus the unemployed. Employed persons are those individuals, 16 years of age and older, who did any work at all during the survey week as paid employees, in their own business, profession or farm, or who worked 15 hours or more as unpaid workers in a family operated business. Also counted as employed are those persons who had jobs or businesses from which they were temporarily absent because of illness, bad weather, vacation, labor-management dispute, or personal reasons. Individuals are counted only once even though they may hold more than one job. Unemployed persons comprise all persons who did not work during the survey week but who made specific efforts to find a job within the previous four weeks and were available for work during the survey week (except for temporary illness). Also included as unemployed are those who did not work at all, were available for work, but were not actively seeking work because they were either waiting to be called back to a job from which they were laid off or waiting to report to a new job within 30 days. The unemployment rate represents the number of unemployed persons as a percent of the total civilian labor force.

Unemployment Rate in South Africa increased to 32.90 percent in the first quarter of 2025 from 31.90 percent in the fourth quarter of 2024. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate in Thailand increased to 0.89 percent in the first quarter of 2025 from 0.88 percent in the fourth quarter of 2024. This dataset provides the latest reported value for - Thailand Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Percentage of unemployed adults, ages 25 and older. This indicator is calculated as the total number of unemployed adults ages 25 and older divided by the labor force in the same age range, which is the sum of employed and unemployed persons. The result is then multiplied by 100 to calculate the unemployment rate. Name in source: Unemployment rate by sex and age -- ILO modelled estimates, May 2024 (%) -- Annual.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in US unemployment insurance in the pandemic and beyond, PIIE Policy Brief 20-10. If you use the data, please cite as: Furman, Jason. (2020). US unemployment insurance in the pandemic and beyond. PIIE Policy Brief 20-10. Peterson Institute for International Economics.

Unemployment Rate in Hong Kong increased to 3.50 percent in May from 3.40 percent in April of 2025. This dataset provides the latest reported value for - Hong Kong Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This table contains unemployment rates (number of unemployed people aged 15 - 64 divided by those in the labour force in the area) by age group (15 - 24, 25 - 44, 45 - 64) calculated from the 2011 Census for the AURIN Social Indicators project.

Unemployment Rate in Canada increased to 7 percent in May from 6.90 percent in April of 2025. This dataset provides - Canada Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Percentage of youth ages 15-24 who are unemployed. This indicator is calculated as the total number of unemployed persons ages 15-24 divided by the labor force in the same age range, which is the sum of employed and unemployed persons. The result is then multiplied by 100 to calculate the unemployment rate. Name in source: Unemployment rate by sex and age -- ILO modelled estimates, May 2024 (%) -- Annual.

Unemployment rate, participation rate, and employment rate by educational attainment, gender and age group, annual.

Analysis of ‘Recorded unemployment, July 2020 ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/853ede7e-b091-4e95-adc7-811410a79dce on 15 January 2022.

--- Dataset description provided by original source is as follows ---

ANOFM calculates and publishes statistical indicators on registered unemployment, as required by the law. Registered unemployed persons represent both the unemployed paid (unemployed jobseekers with work experience benefits and SOMERI recipients of unemployment benefits without work experience/education graduates) as well as the unemployed (without receiving unemployment benefits) and are squeezed on the basis of data from the primary documents and records in the database of territorial employment agencies. Is the stock at the end of the reference month. The unemployment rate recorded is determined as the ratio between the number of unemployed persons registered with the county and Bucharest employment agencies (paid and unpaid) at the end of the reference month and the active civilian population. The civilian active population represents the potential labour supply and employment of the civilian and registered unemployed population. The indicator is determined annually by the National Institute of Statistics by means of the balance of labour at country, development region and county level. The rate of summons is calculated with the population of civil activity on 1 January 2017. The total number of registered SOMERI is structured on: Gender (women, Barbate), Type of compensation (indemnities, non-indemnities); Level of education (without education, primary education, secondary education, upper secondary education, postgraduate education, professional education/arts and trades, university education); Age groups (under 25, 25-29, 30-39, 40-49, 50-55 years, over 55 years). Average residency (urban, rural).The ANOFM calculates and publishes statistics on registered unemployment in accordance with the legal provisions. Registered unemployed persons represent both the unemployed paid (unemployed jobseekers with work experience benefits and SOMERI recipients of unemployment benefits without work experience/education graduates) as well as the unemployed (without receiving unemployment benefits) and are squeezed on the basis of data from the primary documents and records in the database of territorial employment agencies. Is the stock at the end of the reference month. The unemployment rate recorded is determined as the ratio between the number of unemployed persons registered with the county and Bucharest employment agencies (paid and unpaid) at the end of the reference month and the active civilian population. The civilian active population represents the potential labour supply and employment of the civilian and registered unemployed population. The indicator is determined annually by the National Institute of Statistics by means of the balance of labour at country, development region and county level. The rate of summons is calculated with the population of civil activity on 1 January 2017. The total number of registered SOMERI is structured on: Gender (women, Barbate), Type of compensation (indemnities, non-indemnities); Level of education (without education, primary education, secondary education, upper secondary education, postgraduate education, professional education/arts and trades, university education); Age groups (under 25, 25-29, 30-39, 40-49, 50-55 years, over 55 years). Residential environments (urban, rural).

--- Original source retains full ownership of the source dataset ---