This dataset contains information about the unemployment rate in Austin (SD23 measure EOA.A.1). Texas Workforce Comission provides Texas Labor Market Information for Austin, the Austin Round-Rock MSA, Texas, and the United States. This dataset includes the average number of people in the civilian labor force, the employment count, the unemployment count, and the unemployment rate for Austin, the Austin Round-Rock MSA, Texas, and the United States. The unemployment rate can be useful in understanding economic and workforce trends in Austin over time. View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/Percentage-Unemployment-Rate/ehhu-nafn/

This data shows a summary of annual unemployment rates for cities within the metro Phoenix area and supports Tempe's Unemployment Rate performance measure.The performance measure page is available at 5.13 Unemployment Rate. Additional InformationSource: https://www.bls.gov/Contact (author): Madalaine McConvilleContact E-Mail (author): madalaine_mcconville@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Extracted for selected citiesPublish Frequency: AnnualPublish Method: ManualData Dictionary

This dataset contains unemployment rates for the U.S. (1948 - Present) and California (1976 - Present). The unemployment rate represents the number of unemployed as a percentage of the labor force. Labor force data are restricted to people 16 years of age and older, who currently reside in 1 of the 50 states or the District of Columbia, who do not reside in institutions (e.g., penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces. This rate is also defined as the U-3 measure of labor underutilization.

Analysis of ‘Strategic Measure_Percentage Unemployment Rate’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/fb383985-5de9-4f55-ba17-581333f28ba9 on 26 January 2022.

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

This dataset contains information about the unemployment rate in Austin (SD23 measure EOA.A.1). Texas Workforce Comission provides Texas Labor Market Information for Austin, the Austin Round-Rock MSA, Texas, and the United States.

This dataset includes the average number of people in the civilian labor force, the employment count, the unemployment count, and the unemployment rate for Austin, the Austin Round-Rock MSA, Texas, and the United States. The unemployment rate can be useful in understanding economic and workforce trends in Austin over time.

View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/Percentage-Unemployment-Rate/ehhu-nafn/

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

Unemployment Rate in the United States remained unchanged at 4.20 percent in May. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Data of the US Employment and Unemployment rates since 1940. The data is obtained from the USA Bureau of Labor Statistics and includes the employment status of the civilian noninstitutional population from 1940 to the present day. The numbers in the dataset are measured in thousands and provide important information on the labor market in the US over several decades. This dataset can be used by researchers, policymakers, and analysts to understand the trends and fluctuations in the US labor market, as well as to develop strategies for improving employment and reducing unemployment rates.

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.

This operations dashboard shows historic and current data related to this performance measure. The performance measure dashboard is available at 5.13 Unemployment Rate.Data Dictionary

****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%.

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.

Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

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.

1990 to present (approximate 2 month lag) Virginia Labor Force and Unemployment estimates by Month by County.

Special data considerations: Period values of "M01-M12" represent Months of Year; "M13" is the Annual Average.

U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, table la.data.54.Virginia Data accessed from the Bureau of Labor Statistics public database LABSTAT (https://download.bls.gov/pub/time.series/la/)

Supporting documentation can be found on the U.S. Bureau of Labor Statistics website under Local Area Unemployment Statistics, Handbook of Methods (https://www.bls.gov/opub/hom/lau/home.htm)

Survey Description: Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

To establish uniform labor force concepts and definitions in all States and areas consistent with those used for the U.S. as a whole, monthly national estimates of employment and unemployment from the Current Population Survey are used as controls (benchmarks) for the State labor force statistics.

Summary Data Available: Monthly labor force and unemployment series are available for approximately 7,500 geographic areas, including cities over 25,000 population, counties, metropolitan areas, States, and other areas.

For each area, the following measures are presented by place of residence:

• Total civilian labor force,
• Total number of people employed,
• Total number of people unemployed, and
• Unemployment rate

Data Characteristics: Rates are expressed as percents with one decimal place. Levels are measured as individual persons (not thousands) and are stored with no decimal places.

This data set shows unemployment rate by sex and state in Malaysia for year 1982 until 2020. The statistics is derived from Labour Force Survey (LFS) which is conducted every month using household approach and refers to those between the working age of 15-64 years old. Unemployment rate is the proportion of unemployed population to the total population in the labour force, which measures the percentage of unemployed population in the labour force. W.P. Labuan is gazzeted as a Federal Territory in 1984 while W.P. Putrajaya is gazzeted as a Federal Territory in 2001. The statistics for W.P. Putrajaya for 2001-2010 is treated as part of Selangor. Statistics for W.P. Putrajaya is available separately since 2011 onwards. LFS was not conducted during the years 1991 and 1994.

This data set shows unemployment rate by state in Malaysia for year 1982 until 2020. The statistics is derived from Labour Force Survey (LFS) which is conducted every month using household approach and refers to those between the working age of 15-64 years old. Unemployment rate is the proportion of unemployed population to the total population in the labour force, which measures the percentage of unemployed population in the labour force. W.P. Labuan is gazzeted as a Federal Territory in 1984 while W.P. Putrajaya is gazzeted as a Federal Territory in 2001. The statistics for W.P. Putrajaya for 2001-2010 is treated as part of Selangor. Statistics for W.P. Putrajaya is available separately since 2011 onwards. LFS was not conducted during the years 1991 and 1994.

This dataset contains the Local Area Unemployment Statistics (LAUS), annual averages from 1990 to 2023. The Local Area Unemployment Statistics (LAUS) program is a Federal-State cooperative effort in which monthly estimates of total employment and unemployment are prepared for approximately 7,600 areas, including counties, cities and metropolitan statistical areas. These estimates are key indicators of local economic conditions. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS. Estimates for counties are produced through a building-block approach known as the "Handbook method." This procedure also uses data from several sources, including the CPS, the CES program, state UI systems, and the Census Bureau's American Community Survey (ACS), to create estimates that are adjusted to the statewide measures of employment and unemployment. Estimates for cities are prepared using disaggregation techniques based on inputs from the ACS, annual population estimates, and current UI data.

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

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.

These data are taken from the ANNUAL datasets from the Labour Force Survey (LFS) carried out by the Office for National Statistics (ONS), providing labour market data back to 1996 for the NUTS2 areas in Wales, and back to 2001 for the local authorities in Wales. The availability of local authority data is dependent upon on an enhanced sample (around 350 per cent larger) for the annual LFS, which commenced in 2001. For years labelled 1996 to 2004 in this dataset, the actual periods covered are the 12 months running from March in the year given to February in the following year (e.g. 2001 = 1 March 2001 to 28 February 2002). Since 2004, the annual data have been produced on a rolling annual basis, updated every three months, and the dataset is now referred to as the Annual Population Survey (APS). The rolling annual averages are on a calendar basis with the first rolling annual average presented here covering the period 1 January 2004 to 31 December 2004, followed by data covering the period 1 April 2004 to 31 March 2005, with rolling quarterly updates applied thereafter. Note therefore that the consecutive rolling annual averages overlap by nine months, and there is also a two-month overlap between the last period presented on the former March to February basis, and the first period on the new basis. The population can be broken down into economically active and economically inactive populations. The economically active population is made up of persons in employment, and persons unemployed according to the International Labour Organisation (ILO) definition. This report allows the user to access these data. Although each measure is available for different population bases, there is an official standard population base used for each of the measures, as follows. Population aged 16 and over: Economic activity level, Employment level, ILO unemployment level Population aged 16-64: Economic inactivity level 16-64 population is used as the base for economic inactivity. By excluding persons of pensionable age who are generally retired and therefore economically inactive, this gives a more appropriate measure of workforce inactivity. Rates for each of the above measures are also calculated in a standard manner and are available in the dataset. With the exception of the ILO unemployment rate, each rate is defined in terms of the shares of population that fall into each category. The ILO unemployment rate is defined as ILO unemployed persons as a percentage of the economically active population. Although each rate is available for the different population bases, there is an official standard population base used for each of the rates, as follows. Percentage of population aged 16-64: Economic activity, Employment,. Economic inactivity Percentage of economically active population aged 16 and over: ILO unemployment