Graph and download economic data for Unemployment Rate - Black or African American (LNS14000006) from Jan 1972 to Sep 2025 about African-American, 16 years +, household survey, unemployment, rate, and USA.

Graph and download economic data for Unemployment Rate - 16-19 Yrs., Black or African American (LNS14000018) from Jan 1972 to Sep 2025 about 16 to 19 years, African-American, household survey, unemployment, rate, and USA.

In 1990, the unemployment rate of the United States stood at 5.6 percent. Since then there have been many significant fluctuations to this number - the 2008 financial crisis left millions of people without work, as did the COVID-19 pandemic. By the end of 2022 and throughout 2023, the unemployment rate came to 3.6 percent, the lowest rate seen for decades. However, 2024 saw an increase up to four percent. For monthly updates on unemployment in the United States visit either the monthly national unemployment rate here, or the monthly state unemployment rate here. Both are seasonally adjusted. UnemploymentUnemployment is defined as a situation when an employed person is laid off, fired or quits his work and is still actively looking for a job. Unemployment can be found even in the healthiest economies, and many economists consider an unemployment rate at or below five percent to mean there is 'full employment' within an economy. If former employed persons go back to school or leave the job to take care of children they are no longer part of the active labor force and therefore not counted among the unemployed. Unemployment can also be the effect of events that are not part of the normal dynamics of an economy. Layoffs can be the result of technological progress, for example when robots replace workers in automobile production. Sometimes unemployment is caused by job outsourcing, due to the fact that employers often search for cheap labor around the globe and not only domestically. In 2022, the tech sector in the U.S. experienced significant lay-offs amid growing economic uncertainty. In the fourth quarter of 2022, more than 70,000 workers were laid off, despite low unemployment nationwide. The unemployment rate in the United States varies from state to state. In 2021, California had the highest number of unemployed persons with 1.38 million out of work.

In 2024, six percent of the Black or African-American population in the United States were unemployed, the highest unemployment rate of any ethnicity. In 2024, the national unemployment rate stood at four percent.

The unemployment rate for people ages 16 to 24 in the United States in 202024 23 was 10 percent. However, this rate was much lower for people aged 45 and over, at 2.9 percent. U.S. unemployment The unemployment rate in the United States varies based on several factors, such as race, gender, and level of education. Black and African-American individuals had the highest unemployment rate in 2021 out of any ethnicity, and people who had less than a high school diploma had the highest unemployment rate by education level. Alaska is consistently the state with the highest unemployment rate, although the El Centro, California metropolitan area was the area with the highest unemployment rate in the country in 2019. Additionally, in August 2022, farming, fishing, and forestry occupations had the highest unemployment rate in the United States Unemployment rate The U.S. Bureau of Labor Statistics is the agency that researches and calculates the unemployment rate in the United States. Unemployment rises during recessions, which causes the cost of social welfare programs to increase. The Bureau of Labor Statistics says unemployed people are those who are jobless, have looked for employment within the last four weeks, and are free to work.

United States - Unemployment Rate - 20 Yrs. & over, Black or African American Women was 7.50% in September of 2025, according to the United States Federal Reserve. Historically, United States - Unemployment Rate - 20 Yrs. & over, Black or African American Women reached a record high of 18.20 in January of 1983 and a record low of 4.20 in August of 2019. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Unemployment Rate - 20 Yrs. & over, Black or African American Women - last updated from the United States Federal Reserve on December of 2025.

This dataset provides information on the unemployment rates for different demographic groups in the United States.

The data is sourced from the Economic Policy Institute’s State of Working America Data Library and economic research conducted by the Federal Reserve Bank of St. Louis.

The dataset contains unemployment rates for various age groups, education levels, genders, races, and more.

Interesting Task Ideas:

1. See how unemployment rates have changed for different groups of people over time.
2. Look into how education levels can affect unemployment rates.
3. Compare unemployment rates between different races / genders.
4. Check out how unemployment rates can vary across different age groups and genders.
5. Find out if there's a connection between education levels and unemployment rates within specific racial or gender groups.
6. Explore how economic downturns can impact unemployment rates for specific groups of people.
7. Use the data to create visuals that show how unemployment rates differ across all sorts of factors.

Don't forget to upvote this dataset if you find it useful! 😊💝

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Column Descriptions

In the second quarter of 2024, the unemployment rate among Black South Africans was 36.9 percent, marking a year-on-year change of 0.8 percent compared to the second quarter of 2023. On the other hand, the unemployment rate among white South Africans was 7.9 percent in the second quarter of 2024, with a 0.5 percent year-on-year change. Unemployment prevalent among youth and women The unemployment rate is the share of the labor force population that is unemployed, while the labor force includes individuals who are employed as well as those who are unemployed but looking for work. South Africa is struggling to absorb its youth into the job market. For instance, the unemployment rate among young South Africans aged 15-24 years reached a staggering 60.7 percent in the second quarter of 2023. Furthermore, women had higher unemployment rates than men. Since the start of 2016, the unemployment rate of women has been consistently more than that of men, reaching close to 36 percent compared to 30 percent, respectively. A new minimum wage and most paying jobs      In South Africa, a new minimum hourly wage went into effect on March 1, 2022. The minimum salary reached 23.19 South African rand per hour (1.44 U.S. dollars per hour), up from 21.69 South African rand per hour (1.35 U.S. dollars per hour) in 2021. In addition, the preponderance of employed South Africans worked between 40 and 45 hours weekly in 2021. Individuals holding Executive Management and Change Management jobs were the highest paid in the country, with salaries averaging 74,000 U.S. dollars per year.

Unemployment Rate in the United States increased to 4.40 percent in September from 4.30 percent in August of 2025. 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.

Unemployment Rate in South Africa decreased to 31.90 percent in the third quarter of 2025 from 33.20 percent in the second quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate: Foreign Born data was reported at 3.600 % in Apr 2025. This records a decrease from the previous number of 4.400 % for Mar 2025. Unemployment Rate: Foreign Born data is updated monthly, averaging 4.800 % from Jan 2007 (Median) to Apr 2025, with 220 observations. The data reached an all-time high of 16.500 % in Apr 2020 and a record low of 2.600 % in Oct 2019. Unemployment Rate: Foreign Born 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.

Unemployment Rate in Canada decreased to 6.90 percent in October from 7.10 percent in September of 2025. This dataset provides - Canada Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate in Australia decreased to 4.30 percent in October from 4.50 percent in September of 2025. This dataset provides - Australia Unemployment Rate at 5.8% in December - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Unemployment Rate - Hispanic or Latino (LNS14000009) from Mar 1973 to Sep 2025 about latino, hispanic, 16 years +, household survey, unemployment, rate, and USA.

Unemployment Rate in Spain increased to 10.45 percent in the third quarter of 2025 from 10.29 percent in the second quarter of 2025. This dataset provides the latest reported value for - Spain Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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 CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

In any society, the human element represents the basis of the work force which exercises all the service and production activities. Therefore, it is a mandate to produce labor force statistics and studies, that is related to the growth and distribution of manpower and labor force distribution by different types and characteristics.

In this context, the Central Agency for Public Mobilization and Statistics conducts "Quarterly Labor Force Survey" which includes data on the size of manpower and labor force (employed and unemployed) and their geographical distribution by their characteristics.

By the end of each year, CAPMAS issues the annual aggregated labor force bulletin publication that includes the results of the quarterly survey rounds that represent the manpower and labor force characteristics during the year.

---> Historical Review of the Labor Force Survey:

1- The First Labor Force survey was undertaken in 1957. The first round was conducted in November of that year, the survey continued to be conducted in successive rounds (quarterly, bi-annually, or annually) till now.

2- Starting the October 2006 round, the fieldwork of the labor force survey was developed to focus on the following two points: a. The importance of using the panel sample that is part of the survey sample, to monitor the dynamic changes of the labor market. b. Improving the used questionnaire to include more questions, that help in better defining of relationship to labor force of each household member (employed, unemployed, out of labor force ...etc.). In addition to re-order of some of the already existing questions in much logical way.

3- Starting the January 2008 round, the used methodology was developed to collect more representative sample during the survey year. this is done through distributing the sample of each governorate into five groups, the questionnaires are collected from each of them separately every 15 days for 3 months (in the middle and the end of the month)

4- Starting the January 2012 round, in order to follow the international recommendation, to avoid asking extra questions that affect the precision and accuracy of the collected data, a shortened version of the questionnaire was designed to include the core questions that enable obtaining the basic Egyptian labor market indicators. The shortened version is collected in two rounds (January-March), (April-June), and (October-December) while the long version of the questionnaire is collected in the 3rd round (July-September) that includes more information on housing conditions and immigration.

---> The survey aims at covering the following topics:

1- Measuring the size of the Egyptian labor force among civilians (for all governorates of the republic) by their different characteristics. 2- Measuring the employment rate at national level and different geographical areas. 3- Measuring the distribution of employed people by the following characteristics: Gender, age, educational status, occupation, economic activity, and sector. 4- Measuring unemployment rate at different geographic areas. 5- Measuring the distribution of unemployed people by the following characteristics: Gender, age, educational status, unemployment type “ever employed/never employed”, occupation, economic activity, and sector for people who have ever worked.

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 of urban and rural areas in all the governorates.

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 CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

---> Sample Design and Selection

At the beginning of the first quarter in 2018 (January-March),the sample design was developed. sample size was withdrawn 50% of the (panel households) visited in the same quarter last year and 50% of the sample size (new households) visited for the first time, as well as to divide the sample of each governorate into six parts instead of five , in addition to Develop research questions according to the goals of Nineteenth Congress of Labor Statistics held at Geneva in 2013, therefore new questions to measure informal employment and the informal sector. An application for the new questionnaire has been designed and implemented on the tablet, Entry application has been designed for the new questionnaire so that the question will be completed on the field and then The data is entered through the researchers at the offices, correcting the errors first-hand and returning to the family again and sending data daily.

The sample of Labor Force Survey is a two-stage stratified cluster sample and selfweighted to the extent practical.

The main elements of the sampling design are described as follows:

• Sample Size The sample size in each quarter is 22,500 households with a total number of 80825 households . These households are distributed on the governorate level (urban/rural), according to the estimated number of households in each governorate in accordance with the percentage of urban and rural population in each governorate.

• Cluster size The cluster size is 18 households.

• Sampling stages:

  (1) Primary Sampling Unit (PSU): The 2006 Population Census provided sufficient data at the level of the Enumeration Area (EA). Hence, the electronic list of EA's represented the frame of the first stage sample; in which the corresponding number of households per EA was taken as a measure of size. The size of an EA is almost 200 households on average, with some variability expected. The size of first stage national sample was estimated to be 5,024 EA.

  (2) Sample Distribution by Governorate: The primary stratifying variable is the governorate of residence, which in turn is divided into urban and rural sub-strata, whenever applicable.

  (3) First Stage Sample frame: The census lists of EAs for each substratum, associated with the corresponding number of households, constitute the frame of the first stage sample. The identification information appears on the EA's list includes the District code, Shiakha/Village code, Census Supervisor number, and Enumerator number. Prior to the selection of the first stage sample, the frame was arranged to provide implicit stratification with regard to the geographic location. The urban frame of each governorate was ordered in a serpentine fashion according to the geographic location of kism/ district capitals. The same sort of ordering was made on the rural frame, but according to the district location. The systematic selection of EA's sample from such a sorted frame will ensure a balanced spread of the sample over the area of respective governorates. The sample was selected with Probability Proportional to Size (PPS), with the number of census households taken as a Measure of Size (MOS).

  (4) Core Sample allocation The core sample EAs (5,024) were divided among the survey 4 rounds, each round included 1,271 EAs (546 in urban areas and 725 in rural areas).

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire design follows the latest International Labor Organization (ILO) concepts and definitions of labor force, employment, and unemployment.

The questionnaire comprises 4 tables in addition to the identification and geographic data of household on the cover page.

---> Table 1- The housing conditions of the households

This table includes information on the housing conditions of the household: - Type of the dwelling, - Tenure of the dwelling (owned/rent) , - Availability of facilities and services connected to the house - Ownership of durables.

---> Table 2- Demographic and employment characteristics and basic data for all household individuals

Including: gender, age, educational status, marital status, residence mobility and current work status

---> Table 3- Employment characteristics table

This table is filled by employed individuals at the time of the survey or those who were engaged to work during the reference week, and provided information on: - Relationship to employer: employer, self-employed, waged worker, and unpaid family worker - Economic activity - Sector - Occupation - Effective working hours - Health and social insurance - Work place - Contract type - Average monthly wage

---> Table 4- Unemployment characteristics table

This table is filled by all unemployed individuals who satisfied the unemployment criteria, and provided information on: - Type of unemployment (unemployed, unemployed ever worked) - Economic

In 2024, the unemployment rate of both sexes aged 15 years and over in all industries in Canada stood at 6.3 percent. Between 1976 and 2024, the figure dropped by 0.8 percentage points, though the decline followed an uneven course rather than a steady trajectory.

The data covers job search activities and employment outcomes for participants in an online study on the provision of occupational recommendations to job seekers.

Providing job search assistance to job seekers in a cost effective manner is a challenging goal. Interventions aimed at providing tailored advice typically involve large personnel costs that often dissipate the benefits. However, the advances in information technologies and the shift of formal job search to online platforms over the last 20 years offer new opportunities for providing advice at very low-cost. In this study we examine the potential for providing on-line advice to a population of hard-to-place job seekers.

In a randomized field experiment, we provided suggestions about suitable alternative occupations to long-term unemployed job seekers. The suggestions were automatically generated, integrated in an online job search platform, and fed into actual search queries. Effects on the primary pre-registered outcomes of "finding a stable job" and "reaching a cumulative earnings threshold" are positive, large, and are more pronounced for those who are longer unemployed. Treated individuals include more occupations in their search and find more jobs in recommended occupations.

The crisis and its aftermath have thrown up many challenges for macroeconomics. For the past thirty years the predominant methodology in macroeconomics has been a class of models that assume an absence of heterogeneity across firms, individuals, etc., and assume that individuals have access to well-functioning insurance markets.

These models have been widely criticised for providing no insight into the current crisis. The crisis has highlighted i) the extreme nature of labour market responses as unemployment has remained high while nominal wages have remained inflexible; ii) the importance of credit markets in generating as well as propagating shocks.. It is our view that that a deeper understanding of credit and labour markets, how they interact and how shocks in these markets aggregate and propagate is fundamental to the understanding of the macroeconomy. This agenda requires building a model of the economy based on realistic features of credit and labour markets including differences in information among agents, differences in attitudes towards risk, the inability to specify or contract upon all future contingencies, and recognising the limits of contractual enforceability. It requires an understanding of how behaviour in individual markets aggregates and how, in turn, the macroeconomic environment feeds back to individual markets. Our aim is to transform research in macroeconomics and to build its foundations on a thorough understanding of credit and labour markets.

Credit markets: We will consider why financial markets occasionally dry up, why banks simultaneously borrow and lend to each other and how this affects financial risk and monetary policy. An important component of this analysis is that differences in information between holders of assets and potential buyers creates illiquidity, that is, holders find it costly to reverse an asset trade once made. The relationship between contagious illiquidity and market failure, such as we have seen in the financial crisis, is a core element of this theme.

Labour markets: Traditional models have difficulties accounting for the fluctuations, and the sluggishness in responses, of employment and wages. We will investigate this issue from two angles. First, we will look into the black-box of standard job search models by examining how job-seekers determine which jobs to apply for, how this changes with unemployment and how selections depend on occupation, salary and travel distance. Second, we will examine the nature of the employment relationship after job search is completed, its durability, the evolution of wages and productivity and the dependence of both on current, past, and anticipated macroeconomic conditions.

The macroeconomy: An economy is the aggregation of the activities in individual markets. It is important to know if behaviour at the level of individual markets is amplified or washed-out at the aggregate level. For example, if employment responses at the firm level are sluggish, does this imply sluggish responses at the macro level? Understanding this aggregation issue requires insight into the structure of employment responses at the firm level. We expect that the joint analysis of credit and labour markets and how they aggregate will provide new insights for the understanding of the macroeconomy.

About the Dataset:

Amazon is one of the biggest online retailers in the USA that sells over 12 million products. With this dataset, you can get an in-depth idea of what products sell best, which SEO titles generate the most sales, the best price range for a product in a given category, and much more.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

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Interesting Task Ideas:

1. Uncover trending product categories and their sales performance.
2. Analyze customer ratings to find top-rated products.
3. Train a product title generator that can generate sales-worthy product titles based on products with the most sales.
4. Gain insight into the best price for any given product based on sales data and competition.
5. Identify which niches are the easiest to make sales in.
6. Gain insights into the general spending habits of online shoppers.
7. Use as a seed dataset for practicing database management and performance optimization.
8. Train (or learn to train) an AI-based search model to recommend Amazon products.

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The unemployment rate in South Africa stood at 33.17 percent in 2024. Between 1991 and 2024, the unemployment rate rose by 10.17 percentage points, though the increase followed an uneven trajectory rather than a consistent upward trend.