Unemployment Insurance Benefits (NYS)

Beneficiary Counts and Benefit Amounts By Region and County

By State of New York [source]

About this dataset

This dataset provides a powerful opportunity to analyze and understand the effects of unemployment insurance in New York State from 2001 to present. It provides a comprehensive overview of the monthly counts for individuals receiving regular unemployment insurance benefits, as well as the total amount of benefits received from New York State. In addition, data are provided for all 10 labor market regions in the state, which enables an assessment of local labor markets and helps inform strategies for improving regional employment outcomes. Moreover, information on out-of-state residents receiving benefits is also included in these data – allowing a unique cross-border examination. Therefore, with this dataset on hand it is possible to gain insights into how recipients are being affected by economic trends across different sectors, cities and counties throughout New York State. With these insightful statistics at our disposal we can better understand who has been affected by financial ups and downs across our state over time – enabling us to take smarter steps forward!

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How to use the dataset

This dataset provides an in-depth look at the number of people receiving regular unemployment insurance benefits in New York State as well as the total amount of these benefits paid out by the state from 2001 through present. The data is broken down by state, labor market region, and county. It includes Unemployment Insurance (UI) Compensation, Compensation for Federal Employees (UCFE), Unemployment Compensation for Ex-Service Members (UCX), Shared Work (SW) and Self Employment Assistance Program (SEAP).

Research Ideas

• Employers in New York can measure the impact of their business decisions on unemployment insurance beneficiaries in their regions over a specific period of time. This can help them better assess the effectiveness of their decisions, and identify where there are gaps that need to be addressed or areas they should focus on.
• Education organizations and institutions can compare unemployment insurance beneficiary trends within counties vs regionally to identify in-demand job concentrations and create programming around those skills sets needed by employers.
• Policymakers can analyze this dataset to understand the current state of unemployment benefits, including frequency of claims, regional variations, and amount paid out per month in order to ensure an equitable distribution of resources throughout the state

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: unemployment-insurance-beneficiaries-and-benefit-amounts-paid-beginning-2001-1.csv | Column name | Description | |:------------------|:-----------------------------------------------------------------------------------| | Year | Year of the data. (Integer) | | Month | Month of the data. (String) | | Region | Region of New York State. (String) | | County | County of New York State. (String) | | Beneficiaries | Number of individuals receiving regular unemployment insurance benefits. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit State of New York.

Unemployment Rate in Germany remained unchanged at 6.30 percent in November. 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.

Initial Claims for UI released by the CT Department of Labor. Initial Claims are applications for Unemployment Benefits. Initial Claims may not result in receiving UI benefits if the individual doesn't qualify. Claims data can be access directly from CT DOL here: https://www1.ctdol.state.ct.us/lmi/claimsdata.asp

The initial claims reported in these tables are "processed" claims to the extent that duplicates and "reopened" claims have been eliminated. The claim counts in this dataset may not match claim counts from other sources.

Claims are disaggregated by age, education, industry, race/national origin, sex, and wages.

The claim counts in this dataset may not match claim counts from other sources.

Unemployment claims tabulated in this dataset represent only one component of the unemployed. Claims do not account for those not covered under the Unemployment system (e.g. federal workers, railroad workers or religious workers) or the unemployed self-employed.

Claims filed for a particular week will change as time goes on and the backlog is addressed.

Continued Claims for UI released by the CT Department of Labor. Continued Claims are total number of individuals being paid benefits in any particular week.

Claims are disaggregated by age, education, industry, race/national origin, sex, and wages.

The claim counts in this dataset may not match claim counts from other sources.

Unemployment claims tabulated in this dataset represent only one component of the unemployed. Claims do not account for those not covered under the Unemployment system (e.g. federal workers, railroad workers or religious workers) or the unemployed self-employed.

Claims filed for a particular week will change as time goes on and the backlog is addressed.

For data on initial claims at the town level, see the dataset "Initial Claims for Unemployment Benefits by Town," here: https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits-by-Town/twvc-s7wy

For data on continued claims see the following two datasets:

"Continued Claims for Unemployment Benefits in Connecticut," https://data.ct.gov/Government/Continued-Claims-for-Unemployment-Benefits-in-Conn/f9e5-rn42

"Continued Claims for Unemployment Benefits by Town," https://data.ct.gov/Government/Continued-Claims-for-Unemployment-Benefits-by-Town/r83t-9bjm

Dataset contains monthly counts, from 2001 to present, of individuals receiving regular unemployment insurance benefits, as well as the total amount of benefits received from New York State.

Data are provided for the state, 10 labor market regions, and counties. State counts can include everyone who receives benefits through New York State (including out-of-state residents) or only state residents who do so (excluding out-of-state residents).

Regular unemployment insurance includes: Unemployment Insurance (UI) Compensation, Compensation for Federal Employees (UCFE), Unemployment Compensation for Ex-Service Members (UCX), Shared Work (SW) and Self Employment Assistance Program (SEAP). It excludes federal extensions and 599.2 training.

Initial Jobless Claims in the United States decreased to 216 thousand in the week ending November 22 of 2025 from 222 thousand in the previous week. This dataset provides the latest reported value for - United States Initial Jobless Claims - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This data has been taken from LGInform at http://lginform.local.gov.uk/ data reference ID 5470 The figures show the numbers of people claiming unemployment benefits aged between 25-49 and living in Plymouth. The data is monthly and shows data ranging from Jan 2013 to May 2017. Number of people claiming unemployment related benefits, aged 25-49 - This is the total number of people aged 24-49 claiming unemployment related benefits (Claimant Count). The Claimant Count is a measure of the number of people claiming benefits principally for the reason of being unemployed, based on administrative data from the benefits system. From April 2015, the Claimant Count includes all Universal Credit claimants who are required to seek work and be available for work, as well as all Jobseeker's Allowance (JSA) claimants, between May 2013 and March 2015, the Claimant Count includes all out of work Universal Credit claimants as well as all JSA claimants prior to this the Claimant Count is a count of the number of people claiming JSA. The Claimant Count includes people who claim unemployment related benefits but who do not receive payment. For example some claimants will have had their benefits stopped for a limited period of time by Jobcentre Plus. Some people claim JSA in order to receive National Insurance Credits. The Claimant Count does not attempt to measure unemployment, which is a concept defined by the International Labour Organisation (ILO) as all those who are out of work, actively seeking work and available to start work. However, since the people claiming benefits are generally a particular subset of the unemployed, the Claimant Count can provide a useful indication of how unemployment is likely to vary between areas and over time. The Claimant Count estimates provide the best available estimates of the number of people claiming unemployment related benefits in the UK. Source name: Nomis Collection name: Claimant county by sex and age Polarity: No polarity Polarity is how sentiment is measured "Sentiment is usually considered to have "poles" positive and negative these are often translated into "good" and "bad" sentiment analysis is considered useful to tell us what is good and bad in our information stream

Unemployment Rate in France increased to 7.70 percent in the third quarter of 2025 from 7.60 percent in the second quarter of 2025. This dataset provides the latest reported value for - France Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Context

This is a paid research survey to explore the linkage between mental illness and unemployment. NAMI has conducted multiple surveys verifying the high unemployment rate among those with mental illness, but this is the only survey to date which targets causation (why they are unemployed). Statistical significance of the variance has long since been proven by previous, larger samples.

You are free to visualize and publish results, please just credit me by name.

Collection methodology

I received several messages about methodology of collection because various people would like to use this data for papers.

• I paid respondents on Survey Monkey in a general population sampling. I did not target any specific demographic as not to get skewed results. Survey Monkey stratifies the sample according to certain characteristics like income and location.

• I know that the general population sampling went well because the number of people self identifying as having a mental illness is consistent with larger samples.

• Although we disqualified people without a mental illness, they were still given the complete survey. That means that the data contains sampling of people with and without mental illness and a yes/no indicator.

Potential area's to investigate

• Linkage between unemployment and education level
• The effect of a gap on your resume on income level
• Symptom/side effects impact on employment
• The effectiveness of social welfare programs
• The linkage between gaps in your resume and hospitalizations due to mental illness

Content

***Sample size:** n = 334; 80 w/ mental illness - this proportion is approximately equal to estimates of the general population diagnosed with mental illness (typically estimated at 20-25% according to various studies).*

Questions:

I identify as having a mental illness Response
Education  Response
I have my own computer separate from a smart phone Response
I have been hospitalized before for my mental illness  Response
How many days were you hospitalized for your mental illness Open-Ended Response
I am currently employed at least part-time Response
I am legally disabled  Response
I have my regular access to the internet  Response
I live with my parents Response
I have a gap in my resume  Response
Total length of any gaps in my resume in months.  Open-Ended Response
Annual income (including any social welfare programs) in USD  Open-Ended Response
I am unemployed Response
I read outside of work and school  Response
Annual income from social welfare programs Open-Ended Response
I receive food stamps  Response
I am on section 8 housing  Response
How many times were you hospitalized for your mental illness  Open-Ended Response

I have one of the following issues in addition to my illness:
  Lack of concentration
  Anxiety
  Depression
  Obsessive thinking
  Mood swings
  Panic attacks
  Compulsive behavior
  Tiredness

Age Response
Gender Response
Household Income  Response
Region Response
Device Type Response

Important data transformation note

When comparing the actual rate to government statistics, it is important to take into account the labor force participation rate (the % of people who are legally considered to be in the workforce). People not included in the unemployment statistic, like discouraged workers (for example the mentally ill) will be "not participating" in the workforce.

Other studies

1. Nami: https://www.nami.org/Press-Media/Press-Releases/2014/Mental-Illness-NAMI-Report-Deplores-80-Percent-Une

2. NIH: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4182106/

Unemployment rates of 25- to 29-year-olds, by educational attainment, Canada and jurisdictions. This table is included in Section E: Transitions and outcomes: Labour market outcomes of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

This dataset contains, by region and county, for each month from January 2002 to present, the number of New York State unemployment insurance average duration. Average Duration is the average number of unemployment insurance weeks beneficiaries receive within their benefit year. Data include only Regular Unemployment Insurance(UI) excluding Unemployment Compensation for Federal Employees (UCFE), Unemployment Compensation for Ex-Service Members (UCX), Shared Work (SW), Self Employment Assistance Program (SEAP), 599.2 training, and federal extension programs. Data are provided for the10 labor market regions, and 62 counties.

Employment Rate in the United States increased to 59.70 percent in September from 59.60 percent in August of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate in Brazil decreased to 5.40 percent in October from 5.60 percent in September of 2025. This dataset provides the latest reported value for - Brazil Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Number of unemployed persons by duration of unemployment, gender and age group, annual.

Quarterly Employment and Wage Data (Timeseries)

Detailed Insights into Local Industries

By State of New York [source]

About this dataset

The Quarterly Census of Employment and Wages (QCEW) program is the most comprehensive labor market data source out there, collecting vital information on employment and wage trends across New York State. It provides a virtual census of 97 percent of the state's nonfarm employees and employers who are covered by the Unemployment Insurance (UI) Law, making it incredibly precise in measuring total wages, establishments, unemployment insurance reports, as well as crucial geographical labor information by state region and county.

At its core, this program seeks to give users a precise quantitative view comparative data that takes into account differences in employee coverage regulatory policy across bureaus or federal laws. All this while taking into consideration factors like agricultural workers, private households employments students or unpaid family workers that are excluded from UI considerations but still count towards Current Employment Statistics totals. This dataset offers an eye-opening look into employment dynamics in New York State; one that you won't find anywhere else! Before using any found data though make sure to review and read through the Terms of Service license requirements first!

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How to use the dataset

The New York Quarterly Employment and Wage Data is an invaluable resource for researchers, students, professionals and policymakers. The data offers a wealth of information on employment status and wages in New York State across all industries. This guide will provide you with a step-by-step introduction to using this dataset.

Research Ideas

• Analyzing small business trends over time to understand hiring trends in the localization and industry level.
• Creating predictive models to forecast future employment levels and wage demands for New York State's departments, businesses, and regions in the upcoming quarters or fiscal years.
• Tracking changes in average wages and employment by industry, region or area type over time to identify potential labor shortages or job losses due to automation or other factors that could lead to policy recommendations at a state level

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: quarterly-census-of-employment-and-wages-quarterly-data-beginning-2000-1.csv | Column name | Description | |:-----------------------|:-----------------------------------------------------------------| | Area Type | The type of area the data is for (String) | | Year | The year the data is for (Integer) | | Quarter | The quarter the data is for (Integer) | | NAICS | The North American Industry Classification System code (Integer) | | NAICS Title | The title of the NAICS code (String) | | Establishments | The number of establishments in the area (Integer) | | Month 1 Employment | The number of employees in the first month (Integer) | | Month 2 Employment | The number of employees in the second month (Integer) | | Month 3 Employment | The number of employees in the third month (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit State of New York.

Social Security Fund: Unemployment: Number of People Receiving Benefit: at the Year End: Beijing data was reported at 209.828 Person th in 2023. This records an increase from the previous number of 165.643 Person th for 2022. Social Security Fund: Unemployment: Number of People Receiving Benefit: at the Year End: Beijing data is updated yearly, averaging 37.450 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 209.828 Person th in 2023 and a record low of 15.600 Person th in 2010. Social Security Fund: Unemployment: Number of People Receiving Benefit: at the Year End: Beijing data remains active status in CEIC and is reported by Ministry of Human Resources and Social Security. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GT: Social Insurance: MOHRSS: Unemployment: No of People Receiving Benefit: By Region.

Social Security Fund: Unemployment: Number of People Receiving Benefit: at the Year End: Anhui data was reported at 90.623 Person th in 2023. This records an increase from the previous number of 80.435 Person th for 2022. Social Security Fund: Unemployment: Number of People Receiving Benefit: at the Year End: Anhui data is updated yearly, averaging 84.500 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 263.800 Person th in 2004 and a record low of 60.600 Person th in 2013. Social Security Fund: Unemployment: Number of People Receiving Benefit: at the Year End: Anhui data remains active status in CEIC and is reported by Ministry of Human Resources and Social Security. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GT: Social Insurance: MOHRSS: Unemployment: No of People Receiving Benefit: By Region.

Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by educational degree, gender and age group, annual.

This dataset, released February 2021, contains statistics relating to the income support recipients of Age pensioners, June 2020; Disability support pensioners, June 2020; Female sole parent pensioners, June 2020; People receiving an unemployment benefit, June 2020; JobSeeker unemployment beneficiaries, June 2020; Young people aged 16 to 21 receiving an unemployment benefit, June 2020; People receiving an unemployment benefit short-term and long-term, June 2017; Low income, welfare-dependent families (with children), June 2017; Children in low income, welfare-dependent families, June 2017; Health Care Card holders, June 2020; Pensioner Concession Card holders, June 2020; Seniors Health Card holders, June 2020; The data is by Local Government Area (LGA) 2016 geographic boundaries. For more information please see the data source notes on the data. Source: Compiled by PHIDU based on data from the Department of Social Services Payment Demographic Data, June 2020; Compiled by PHIDU based on data from the Department of Social Services, June 2017; and the ABS Estimated Resident Population, 30 June 2017; AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Indicators describing the levels of different aspects of wellbeing within the South Australian population: Children -Children aged less than 15 years living in jobless families, 2011 -Children developmentally vulnerable in one or more domains, 2012 -Early school leavers who left school at Year 10 or below, or did not go to school, 2011 Unemployment -Unemployment benefits recipients, June 2014 -Young people aged 16 to 24 years receiving an unemployment benefit, June 2014 -Young people aged 15 to 24 years engaged in learning or earning, 2011 Health -Prevalence of high or very high psychological distress, 2011-13 -Smoking: persons, 2011-13 -Obesity: adults, 2011-13 Overview here: http://dcsi.maps.arcgis.com/apps/MapJournal/index.html?appid=1b84d1ccea924d58ad8247d9f7e8395a

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.