Regional unemployment rates used by the Employment Insurance program, by effective date, current month.

Table depicting the rate of unemployment within the Employment Insurance Regions across Canada.

In 2024, the Canadian province of Newfoundland and Labrador had the highest unemployment rate in Canada. That year, it had a ten percent unemployment rate. In comparison, Québec had the lowest unemployment rate at 5.3 percent. Nunavut Nunavut is the largest and most northern province of Canada. Their economy is powered by many industries which include mining, oil, gas, hunting, fishing, and transportation. They have a high amount of mineral resources and many of their jobs come from mining, however, the territory still suffers from a high unemployment rate, which has fluctuated since 2004. The lack of necessary education, skills, and mobility are all factors that play a part in unemployment. Most of the population identifies as Inuit. Their official languages include English, French, and several Inuit languages. The capital is Iqaluit, which is their largest community and only city. The climate in Nunavut is a polar climate due to its high latitude, and as a result, it rarely goes above 50 degrees Fahrenheit. Unemployment in Canada The unemployment rate in Canada had been decreasing since 2009, but increased to 9.7 percent in 2020 due to the impact of the coronavirus pandemic. Since 2006, landed immigrants have faced higher unemployment rates compared to those born in Canada. Youth unemployment in Canada has fluctuated since 1998, but has always remained in the double digits. Additionally, the average duration of unemployment in Canada in 2023 was about 17.4 weeks.

View monthly updates and historical trends for Ontario Unemployment Rate. Source: Statistics Canada. Track economic data with YCharts analytics.

Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by province, territory and economic region, last 5 years.

Regional unemployment rates used by the Employment Insurance program, by effective date, current month.

This table contains 296 series, with data for years 2006 - 2013 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (148 items: Canada; Newfoundland and Labrador; Eastern Regional Integrated Health Authority, Newfoundland and Labrador; Central Regional Integrated Health Authority, Newfoundland and Labrador; ...); Unemployment rate (2 items: Unemployment rate, 15 years and over; Unemployment rate, 15 to 24 years).

Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate and employment rate by Atlantic region, Central provinces, Western provinces, Indigenous population (First Nations or Métis) and Non-Indigenous population, sex, and age group, last 5 years.

LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, data on wage rates, union status, job permanency and establishment size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Statistical activity Together, four statistical programs tell a more complete story of current labour market events. These programs are: the Labour Force Survey (LFS), the Survey of Employment, Payrolls and Hours (SEPH), Employment Insurance Statistics (EIS), and the Job Vacancy and Wage Survey (JVWS). Every month, the LFS provides timely data on the labour market, including the unemployment rate and demographic analysis. Later on, the SEPH report shows greater detail on non-farm industry employment and earnings and the JVWS supplies preliminary indicators on job vacancies. EIS provides substantial detail on Employment Insurance benefits by geography, socio-demographics and former occupation. Every quarter, the JVWS provides detailed information on job vacancies by occupation and economic region.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by province, gender and age group. Data are presented for 12 months earlier, previous month and current month, as well as year-over-year and month-to-month level change and percentage change. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

This statistic shows the unemployment rate in Canada in June 2024, by metropolitan area. In 2024, about *** percent of the labor force in the Calgary metropolitan area (Alberta) was unemployed.

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector.This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). It contains both personal characteristics for all individuals in the household and detailed labour force characteristics for household members 15 years of age and over. The personal characteristics include age, sex, marital status, educational attainment, and family characteristics. Detailed labour force characteristics include employment information such as class of worker, usual and actual hours of work, employee hourly and weekly wages, industry and occupation of current or most recent job, public and private sector, union status, paid or unpaid overtime hours, job permanency, hours of work lost, job tenure, and unemployment information such as duration of unemployment, methods of job search and type of job sought. Labour force characteristics are also available for students during the school year and during the summer months as well as school attendance whether full or part-time and the type of institution.LFS revisions: Labour force surveys are revised on a periodic basis, either to adopt the most recent geography, industry and occupation classifications; to use new observations to fine-tune seasonal adjustment factors; or to introduce methodological enhancement. Prior LFS revisions were conducted in 2011, 2015 and 2021. The most recent revisions to the LFS were conducted in 2023. The first major change was a transition to the National Occupational Classification (NOC) 2021 V1.0, with all LFS series from 1987 onwards having been revised to the new classification. The second major change were methodological enhancements to LFS data processing, applied to all LFS series beginning Jan 2006. The third major change was a revision of seasonal adjustment factors, applied to LFS series Jan 2002 onward. A list of prior versions of this LFS dataset can be found under the ‘Versions’ tab.

New York State Unemployment Insurance Average Duration (2002-Present)

Regional and County Level Trends

By State of New York [source]

About this dataset

This dataset provides crucial insights on the unemployment benefits of New York State residents, unveiling the average duration of unemployment insurance security they receive during their benefit year. From January 2002 to present, discover trends related to ten labor market regions, recapping intricate information gathered from 62 counties and subdivisions. With a simple download of data including columns such as Year, Month, Region, County and Average Duration who insight can be provided with proper understanding and interpretation.

As each region has distinct characteristics this dataset contains a broad spectrum of data types ranging from regular unemployment insurance (UI) cases not associated with Federal Employees (UCFE), Veterans (UCX), Self Employment Assistance Program (SEAP) or other situations to Shared Work programs including 599.2 training or Federal extensions recipients all adding tremendous value for users leveraging it responsibly. Before using the data make sure you read the Terms of Service in order to understand any legal requirements related executing use right upon installation! Last updated at 2020-09-16 this dataset is an April Fools gift not just for passionate researchers but also community impact leaders seeking direction when addressing prevalent social problems!

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How to use the dataset

This dataset contains data on the average duration of unemployment insurance benefits in New York state from 2002 to present. This data can be useful for analyzing trends in unemployment rates, understanding regional differences, and evaluating labor market changes over time. In this guide we will explore how to use this dataset for your own research and analysis.

Firstly, you'll need to download the dataset from Kaggle. Once downloaded, you can open it with a spreadsheet program such as Microsoft Excel or Google Sheets to begin exploring the data.

The columns of the dataset that are available include Year, Month, Region, County, and Average Duration. Year indicates what year the related month's data falls under while Month shows which month that number corresponds with. Region and County represent the geographic areas these numbers are describing within New York State whereas Average Duration provides an indication of how long beneficiaries received their unemployment insurance benefits within their benefit year period on average within each given area.

Using these columns as your guide you can start analyzing different aspects of state-level unemployment trends in New York over time or compare counties’ benefit level information against each other during any given year or specific month by filtering accordingly using Pivot Tables or Visualizations tools such as Microsoft Power BI and Tableau Desktop/Desktop Server depending on what type of analysis you want to conduct further down (e..g clustering/kmeans algorithms etc). You may also consider combining this with other macroeconomic datasets such as GDP growth rate per county/region etc., if applicable for further insight into factors influencing unemployed benefit duration levels over time etc.. Depending upon your objective make sure to review reference material cited at bottom part & ensure that all applicable terms & conditions have been read & accepted prior to proceeding further on research at hand!

In conclusion ,this is a comprehensive yet easy-to-use source if you're looking for a detailed overview when examining Unemployment Insurance Average Duration across various geographic regions within New York State between 2002 up until present day! We hope that this guide outlined has been helpful in getting started with understanding insights relevant behind utilizing this powerful yet versatile dataset made available courtesy via Kaggle platform today!

Research Ideas

• Comparing current to historical unemployment insurance average duration trends (e.g. year over year, month to month).
• Analyzing correlations between unemployment insurance average duration and other economic factors such as housing prices or wage growth in a particular county or region.
• Mapping the distributions of unemployment insurance average duration across different regions and counties in New York State, providing useful insights into regional economic differences within the state that can inform policy decision-making by local governments

Acknowledgements

If you use this data...

Labour force characteristic estimates by visible minority group, region, age group, and gender.

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

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.

Labour Force Survey The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. The LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. Objective The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Collection This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). It contains both personal characteristics for all individuals in the household and detailed labour force characteristics for household members 15 years of age and over. The personal characteristics include age, sex, marital status, educational attainment, and family characteristics. Detailed labour force characteristics include employment information such as class of worker, usual and actual hours of work, employee hourly and weekly wages, industry and occupation of current or most recent job, public and private sector, union status, paid or unpaid overtime hours, job permanency, hours of work lost, job tenure, and unemployment information such as duration of unemployment, methods of job search and type of job sought. Labour force characteristics are also available for students during the school year and during the summer months as well as school attendance whether full or part-time and the type of institution. LFS revisions: Labour force surveys are revised on a periodic basis. The most recent revisions took place in 2025. As of January 2025, LFS microdata and estimates have been adjusted to reflect population counts from the 2021 Census, with revisions going back to 2011. Additionally, several changes were made to key variables on the PUMFs: Survey weights (FINALWT) have been updated to use 2021 Census population control totals. Sub-provincial geography (CMA) has been updated to the 2021 Standard Geographical Classification (SGC) boundaries. All industry data (NAICS_21) was revised to use the latest standard, North American Industry Classification System (NAICS) 2022. Coding enhancements were applied to improve longitudinal consistency of detailed National Occupational Classification data (NOC_10 and NOC_43). Data were revised to use the gender of person instead of sex (GENDER).

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Note: Because missing values are removed from this dataset, any form of non-response (e.g. valid skip, not stated) or don't know/refusal cannot be coded as a missing. The "Sysmiss" label in the Statistics section indicates the number of non-responding records for each variable, and the "Valid" values in the Statistics section indicate the number of responding records for each variable. The total number of records for each variable is comprised of both the sysmiss and valid values. LFS revisions: LFS estimates were previously based on the 2001 Census population estimates. These data have been adjusted to reflect 2006 Census population estimates and were revised back to 1996. The census metropolitan area (CMA) variable has been expanded from the three largest CMAs in Canada to nine. Two occupation variables based on the 2016 National Occupation Classicifcation have been reintroduced: a generic 10- category variable (NOC_10) and a detailed 40-category variable (NOC_40). A new variable on immigrant status (IMMIG) has been introduced, which distingushes between recent immigrants and established immigrants. Fourteen variables related to family and spouse/partner's labour force characteristics have been removed, as well as eight out of date variables which have been removed from the record layout.