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28 Results
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Local area labor force information. Information by calendar year including labor force, employed, unemployed, and unemployment rate. Statewide and county statistics.
Updated
February 18 2022
Views
1,960
The Pennsylvania Office of Vocational Rehabilitation, or OVR, provides vocational rehabilitation services to help persons with disabilities prepare for, obtain, or maintain employment. OVR provides services to eligible individuals with disabilities, both directly and through a network of approved vendors. Services are provided on an individualized basis.
Updated
April 3 2023
Views
1,672
New Dataset for 2019 - Current by Quarter is now available -
Quarterly Census of Employment and Wages (QCEW) 2019 - Current County Labor and Industry
The Quarterly Census of Employment and Wages (QCEW) dataset provides information about the number of establishments within a geographic area by industry as well as the average number of employees and average weekly wages paid. QCEW is the universe of employment covered under Pennsylvania’s unemployment insurance laws. QCEW employment is based on the location of the position not where the person resides.
Quarterly Census of Employment and Wages (QCEW) 2019 - Current County Labor and Industry
The Quarterly Census of Employment and Wages (QCEW) dataset provides information about the number of establishments within a geographic area by industry as well as the average number of employees and average weekly wages paid. QCEW is the universe of employment covered under Pennsylvania’s unemployment insurance laws. QCEW employment is based on the location of the position not where the person resides.
Updated
May 11 2022
Views
1,833
The information included in this dataset is for the Governor’s Executive Budget and provides key Program Measures by Agency or Office.
Updated
March 23 2023
Views
766
The data represents the percent change in wages for an individual who has wages recorded in the Unemployment Compensation (UC) wage record file in the quarter in which they completed Industry Partnership training and wages found in the UC wage record file for that individual four quarters later. The change could be an increase or a decrease in wages. For example, if an individual completed training in the third quarter of 2013 and earned $5,000 in that quarter and earned $7,500 in the third quarter of 2014 the percent change for that individual would be 50%. The file incudes a count of all individuals who benefited from industry partnership training, the workforce development area of the industry partnership, the training program completed and the percentage change in wages per individual training. The top line of the file includes the overall percentage change for all trainings.
*The goal for Labor & Industry is based on receiving $10 million to fund Industry Partnerships.
This dataset is for Program Year 2013-2017 and will be updated annually due to federal release schedule.
There are many reasons why an individual’s wage may have changed dramatically. Some of the reasons for negative wage changes or large increases in wages are listed below (not an exhaustive list).
• An individual may have left the job, was laid off, or retired within the year after they were trained.
• An individual may have become ill and left work.
• An individual may have accepted a job in or moved to another state.
• An individual may have been working two jobs and switched to one, or vice versa.
• An individual’s hours may have been reduced/increased during a quarter.
• Overtime hours may have been reduced/increased during a quarter.
• An individual may have taken family leave.
• A bonus could have been paid right after training was completed.
• Wage records may not have been reported.
• An employer may have closed and laid off all of their employees.
There are many reasons why an individual’s wage may have changed dramatically. Some of the reasons for negative wage changes or large increases in wages are listed below (not an exhaustive list).
• An individual may have left the job, was laid off, or retired within the year after they were trained.
• An individual may have become ill and left work.
• An individual may have accepted a job in or moved to another state.
• An individual may have been working two jobs and switched to one, or vice versa.
• An individual’s hours may have been reduced/increased during a quarter.
• Overtime hours may have been reduced/increased during a quarter.
• An individual may have taken family leave.
• A bonus could have been paid right after training was completed.
• Wage records may not have been reported.
• An employer may have closed and laid off all of their employees.
Updated
February 21 2022
Views
2,176
Prior Dataset for 2016 - 2018 Annual available - Quarterly Census of Employment and Wages (QCEW) 2016 - 2018 County Labor and Industry
The Quarterly Census of Employment and Wages (QCEW) dataset provides information about the number of establishments within a geographic area by industry as well as the average number of employees and average weekly wages paid. QCEW is the universe of employment covered under Pennsylvania’s unemployment insurance laws. QCEW employment is based on the location of the position not where the person resides.
The Quarterly Census of Employment and Wages (QCEW) dataset provides information about the number of establishments within a geographic area by industry as well as the average number of employees and average weekly wages paid. QCEW is the universe of employment covered under Pennsylvania’s unemployment insurance laws. QCEW employment is based on the location of the position not where the person resides.
Updated
May 18 2023
Views
907
Universities have historically operated under a supply-driven model, wherein learners seek out programs and degrees offered by the institution regardless of business need. In order to better align programs and identify opportunities for university and learner success, new approaches must be undertaken at various levels within the institution. To address this need, the State System conducted original research in 2016 and produced Pennsylvania’s first comprehensive gap analysis study.
Updated
September 13 2022
Views
1,810
Represents a comprehensive collection of occupational wage data available for Pennsylvania. Data are collected through the Occupational Employment Statistics program in cooperation with the U.S. Department of Labor’s Bureau of Labor Statistics. Occupational wage information can be used as a reference by educators, PACareerLink® staff, career counselors, Workforce Development Boards, economic developers, program planners, and others.
Technical Note
Occupational wages do not represent a time series. Due to the prescribed production methodology, current occupational wages are not comparable to previously published occupational wages.
Occupational wages do not represent a time series. Due to the prescribed production methodology, current occupational wages are not comparable to previously published occupational wages.
Updated
October 17 2022
Views
655
Story explaining the information in the Governor’s Executive Budget and provides key Program Measures for the Department of Labor & Industry
Updated
March 30 2023
Views
796
This data set includes the unemployment rate and the labor force participation rate for individuals with and without disabilities as well as the total for all individuals. This data is Pennsylvania specific and is source from the U.S. Census' Current Population Survey (CPS).
The data given for each month is a "rolling" average, which represents the average for the 12 month period ending with the reference month. For example: The July 2019 “People with Disabilities Participation Rate” is the average participation rate of August 2018 – July 2019. The August 2019 rate is the average of September 2018 – August 2019, and so on.
The data given for each month is a "rolling" average, which represents the average for the 12 month period ending with the reference month. For example: The July 2019 “People with Disabilities Participation Rate” is the average participation rate of August 2018 – July 2019. The August 2019 rate is the average of September 2018 – August 2019, and so on.
Updated
May 4 2022
Views
449
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