County level educational attainment data on the adult working aged population (25-64) by age range and gender. Data is sourced from the US Census Bureau’s American Community Survey (ACS) 5-year estimates allowing for increased statistical reliability of the data for less populated areas and small population subgroups.

More information here - https://www.census.gov/data/developers/data-sets/acs-5year.html

In Pennsylvania, as in many other places, job-seekers and employers face the shared challenge of a worker shortage. There are currently more job openings than there are available workers to fill them. Both job-seekers and employers must overcome significant barriers for Pennsylvania to close that gap. Five key barriers have been identified through the Command Center's work: child care, transportation, training, reentry, and professional licensure.

Pennsylvania faces a changing economy that's placing new demands on our workers and businesses. Employers are hiring, but the job-skills gap in today's workforce too often leads to a shortage of qualified job candidates. At the same time, too many workers are employed in low-wage jobs and lack the training they need to compete for in-demand careers. To meet these common challenges, state government, the education sector, labor, and industry must all work together to close the skills gap and build a well-trained workforce.

Pennsylvania's current low unemployment rate has created a tight labor market with a shortage of job applicants. Looking ahead, slow population growth and an anticipated surge in retirements present an urgent need to attract more skilled workers to our commonwealth, retain the ones who are already here, and prepare the next generation of workers for in-demand careers.

Attainment data is a 3-year average estimate of the adult, working age population (age 25-64) by age group, gender, and race/ethnicity. Data is based on Public Use Microsample (PUMS) data from the American Community Survey (ACS) downloaded in a custom data set from the IPUMS USA project at the University of Minnesota and summarized for Pennsylvania. Note that the estimates in this data set represent a 3-year average and is not directly comparable to the county-level 5-year county level estimates.

These data describe the percentages of students that attained specific education milestones and objectives. The indictor-level definitions can be found here: Future Ready Glossary

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.

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.

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.

Welcome to Pennsylvania's Innovation Economy Dashboard. This dashboard, along with the report: Pennsylvania's Innovation Economy Annual Report (May 2021), was developed by students at Carnegie Mellon University. The information here focuses on translating new ideas into jobs, developing and maintaining a talented workforce, and connecting workers to jobs--to keep our state prosperous, competitive, and supportive of all Pennsylvanians.