Workforce Data Profile Definitions
Author: Simona Balazs, Blueprint Kentucky Research Director
Definitions:
Workforce by Education & Gender: This graph represents the 2017 distribution of workforce by education level and gender. The data on education by gender come from the U.S. Census Bureau’s Quarterly Workforce Indicators (QWI) and are reported at county level. The dark blue bars represent the percent distribution for Male and the light blue bars for Female.
Workforce by Education & Earnings: Similar with the bar chart on education and gender, this graph represents the 2017 distribution of workforce by education level and earnings. These data are provided also by the U.S. Census Bureau’s Quarterly Workforce Indicators (QWI) and are reported for the selected county. The dark blue bars are for Male and the light blue bars are for Female. While the figure differs for every county, in almost every county the bar chart reveals an income gap between men and women within the education levels.
Area Employment for KY Top 10 Occupations: The table on area employment provides 2019 employment numbers for the top ten occupations in the state of Kentucky, ranked from the highest to smallest. Additionally, employment within these occupations is reported at the regional Area Development District and for the selected county. The 5-year percent change in employment is also provided at the county level. If the percent change is positive, then county employment has increased for this occupation within the given time period. Conversely, if the percent change is negative, then county employment has declined. Data for the top ten occupations in Kentucky and the county were acquired from Chmura/JobsEQ. The occupations are classified based on the Standard Occupational Classification (SOC) system at two-digit level.
Employment & Average Annual Earnings by Age: Data in this table provide the employment and average annual earnings by age groups. These workforce demographic data also come from U.S. Census Bureau’s Quarterly Workforce Indicators (QWI) and are reported for the selected county.
Commuting to Work Characteristics: This table describes commuting patterns of workers in and out of the county. The three measures represent the number of people living outside of the county but who are employed inside (in-commuters), of people who live and work in the selected county and, of people that live in the county but work outside (out-commuters). For any county, how many people in-commute and out-commute affects the county’s economy. In both cases, it is likely that commuters will spend part of their earnings in their county of work and some in their county of residence. In-commuters may shop and dine in your county (especially on lunch break), but they would likely spend more locally if they resided in your county too. Similarly, out-commuters may pay property tax in the county of residence, but they spend part of their earnings in the county where they work. In general, if your county has more in-commuters than out-commuters, then the county has a positive net job flow. Conversely, if your county has fewer in-commuters than out-commuters, then the county has a negative net job flow. These data are provided by U.S. Census OnTheMap and are reported at county level for 2017.
Top 5 Counties People Commute From/To: The table in this section reports the top five outside counties where people commute from (in-commuters) and to (out-commuters) for work. These data are also provided by the U.S. Census OnTheMap for 2017.
Number of Out-commuters by Earnings: This graph illustrates the distribution of people living in the county but working outside of it (out-commuters) for three average annual earnings brackets, for the 2013-2017 time period. The three income brackets are: people with annual earnings of less than $15,000, between $15,000-$40,000, and more than $40,000. If the number of people with average annual earnings >$40,000 is greater than the other two categories, then the county is losing/exporting highly trained workers.
Number of Out-commuters by Industry: The number of out-commuters by three major industry groups (goods producing; trade, transportation and utilities; and, all other services) is represented in the timeline graph at the bottom-right of the page. Ideally, you’d like people living and working in your county in order to limit the dollar-amount leaking outside of the county. The data in this graph can help identify the industry that has the highest leakage/export of workforce for the selected county. Out-commuting data are provided by U.S. Census OnTheMap for 2013-2017.
Data Sources:
- Chmura/JobsEQ 2019, http://www.chmuraecon.com/jobseq/
- U.S. Census/QWI 2017 https://qwiexplorer.ces.census.gov/static/explore.html
- U.S. Census/OnTheMap 2017 https://onthemap.ces.census.gov/