Quarterly Census of Employment and Wages (QCEW) 2016-2017 Labor and Industry

data.pa.gov | Last Updated 13 Aug 2018

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.

Tags: employ, wages, establish, jobs, labor, census, dli

This dataset has the following 10 columns:

Column NameAPI Column NameData TypeDescriptionSample Values
Area Namearea_nametextThe name for the area that the row of data supports. The state of Pennsylvania and all the county names.
County Codecounty_codetextThere are 67 counties in Pennsylvania. They're numbered 01 thru 67, and 00 identifies the statewide total.
State FIPS Codestate_fipstextThe Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify states and counties. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code. The state code is the first two digits of the five digit FIPS code.
County FIPS Codecounty_fipstextFIPS code. The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify counties, is provided with each entry. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code. The County FIPS is the last three digits of the five digit FIPS and the code 000 is for statewide.
Calendar Yearcalendar_yearnumberRepresents the period inclusive of January 1st through December 31st.
NAICSnaicstextThe North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. The NAICS coding hierarchy shared among Canada, Mexico, and the United States ranges from aggregated 2-digit industry sectors to detailed 6-digit country-specific industries. Industries at the 2-, 3-, 4-, and 5-digit NAICS level are comparable among all three countries.
NAICS Titlenaics_titletextThe North American Industry Classification System (NAICS) Title conveys in brief the industries represented by the NAICS code.
EstablishmentsestablishmentsnumberAn employer establishment represents a single economic unit such as a mine, factory or store engaged in one, or predominantly one activity. An employer represents a business entity and may consist of one or more establishments. Establishments represent the 12-month average of monthly counts.
EmploymentemploymentnumberEmployment data under the QCEW program represent the number of covered workers who worked during, or received pay for, the pay period including the 12th of the month. Excluded are members of the armed forces, the self-employed, proprietors, domestic workers, unpaid family workers, and railroad workers. Employment data is presented as the 12-month average of the calendar year. When the field is blank it tells us the data is non-disclosed which has the following meaning: The non-disclosure guidelines essentially exist for one or two reasons: 1) Disclosure of the information would breach confidentiality. 2) The data lacks the statistical rigor to be valid or reliable.
Weekly Wagesweekly_wagesnumberQCEW wages represent total compensation paid during the calendar year, regardless of when services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging. Weekly Wages are derived by dividing total wages reported by average employment and then dividing the quotient by 52 weeks per year. When the field is blank it tells us the data is non-disclosed which has the following meaning: The non-disclosure guidelines essentially exist for one or two reasons: 1) Disclosure of the information would breach confidentiality. 2) The data lacks the statistical rigor to be valid or reliable.