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-- U.S. by County 2023 Annual by Detailed Type of Business September 2023 .. the changing number of establishments, employment and earnings by county and type of business has some might impact on most organizations. This section is focused on quarterly/annual data based on employer reported data that provide characteristics of establishments, employment and earnings (EEE) by detailed type of business. These data are collected and tabulated by the Bureau of Labor Statistics BLS QCEW program. Derived from reports submitted by every employer subject to unemployment insurance (UI) laws, the data cover 9.5 million employers and 136.2 million full- and part-time workers. Use the interactive table below to see that for Orange County, CA in 2023, among private sector employers, the "Real Estate and Rental and Leasing" sector had the highest average annual pay of $151,150 among all sectors. And, that among all counties, Santa Clara, CA had the highest average annual pay of $462,468 in that sector. Use the table to learn how industry sectors in one county compares to others. Why these data are important ... • source of unique insights into levels of EEE and how EEE are changing • available for all counties, metros, states and the U.S. • available for detailed types of business (6-digit NAICS) • quarterly and annual data enable time-series modeling • employer-based administratively collected data; not estimates • short lag (6 months) between reporting date and date of data accessibility Limitations of these data Accessing & Using these Data ... • part of the Workforce Insights Program data for subcounty geography QCEW data suppression removed accessible for time-series analysis • using VDAGIS & DEDE tools 2023 Establishments, Employment, Earnings by Type of Business by County .. Interactive Table .. goto top each row shows attributes for a county iterated by owner type and divisional level type of business more about these data click ShowAll button between queries. click column header to sort; click again to sort other direction. Usage Notes - Examine industry characteristics for a county of interest; click Find StCty button below table. -- enter state-county code in edit box then click Find StCty button. -- default code 06059 is Orange County, CA. - Click ShowAll button between queries. - Click column header to sort; click again to sort other direction. - try these codes: 20173: Sedgwick (Wichita), KS; 51059 Fairfax County, VA -- click ShowAll between queries. Data suppression. Employment and pay are suppressed to help insure confidentiality of businesses that dominate and particular type of business in a particular county. In these cases, an "N" appears in the disclosure column and employment and pay cells show as zero in the table. As an example, see that when selecting type of industry/business as Manufacturing, there are 382 counties (of 3,142 total counties) that have suppressed employment and pay (number of establishments are always shown). Column Desriptions (in development) 1 GEOID FIPS code 2 own_code ownership code 3 industry_code code (NAICS) 4 agglvl_code aggregation level code 5 size_code size code 6 year year 7 qtr quarter (always A for annual) 8 disclosure_code disclosure code (either ' '(blank) or 'N' not disclosed) 9 annual_avg_estabs annual average of quarterly establishment counts for a given year 10 annual_avg_emplvl Annual average of monthly employment levels for a given year 11 total_annual_wages Sum of the four quarterly total wage levels for a given year 12 taxable_annual_wages Sum of the four quarterly total taxable wage totals for a given year 13 annual_contributions Sum of the four quarterly contribution totals for a given year 14 annual_avg_wkly_wage Average weekly wage based on the 12-monthly employment levels and total annual wage levels. 15 avg_annual_pay Average annual pay based on employment and wage levels for a given year. 16 lq_disclosure_code location-quotient disclosure code (either '' (blank) or 'N' not disclosed) 17 lq_annual_avg_estabs location quotient of annual average establishment count relative to the U.S. (Rounded to the hundredths place) 18 lq_annual_avg_emplvl location quotient of annual average employment relative to the U.S. (Rounded to the hundredths place) 19 lq_total_annual_wages Location quotient of total annual wages relative to the U.S. (Rounded to the hundredths place) 20 lq_taxable_annual_wages Location quotient of taxable annual wages relative to the U.S. (Rounded to the hundredths place) 21 lq_annual_contributions Location quotient of total annual contributions relative to the U.S. (Rounded to the hundredths place) 22 lq_annual_avg_wkly_wage Location quotient of annual average weekly wage relative to the U.S. (Rounded to the hundredths place) 23 lq_avg_annual_pay Location quotient of annual average pay relative to the U.S. (Rounded to the hundredths place) 24 oty_disclosure_code over-the-year disclosure code (either ' '(blank) or 'N' not disclosed) 25 oty_annual_avg_estabs_chg Over-the-year change in annual average establishments for a given year 26 oty_annual_avg_estabs_pct_chg over-the-year percent change in annual average establishments for a given year (Rounded to the tenths place) 27 oty_annual_avg_emplvl_chg Over-the-year change in annual average employment for a given year 28 oty_annual_avg_emplvl_pct_chg Over-the-year percent change in annual average employment for a given year (Rounded to the tenths place) 29 oty_total_annual_wages_chg Over-the-year change in the total annual wages for a given year 30 oty_total_annual_wages_pct_chg Over-the-year percent change in total annual wages for a given year (Rounded to the tenths place) 31 oty_taxable_annual_wages_chg Over-the-year change in taxable annual wages for a given year 32 oty_taxable_annual_wages_pct_chg Over-the-year percent change in taxable annual wages for a given year (Rounded to the tenths place) 33 oty_annual_contributions_chg Over-the-year change in annual contributions for a given year 34 oty_annual_contributions_pct_chg Over-the-year percent change in annual contributions for a given year (Rounded to the tenths place) 35 oty_annual_avg_wkly_wage_chg Over-the-year change in annual average weekly wage for a given year 36 oty_annual_avg_wkly_wage_pct_chg Over-the-year percent change in annual average weekly wage for a given year (Rounded to the tenths place) 38 oty_avg_annual_pay_chg Over-the-year change in average annual pay for a given year 38 oty_avg_annual_pay_pct_chg Over-the-year percent change in average annual pay for a given year (Rounded to the tenths place) NAICS Sectors 11 Agriculture, Forestry, Fishing, and Hunting 21 Mining 22 Utilities 23 Construction 31-33 Manufacturing 42 Wholesale Trade 44-45 Retail Trade 48-49 Transportation and Warehousing 51 Information 52 Finance and Insurance 53 Real Estate and Rental and Leasing 54 Professional, Scientific and Technical Services 55 Management of Companies and Enterprises 56 Administrative and Waste Services 61 Educational Services 62 Health Care and Social Assistance 71 Arts, Entertainment, and recreation 72 Accommodation and Food Services 81 Other Services (Except Public Administration) 92 Public Administration 99 Unclassified Location Quotients .. goto top Pre-computed location quotients are included in the downloadable files. Location quotients (LQ) are ratios (indicators) that measure the concentration of an industry within a specific area (metro in this case) to the concentration of that industry nationwide. If an employment LQ is equal to 1, then the industry has the same share of its area employment as it does in the nation. An employment LQ greater than 1 indicates an industry with a greater share of the local area employment than is the case nationwide. For example, Las Vegas will have an LQ greater than 1 in the Leisure and Hospitality industry because this industry makes up a larger share of the Las Vegas employment total than it does for the nation as a whole. Employment LQs are calculated by first, dividing local industry employment by the all industry total of local employment. Second, national industry employment is divided by the all industry total for the nation. Finally, the local ratio is divided by the national ratio. LQs are provided in the downloadable file for: a) the reference quarter for each of establishments, employment and wages, and b) over-the-year change for each of establishments, employment and wages. Limitations of these Data .. goto top As released by BLS QCEW: • data are establishment-based • data suppression occurs for many county/MAICS combinations • data are not available for sub-county geography • data are not organized for time-series analysis • some data cannot be classified by county are included in a state multi-county code (999) ProximityOne User Group .. goto top Join the ProximityOne User Group to keep up-to-date with new developments relating to metros and component geography decision-making information resources. Receive updates and access to tools and resources available only to members. Use this form to join the User Group. Support Using these Resources .. goto top Learn more about accessing and using demographic-economic data and related analytical tools. Join us in a Data Analytics Lab session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants. Additional Information .. goto top ProximityOne develops geodemographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our tools (software, data, methodologies) to analyze their own data integrated with other data. Contact us (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest. |
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