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-- county quarterly/annual time series by type of business/industry November 2020 .. this section provides preliminary data and tools to examine initial hard data to assess pandemic economic impact at the county level. Examine data through 2020Q2 and how these measures are changing quarterly. Use the interactive table below to view, rank, query data for counties and regions of interest. Change in Employment & Wages June 2019-June 2020 -- U.S. & Largest 10 Counties The following table shows percent change in total employment and average weekly wages for the U.S. and largest 10 counties over the year June 2019 to June 2020 for "covered" employment. These preliminary numbers, released November 20, 2020, will be updated December 2, 2020, as final and include data for all counties with more detail (number of establishments and data by detailed type of business).
These data are based on the BLS quarterly census of employment and wages (QCEW) whihc provides a quarterly count of establishments, employment and wages reported by employers covering more than 95 percent of U.S. jobs. These data are summarized at the county, metro, state and national levels by type of business. Establishments, Employment, Earnings -- Interactive Table .. goto top -- U.S. by County by Sector/NAICS -- 2018Q3 Over-the-Year through 2019Q3; updates early December See related interactive tables. Usage Notes - Table contains 19 rows (industries) for each of 3,142 counties. - -1 cell values indicates data suppressed for that cell. - Click ShowAll button between queries. - Click column header to sort; click again to sort other direction. Get a county code here Columns - Area Name - State - StCty Code -- State+County FIPS code - Industry Code - Industry Name - Establishments 2018Q3 - Establishments 2018Q4 - Establishments 2019Q1 - Establishments 2019Q2 - Establishments 2019Q3 - Employment 2018Q3 - Employment 2018Q4 - Employment 2019Q1 - Employment 2019Q2 - Employment 2019Q3 - Average Weekly Wages 2018Q3 - Average Weekly Wages 2018Q4 - Average Weekly Wages 2019Q1 - Average Weekly Wages 2019Q2 - Average Weekly Wages 2019Q3 Type of Business Shown in Table
Using MultiRow Select Feature This feature is available where the grid shows a checkbox at the beginning of each row as shown in the graphic below. In this example, use the following sequence of steps: click ShowAll button, click GEOID button (selecting only LA County rows), click checkbox for rows to be multi-selected. Rows turn blue as selected. After selecting, right-click blue area and copy to clipboard. After copy to clipboard, paste into a text file or other application. The following view illustrates how to create a profile for LA County in Excel. The highlighted area was added after the paste into Excel and shows the percent establishments by high level sector. Some columns were deleted and a header row was added to obtain the view shown below. About these Data .. goto top Based on data tabulated by the U.S. Bureau of Labor Statistics, these data are derived from quarterly tax reports submitted to State Employment Security Agencies by over eight million employers subject to State unemployment insurance (UI) laws and from Federal agencies subject to the Unemployment Compensation for Federal Employees (UCFE) program. This includes 99.7% of all wage and salary civilian employment. The EEE quarterly data are based on employer reported data and provide EEE characteristics by detailed type of business collected and tabulated by the Bureau of Labor Statistics (BLS). 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. Important features of these data ... • Tabulated for all counties, metros, states and the U.S. • Tabulated for detailed types of business (6-digit NAICS). • Tabulated quarterly and annually, the data enable time-series modeling. • Employer-based administratively collected data; not estimates. • Short lag (5 months) between reporting date and date of data accessibility - data for second quarter 2020 (2020Q2) are available mid-December 2020. Use these data to examine how a detailed type of business is changing in a county or region ... or how that type of business in one county/metro compares to another county or metro. Answer questions like how much of the healthcare sector in a particular metro is comprised by offices of physicians. Or, are the number of establishments in a business sector growing or declining? How are the characteristics of establishments in one metro changing relative to another metro? Limitations of the EEE Data [goto top] Join us in a Data Analytics Lab session where we discuss these topics and how the EEE data can be improved and related/used with other data. • Extensive suppression (for purposes of confidentiality) limits usefulness of data for more detailed NAICS/types of industry. • Data are employer-based and reflect place of work rather than place of residence. • "Government establishment" coverage limited, inhibiting ability to analyze public/private sector mix. • Employment measure include full- and part-time employment. Using Downloadable Quarterly Establishments, Employment & Earnings Data by NAICS Access/download quarterly establishments, employment & earnings data by detailed NAICS category using the Situation & Outlook Metro Reports. Select a metro from the interactive table by click a link in the "Code" column. The S&O metro report opens in a new page. In the table of contents, select section 6.6. from the table of contents (Establishments, Employment & Earnings by Detailed Type of Business). See this example for the Chicago metro. 1. At the bottom of section 6.6., click a link for a quarterly download. For example, clicking 2019Q3 opens a CSV file. 2. Save this file to a folder on your computer. 3. Start a spreadsheet program and open/import this CSV file. Note that the CSV file provides attributes by detailed NAICS code for MSAs and only totals for MISAs. The file includes the items shown below. This section will be updated soon with more details about content and use.
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. Using the Downloaded CSV File -- Orientation & Location Quotients The following graphic shows a partial view of the downloaded 2016Q1 CSV file after importing into Excel. - This is the 2016Q1 Chicago metro. - Columns correspond to above list and description. - Several columns have been deleted to focus on description of locations quotients (below). - There are no text descriptors included in the file -- for example, NAICS industry name is not provided. - In the following version, industry names were manually inserted for "high level sectors" (column C). - Note that the disclosure code show N for the Information and Other Services categories. .. when N occurs, only the total number of establishments is shown. - LQs: for the Chicago metro in 2016Q1, the highest LQ (among high level sectors) for 1st month employment (column M) was 1.24 (Professional & Business Service sector). - Click graphic for larger view.  ProximityOne User Group 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 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. Follow ProximityOne on Twitter at www.twitter.com/proximityone. 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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