Monthly Local Area Employment Situation; 2015-2016

.. this update on the monthly and over-the-year (August 2015-August 2016) change in the local area employment situation shows general improvement. Yet many areas continue to face challenges due to both oil prices, the energy situation and other factors.  This section provides access to interactive data and GIS/mapping tools that enable viewing and analysis of the monthly labor market characteristics and trends by county and metro for the U.S. See the related Web section for more detail. The civilian labor force, employment, unemployment and unemployment rate are estimated monthly with only a two month lag between the reference date and the data access date (e.g., August 2016 data are available in October 2016).

Unemployment Rate by County – August 2016
The following graphic shows the unemployment rate for each county.

— view created using CV XE GIS and associated LAES GIS Project
— click graphic for larger showing legend details.

As shown in the illustrative interactive table view below, seven of the ten MSAs having the highest August 2016 unemployment rate were in California. Use the table to examine characteristics of counties and metros in regions of interest. As apparent from the monthly patterns shown in the table, some areas are impacted by season factors, but others are not.

View Labor Market Characteristics section in the Metropolitan Area Situation & Outlook Reports, providing the same scope of data as in the table below integrated with other data. See example for the Dallas, TX MSA.

The LAES data and this section are updated monthly. The LAES data, and their their extension, are part of the ProximityOne Situation & Outlook database and information system. ProximityOne extends the LAES data in several ways including monthly update projections of the employment situation one year ahead.

Interactive Analysis
The following graphic shows an illustrative view of the interactive LAES table. Seven of the ten MSAs having the highest August 2016 unemployment rate were in California (ranked on far right column in descending order). Use the table to examine characteristics of counties and metros in regions of interest. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

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