The U.S. Bureau of Economic Analysis released its first official county gross domestic product estimates on December 12, 2019, giving businesses annual measures of local production for 2001–2018. The series covers 3,113 counties and equivalent statistical areas, with some small jurisdictions combined with adjacent counties. It replaces the December 2018 prototype with additional source data, improved methods and more industry detail. For a business comparing locations, the new figures put production alongside an existing measure with a different geography: residents’ personal income. [S1][S2]

County GDP measures the value of goods and services produced locally after subtracting goods and services used up in production. It follows the office or factory, not the worker’s home. County personal income instead follows residents, even when they work elsewhere. For business planning, the implication is straightforward: use GDP to investigate a production base and personal income to investigate residents’ incomes. Commuting can put the workplace and its employee’s income in different counties. [S1][S2]

In the December release’s estimates for 2018, inflation-adjusted GDP increased in 2,375 areas, decreased in 717 and was unchanged in 21. A small county and a large one each count once. These counts describe the spread of growth across counties and county equivalents; they do not measure the share of the population living in areas with growing output. [S1][S2]

California supplied both ends of the growth ranking among the 141 counties with more than 500,000 residents in 2018. Santa Clara County had the fastest real-GDP growth, at 10.2%, with information the leading contributor. Kern County had the largest decline in that population group, at 0.7%, led by mining, quarrying, and oil and gas extraction. Those percentages describe each county’s total real-GDP change from 2017 to 2018, not the growth rates of the named industries. The industry detail identifies what drove the contrast without implying that every local business shared it. [S1]

An analyst building a spreadsheet from the release also needs to distinguish industry levels from contributions to growth. Its real-dollar series use 2012 as the reference year, and their changing weights mean the chained-dollar components are not additive. Adding real industry GDP figures is therefore not a sound way to reconstruct the county total. Industry contributions to the county’s real-GDP growth, by contrast, are additive. Those contributions are the appropriate measure for explaining how industries combine into the overall growth rate. [S1]

BEA uses national industry price indexes to construct county real GDP. The measure does not capture geographic price differences for goods and services produced and sold locally, and a county can produce substantial output for sale elsewhere. Comparing household purchasing power requires local price and income evidence that the county GDP figure does not supply. [S1][S2]

Source documents

  1. Local Area Gross Domestic Product, 2018 | U.S. Bureau of Economic Analysis (BEA)https://www.bea.gov/news/2019/local-area-gross-domestic-product-2018
  2. First Official County GDP Stats Coming Dec. 12 | U.S. Bureau of Economic Analysis (BEA)https://www.bea.gov/news/blog/2019-11-21/first-official-county-gdp-stats-coming-dec-12