Emsi provides historical GRP data down to the ZIP level. GRP, or gross regional product, is simply the GDP (gross domestic product) measure applied to a smaller region.
Wikipedia defines GDP as “a monetary measure of the market value of all the final goods and services produced in a period of time, often annually or quarterly.” There are two widely recognized methods of determining GDP. The first is expenditure-based, and defines GDP as the sum of all final goods and services purchased in an economy. The income approach sums earnings, taxes, and profits, and subtracts subsidies. Emsi uses the income approach to calculate GDP/GRP.
GRP, or Gross Regional Product, is simply GDP calculated for a smaller region. All the same components—earnings, taxes, profits, and subsidies—must be calculated at the regional level. The remainder of this document outlines how Emsi calculates GRP, which is the regional sum of earnings, taxes, and profits, less subsidies.
Emsi’s sources for final GRP data include the following:
Emsi does not use BEA’s GMP (metro-level GDP) or GCP (county-level GDP) datasets. GMP does not agree with GSP, so we favor GSP; however, Emsi’s final results are similar to both GSP and GMP. Emsi evaluated GCP for possible inclusion in our calculation of GRP, but decided against it due to a lack of available component detail, as well as negative client feedback regarding potentially questionable source data. For more information, see Emsi’s review of BEA GCP.
Emsi’s national input-output model breaks national GDP out into its components—earnings, taxes, profits, and subsidies all by 6-digit NAICS. Each component must then be modeled down to the regional level.
Model to State Level
The usual method of creating state-level estimates for taxes, profits, and subsidies (3 of the 4 components of GRP) is to apply national coefficients to state earnings (the fourth component), creating state estimates for the first three components. The BEA also publishes state-level component totals for each state, so Emsi uses those totals to control the state values created by applying national coefficients to state earnings. The result is more accurate state-level data that utilizes Emsi’s state-level earnings data as well as the BEA’s state-level component totals.
If the BEA has not yet reported GSP data for the working year, the latest available GSP data is scaled to match totals taken from BEA National Income and Product Account (NIPA) tables, which are updated quarterly.
Model to County Level
The final step is to move to county-level GRP data. Emsi data provides county-level earnings figures (one component of GRP), and we must calculate the other three components. They are calculated individually by creating ratios at the state level using earnings data. For instance, county-level taxes are calculated by finding the ratio of state-level taxes to state-level earnings. That ratio is then applied to county-level earnings and solves to county-level taxes. The process is repeated for each component for each 6-digit industry. The result is each of the GRP components at the county level.
Historical GRP figures are calculated by using the above process, but with historical I-O models, historical industry earnings, and historical BEA GSP data.
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