Estimating and Distributing Value Added



This document outlines the methodology for the 2019 Data Year. All IMPLAN Value Added data are ultimately controlled to National Income and Product Accounts (NIPA) control totals published by the Bureau of Economic Analysis (BEA).



  • Employee Compensation (EC)
  • Proprietor Income (PI)
  • Other Property Income (OPI)
  • Taxes on Production and Imports, net of subsidies (TOPI)


BLS' CEW is our primary source of employment and income data; however, CEW data excludes some Sectors [1] and does not include proprietors, proprietor income, employer-paid taxes (social insurance, unemployment), or benefits such as health and private retirement. CEW data will have some non-disclosures (i.e., sectors for which wage and employment data are not revealed). To get employment estimates for these, we use the Census Bureau's County Business Pattern (CBP) employment data. Since CBP does not provide data on wages, we use state-level wage per worker ratios together with the county-level CBP employment data to get county-level wage estimates.

Finally, we turn to the BEA's REA data series to get estimates for Employee Compensation (i.e., fully loaded payroll), Proprietor Income and Employment, and the sectors missing from CEW. Due to the REA data being lagged one year and in a more aggregate sectoring scheme, the CEW data are used to project the REA data to the current data year and to distribute them to the 546 IMPLAN Industries.

Please see the article Estimating Non-Disclosures When Creating Employment Databases for detailed information on the estimation of Employee Compensation and Proprietor Income.



Initial estimates of national TOPI by IMPLAN sector are generated by applying TOPI/Output ratios from the latest BEA Benchmark I-O table to current Output estimates. Initial estimates of national OPI by IMPLAN sector are generated by subtracting Intermediate Expenditures, Employee Compensation (EC), Proprietor Income, and TOPI from Output. These first estimates of national TOPI and OPI by IMPLAN sector are then controlled to the BEA's GDP-by-industry data.


To distribute the national data to the states, we turn to the BEA's GDP by State data.  State-level OPI-to-EC and TOPI-to-Employment ratios are used with each county's EC and Employment estimates for each IMPLAN sector to calculate county-level first estimates of OPT and TOPI by IMPLAN sector. County-level OPI and TOPI estimates by IMPLAN sector are then forced to sum to the state level OPI and TOPI estimates.



We start with the raw Value Added data from the BEA, which provides Total GDP, Employee Compensation (EC), Gross Operating Surplus (GOS), Gross TOPI, and Subsidies. These data do not separate out PI from OPI but rather report the combination of the two as GOS.

To get OPI, we subtract our own PI estimates (for which we have a separate process) for the sector and state and year.

The next task is to distribute this value among the IMPLAN sectors that map to the more aggregate BEA sectors. To do this, we rely on the U.S. values, for which we have other data sources that give more sector detail, including the BEA Benchmark, which comes out every 5 years, with the new one having just come out last year and having been incorporated into the IMPLAN data for the first time in the 2018 data set.

IMPLAN Value Added data isn't directly comparable to BEA data for GDP. We do not use the Total GDP data from the BEA since it is lagged a year relative to the IMPLAN data year. However, we do use that data set for some of the components of GDP.


Written April 20, 2022

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