Estimating and Distributing Value Added 2001-2018

INTRODUCTION

This is the methodology for distributing Value Added for data from 2001 - 2018. 

All IMPLAN Value Added data are ultimately controlled to National Income and Product Accounts (NIPA) data published by the Bureau of Economic Analysis (BEA).

EMPLOYEE COMPENSATION & PROPRIETOR INCOME

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

OTHER PROPERTY INCOME (OPI) AND TAXES ON PRODUCTION & IMPORTS (TOPI)

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, after projecting to the current data year.

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.

CALCULATION PROCESS

1. We start with the one-year-lagged raw Value Added data from the BEA, which provides Total GDP, EC, Gross Operating Surplus, Gross TOPI, and Subsidies. These data do not separate out PI from OPI but rather report the combination of the two, known as Gross Operating Surplus (GOS).
   
   
2. To get OPI, we subtract our own PI estimates (for which we have a separate process) for the sector and state and year (which is one year lagged, so we're using the previous year's PI value).
   
   
3. Now, since these are lagged values, we have to project them, and to do that we use the change in EC (for which we have a separate process) between the two years. We use this growth rate to project GDP, Gross TOPI, and Subsidies, then we subtract from this projected GDP value the projected TOPI and subsidies values as well as our non-lagged estimates for EC and PI (for which we have separate processes) to arrive at a "projected" OPI value.
   
   Note: The reason we use the growth rate to project GDP, Gross TOPI, and Subsidies, but not OPI itself, is that GDP and Gross TOPI are always positive numbers, which lends well to them being used with growth rates. Things that can be negative are harder to project - positive growth in EC applied to a negative OPI value would yield even more negative OPI, which is counterintuitive for a growing sector. Thus, we project the other items (GDP, Gross TOPI, Subsidies) and subtract everything else from GDP to arrive at OPI.
   
   
4. The next task is to distribute this value among the IMPLAN construction 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.

RELATED ARTICLES:

Estimating and Distributing Value Added

Estimating Non-Disclosures When Creating Employment Databases

Value Added Data

Updated April 15, 2020