OVERVIEW
Other Property Income (OPI) is a component of Value Added (VA) that represents gross operating surplus less proprietor’s income. OPI includes consumption of fixed capital (CFC), corporate profits, and net business current transfer payments. It includes income derived from dividends, royalties, corporate profits, and interest income. In the case of government payroll industries, it represents capital consumption allowance (i.e., depreciation).
Negative OPI in general means that the Industry spent more than it brought in as revenues (i.e., ran a deficit) that year.
OPI provides a source of income for households, business, and governments. However, I-O models by default treat OPI as a leakage, meaning that any OPI generated as part of an analysis will not generate any additional effects. This is because the assumptions that income generated from OPI will go to recipients within the region and that those recipients will spend that income in a typical manner may not be valid.
DATA SOURCES AND ESTIMATION METHODS
NATIONAL ESTIMATES OF OPI
Even at the national-level, there is no raw data source for OPI separate from Proprietor Income; rather, it is published only within the more-aggregate measure known as Gross Operating Surplus (GOS), which is the sum of OPI and PI. Nonetheless, because OPI is a component of Value Added and IMPLAN has estimates for the other components of VA, as well as for Intermediate Inputs (II) and Output, IMPLAN is able to estimate OPI by way of subtraction.
Initial estimates of national OPI by IMPLAN Industry are generated by subtracting Intermediate Inputs (II), Employee Compensation (EC), Proprietor Income, and Taxes on Production and Income (TOPI) from Output. These first estimates of national OPI by IMPLAN Industry are then controlled to BEA GDP-by-Industry data, which are at a more aggregate level of industry detail..
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.
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.
STATE AND COUNTY ESTIMATES OF OPI
To distribute the national data to the states, we turn to the BEA's GDP by State data. To calculate first estimates of county-level OPI, State-level OPI/-to-EC and OPI/Employment ratios are applied to each county's EC and Employment estimates for each IMPLAN Industry to calculate county-level first estimates of OPI by IMPLAN sector. County-level OPI estimates by IMPLAN industry sector are then forced to sum to the state- level OPI estimates.