Regional Purchase Coefficients


IMPLAN is a non-survey I-O model derived from a national model structural matrix. The national model represents the "average" condition for a particular Industry. Consequently, without adjustments for regional differences, the national production functions do not necessarily represent industries comprising a local or regional economy. Stevens and Trainor (1980) note that estimating regional trade flows (imports and exports) across regional boundaries is perhaps the largest source of error in deriving non-survey I-O models. Utilizing Regional Purchasing Coefficients (RPCs) is one way to eliminate some of the bias inherent in non-survey models.

Gross regional trade flows (gross exports and imports) of commodities are estimated by developing Regional Purchase Coefficients (RPCs) based on a trade model. The RPC for a given commodity represents the proportion of all local demands (industrial and institutional) for that commodity that is supplied locally (i.e., by the region to itself). For example, an RPC of 0.8 for the commodity "fish" indicates that 80% of the demand for fish (by fish processors, fish wholesalers, foreign exports, and all other demands for fish in that region) are met by local fish producers. It also indicates that 20% (1 - RPC) of the local fish demand is imported.



In IMPLAN Version 2 (2007 and earlier data sets), RPCs were estimated whenever an IMPLAN model was built. They were estimated using the coefficients from econometric equations combined with the study area data from the IMPLAN model. These equations were derived from a 51 region, 120 industry, multi-region input-output (MRIO) model developed by Jack Faucett Associates, Inc.1. This multi-regional model was based on 1977 data and represented an update of the pioneering MRIO work done by Karen Polenske2 in 1970. The econometric RPC formulations used in IMPLAN were originally developed by Ben Stevens under contract with the US Forest Service and the methodology is described in the paper by Alward and Despotakis3. For all non-shippable commodities (i.e., services), IMPLAN Pro 2 used the "observed" state values as adjusted by supply/demand pool ratios rather than econometrics. In IMPLAN Version 3 and 4, Econometric method was used for zip-code and congressional district level data (for which gravity model based trade flows data were not available). In IMPLAN Cloud, trade flow data is available for all states, counties, zip codes and congressional districts!



Starting in 1998, an effort was undertaken to create a new MRIO method that would look at trade for each individual IMPLAN sector at the county level. The double-constrained gravity model and data used are described in this paper. The resulting MRIO model data is now incorporated in IMPLAN Cloud. The gravity model is re-run for each year's IMPLAN Data. Since in IMPLAN Cloud we now have the "observed" local usage for each county/state/zip code/congressional districts in the US for each IMPLAN commodity, there is no need for the econometric equations required by IMPLAN Pro 2 as well Versions 3 and 4 in the case of zip-code and congressional district level models. Therefore in IMPLAN Cloud you can now perform MRIO analysis at the state, county, zip code, congressional district and MSA levels of geography, whereas IMPLAN Pro Version 3 was limited to performing MRIO analysis only at the state and county levels. 

A few notes on errors in estimation:

    1. A particular commodity or service classification may contain a number of different grades or attributes. A quality difference, real or perceived, can determine whether or not a local consumer is able or willing to purchase a locally produced commodity or service. Aggregating different products or services into a single category aggravates this problem. Dairy goats and sheep are lumped with pig farmers into Sector 14 "Animal Production", yet neither a cheese maker nor a pork producer will view them as substitutable.
    2. Given a choice between two suppliers of a substitutable commodity, a consumer may still choose the one that is more expensive or of inferior quality for any number of cultural, administrative, or other subjective reasons. A shopper in state A may select organic milk that is imported from state B rather than a less expensive locally produced milk; simultaneously, a shopper in state B, where the organic milk is produced, may select the less expensive traditional milk made in state A. Any number of factors can affect costs and cause inefficiencies observed when haulers of an identical commodity pass each other going opposite directions on the highway (otherwise known as "cross-hauling").

Updated July 12, 2022


1Jack Faucett Associates. 1983. "The Multiregional Input-Output Account, 1977"; vols I-IV; Report submitted to the US Department of Health and Human Services, Contract #HHS-100-81-00-57, July, 1983.
2Polenske, Karen R. 1970. "A Multiregional Input-Output Model for the United States". EDA Report No. 21 (Harvard Economic Research Project). Revised December, 1970.
3Alward, Gregory S. and Kostas Despotakis. 1982. "IMPLAN Version 2.0: Data reduction Methods for Constructing Regional Economic Accounts". Paper. USDA Forest Service; Fort Collins, Colorado.

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