The purpose of this paper is to clarify the differences between three commonly confused terms and methods in the more general realm of input-output analysis: economic impact analysis, economic contribution analysis, and export base analysis. While each of the three types of analyses has a distinct purpose and method, they all rely on data from an input-output (I-O) model, which itself is a bit of a misnomer. When first popularized by Wassily Leontief, I-O tables focused on the purchasing behavior (input) and production (output) of industries only. Later, the purchasing, producing, saving, and investing behavior of institutions such as governments and households was also added to the I-O tables, forming what is now known as a Social Accounting Matrix (SAM) and spurring a corresponding name change from I-O models to SAM models.
Please note that in the discussion that follows, we’ll be using Output as the measure of interest, though the same principles apply to Employment and any of the individual components of Output.
Economic Impact Analysis
In a typical final demand change (i.e., “impact”) analysis, the analyst is modeling a new firm or a change in the level of Output of a given firm. In such cases, the Direct Effect is the new firm’s total Output or the existing firm’s change in Output. In such cases, it is likely (and logical) that the Industry in which that firm belongs will experience total impacts that exceed the direct impacts – that is, the Industry will experience indirect and induced effects that stem from the direct effects.
Consider the example of wood window and door manufacturing in Washington County, MN. This industry already exists in the county, with Anderson Windows being one of the existing firms in this industry in Washington County. Now suppose a new wood windows and doors manufacturer, Wonder Windows, is planning to locate in Washington County with expected Output of $5 million dollars. This new plant would create new demand for some local businesses (the purchase of dimension lumber and preserved wood products, for example), which may spur some of these local businesses to undertake building improvements or expansions, thereby necessitating new windows, thereby creating indirect demand for the wood windows and doors sector. Additionally, most firms make purchases from other firms in their own industry (for example, consulting services, equipment rental), which generates additional indirect demand for that same Industry. In addition to these indirect effects, the new Wonder Windows plant would also attract some new workers to the region, spurring home improvements to some existing homes and apartments, thereby generating induced demand for the wood windows and doors industry. Such “feedback” effects to the industry are part of that industry’s overall impact in the region.
Description and Discussion
However, there are occasions when an analyst would like to see the indirect and induced effects that the current level of Output of an existing industry as a whole has on other industries in that region. In this case, the goal is to generate a total Output effect on the primary industry of interest that is equal to the current level of production of that industry, while showing the indirect and induced effects that this current level of Output has on other industries in the region. In other words, the only “effects” that the industry of interest should experience are the direct effects (e.g., current Output), while other industries in the region experience indirect and induced effects associated with (i.e., in support of) the direct effects in the industry under study. In such a study, it does not make sense to allow feedback effects on the primary industry of interest, since an existing Industry cannot experience a total Output “effect” that exceeds its current level of Output.
As another example, consider the shutting down of an industry. If the current level of industry Output were to be modeled as a negative direct effect using the traditional impact analysis approach, the model would show a total loss to this industry that is greater than its current level of Output – but it’s not possible to lose more Output (or Employment) than currently exists!
Therefore, special modeling techniques are required in these cases to ensure that the results accurately reflect the addition/loss of just the projected/current level of Output of the industry of interest plus the indirect and induced effects in other industries. This is the purpose of what we at IMPLAN term Contribution Analysis. The basic idea is to disallow indirect or induced purchases from the industry of interest in such a way that does not affect the indirect and induced effects on other industries.
If the industry of interest produces just one type of commodity (e.g., wood windows and doors), this is accomplished by setting the Regional Purchase Coefficient (RPC) for that commodity to zero. If, on the other hand, the industry of interest produces additional commodities as by-products of the production of its primary commodity (e.g., cut stock, re-sawn and planed lumber), it is necessary to either a) modify the model to assume that the industry only produces its primary product or b) set the RPC for each of the industry’s by-products to zero. This method can be used for both single- and multi-industry Contribution Analyses, and instructions to do so in IMPLAN can be found on our website, currently at http://support.implan.com/index.php?option=com_content&view=article&id=366. This is a similar approach to that described in Miller and Blair (2009, pp. 624-625 and Appendix 13.2), although they zero out local purchases from the primary industry directly in the A matrix, whereas in IMPLAN we zero them out indirectly by way of multiplying them by an RPC of zero.
When performing a Contribution Analysis on a single industry, an alternative approach is available which involves starting the analysis with a direct Output effect reduced by a factor of that industry’s detailed multiplier on itself, accomplished by dividing the industry’s current Output by its’ detailed output multiplier on that same industry. When this approach is used, there are indirect and induced Output impacts on the original industry that, when summed with the appropriately reduced direct Output, reproduce the original (i.e., current) level of Output in that industry, and thereby also generate the appropriate indirect and induced effects in other industries, equal to those generated by the RPC method above. The only difference between the results is that with this method, the “indirect” and “induced” effects on the primary industry must be reclassified as “direct” effects. A limitation of this approach is that it can only be used when analyzing a single industry, but an advantage of this approach is that that industry is allowed to produce more than one commodity (i.e., no need to reduce the number of by-products to just the one primary commodity). This approach is described in Miller and Blair (2009, p. 625). Instructions for performing this type of analysis in IMPLAN can be found on the IMPLAN website, currently at http://support.implan.com/index.php?option=com_content&view=article&id=211.
A criticism of the multi-industry Contribution Analysis methodology is that, if you were to perform the analysis for all industries simultaneously, the only “impacts” would be the direct impacts (i.e., the gross outputs of every industry), with no indirect or induced impacts. In other words, there would be no new information gained from such an exercise. We agree that there indeed is no point to such an exercise; but that does not invalidate the approach nor negate its usefulness when used to examine any number of sectors less than all possible sectors.
Export Base Analysis
Economic contribution analysis is not, as stated in Watson et al (2015), “generally regarded as referring to the ex post effects on economic activity in a region from the exogenous sales of a given sector in a previous time period”. Such a definition (and accompanying methodology) assumes that exports (i.e., exogenous sales) are the most important contribution an industry can make, disregarding other economic contributions such as import substitution, competitive advantage, and industrial diversity (Malizia and Ke, 1993). We feel that the methodology outlined in Watson et al (2015) would be better termed export base analysis and that, because it represents just one aspect of an industry’s total economic contribution, it should not be generalized as the overall contribution of the industry. In export base analysis, the goal is not to determine what would happen were a sector to disappear from the local economy, but rather to determine the output (ore employment, etc.) required by all local industries in support of that region’s exports (both foreign and domestic). However, the methodology for export base analysis outlined in Watson et al (2015) requires the internalization of all institutions except exports, which is never recommended at the sub-national level.
Malizia, E.E. and S. Ke. 1993. The Influence of Economic Diversity on Unemployment and Stability. Journal of Regional Science, 33(2): 221-35.
Miller, R.E. and P.D. Blair. 2009. Input-Output Analysis: Foundations and Extensions, Second Edition. New York: Cambridge University Press.
Watson, P., S. Cooke, D. Kay, and G. Alward. 2015. A Method for Improving Economic Contribution Studies for Regional Analysis. Journal of Regional Policy and Analysis, 45(1): 1-15.
 The RPC represents the proportion of local demand for a commodity is met by local producers of that commodity.