Larger study areas tend to reflect larger impacts, because larger geographies typically capture more production as 'local' and are subject to less in-commuting. However, analysts are occasionally surprised to find that the economy of a smaller subset region, such as a county, reflects a greater Indirect and Induced impact than that of the larger aggregate region (i.e., the state). Although not exhaustive, this article does highlight the most common reasons for such an occurrence. One easy way to avoid these issues, if you are using IMPLAN Pro, is to use the MRIO methodology.
Why does this occur? How can a smaller region have greater Indirect and Induced Effects than it has when you include surrounding geographies?
Typically larger Indirect and Induced impacts in a smaller subset region are the result of areas of high production surrounded by more rural regions. This creates a situation where we see only a small bump in production between the smaller geography and the larger one, but a significant increase in demand. This change can be economy wide, or it could be related to a specific commodity as a result of regional specialization or clustering. In these areas, the supply relative to demand is much higher in the smaller region than in the larger region (i.e., the RPCs for what is regionally available in the smaller region exceeds that of the larger region). Therefore, the larger geography sees a much larger increase in demand for the products produced in the smaller geography but does not substantially increase the supply available to meet that demand. Wyoming is a classic example of this type of activity because there are few regions of supply and a vast state of demand.
These same principles can apply in regards to Labor Income and Value Added because the regions of greater production often pay higher wages per worker and may pay higher taxes (or be subject to additional taxes such as city taxes not collected in the rest of the county). Since Value Added = Labor Income + Other Property Type Income + Taxes on Production & Imports Net Subsidies, if either or both income and taxes are higher, or if profits are higher in the core region, "upside down" effects, where the results are higher in the smaller region (county) than in the larger region (state), may be generated.
When using Employment to estimate the impact of an Industry an additional caveat arises because a difference in Output per Worker can generate significantly variant Output estimates. If the Output estimate in the smaller region is substantially larger the Output estimate in the larger region, this can result in Indirect impacts in smaller subset regions being larger than in the aggregate regions. Production areas with a greater Output per Worker than the larger surrounding area may reflect a larger impact than the aggregated region as a whole.
Typically, when impacting a larger study region, the results will follow the “normal” pattern of the Indirect and Induced producing large impacts. However it is still advisable to match the Event values in the larger region to those of the county, as this results in a consistent estimate of the Direct Effects.
This same technique also works for adjusting these smaller regions that produce higher impacts than their larger aggregate. Modify the Event in the larger region to match the Event in the smaller region (e.g., same output-per-worker, same labor income per worker) will typically resolve this issue.
However, if sufficient data is availalbe, IMPLAN recommends MRIO (Multi Regional Input Output) rather than direct comparisons of the aggregate state file to a county subset. Before IMPLAN had MRIO capability, analysts were forced to:
- Choose the small region where the actual direct impact occurs but lose much of the indirect and induced impact to leakage.
- Choose a larger region to capture those leaked impacts, but now the impact location is less precisely defined.
This is no longer necessary with the ability to use MRIO. Now the smaller region can be chosen for the Direct impact while still affording analyst the ability to see the impact on the neighboring regions (and those regions' feedback effects back on the smaller region). MRIO also allows for each region to keep it's unique identity and for you to be able to see how the impacts in the core sub-region and the larger aggregate region occur.