transfers and not counting them was typically a difference of several hundred jobs in the trade and
service sectors on a service and trade employment base for the region of approximately 25
thousand jobs. The percent error of not including unemployment transfers would be to overstate
the employment loss in trade and services by about 1 percent.
Comparison to Results with An IO Model
For moderate (50 percent reduction) reduction in federal log supply, the IO results are
much more pessimistic than the CGE results. The magnitude of induced and indirect effects in the
IO model was often on the order of 2 to 3 times as great as equivalent induced and indirect effects
in the CGE model. For the more severe scenarios (reductions of 80 percent or greater) the
logging and wood products impacts began to approach the IO results but the indirect and induced
effects of the IO model were still on the order of twice those of the GGE model. Most of the
difference can be attributed fixed response nature of the IO model relative to flexible price
response nature of the CGE model. It is important to keep in mind the very different assumptions
that each model makes in the treatment of capital. In the IO framework both capital and labor are
assumed perfectly mobile. In the CGE model for this study, capital was assumed fixed by sector
and only labor was allowed to adjust across sectors or out of the region. If capital had been
assumed to be more mobile out of the region the CGE results would have been more like the IO
results or even more pessimistic. The framework for this study was the intermediate run. The
results of this study indicate that economic impacts estimated from an IO model should be
interpreted with great caution involving reductions in timber from the federal forest.
National Price Effects
When log shocks were assumed to be West-wide and therefore to translate into national
price effects for logs and wood products, much of the damage to regional economy in the
17
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