Estimation of Production Behavior Using Pooled Microdata

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Abstract
Lumber industry production behavior is modeled using pooled microdata. Explicit recognition of the crucial role of capacity utilization at the mill level is used to generate information concerning product supply and factor demands. To exploit optimally the panel structure of the data base, fixed effects and error components models are estimated, along with the ordinary least squares model. Results for key elasticities are robust and highly significant. Furthermore, the results are more plausible than those from previous studies that rely on aggregate data and flexible functional forms.

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