论文信息 - Using Static Recreation Demand Models to Forecast Angler Responses to Interseasonal Changes in Catch Rates

Using Static Recreation Demand Models to Forecast Angler Responses to Interseasonal Changes in Catch Rates

This paper examines the out-of-sample forecasting performance of several random utility models of recreation behavior. The application is salmon fishing on Lake Michigan in 1996 and 1997, with the quality of fishing (as measured by catch rates) better in 1997 than in 1996. The models examined are a standard logit model, two random parameters logit (RPL) models, and a finite mixture logit (FML) model. Results indicate that the RPL and FML models forecast equally well, and by one measure the logit model outperforms them both. Results are also consistent with the hypothesis that angler behavior is dynamic.

B. Provencher | R. Bishop

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