A Time Series Approach to Forecasting Angling Activity at a Recreational Site Based on Past Successes

A multiple regression model was developed for estimating or forecasting the impact of past fishing "successes" on the current angling activity or participation at a recreational site. Through this approach we demonstrate the usefulness of time series methodology as a forecasting tool by investigating the lag structure of success and measuring its elasticity. We evaluated empirical results, based on daily time series data for a Lake Superior river; these indicate that anglers respond more to past total success at the site than to past success per unit of effort at the site. Finally, we examined how the model could be extended so as to estimate the economic value of catching a fish and how, in turn, such an extended model might be part of a comprehensive approach for valuing changes in habitat using benefit-cost analysis.