Modeling Trip Count Data with Excess Zeros for U.S. Saltwater Recreational Fishing

Count data, such as recreational fishing trips taken by anglers, is increasingly common in recreational fishing demand analysis. Because of the non-negative integer nature of the recreational fishing trip data, some over-dispersion problems, and truncation of the data at zero trips, count data models are more appropriate for estimating the recreational fishing demand function. This study employed count data models to analyze U.S. saltwater recreational fishing trips with excess zeros, using a cross-sectional data extracted from the 2011 National Survey of Fishing, Hunting, and Wildlife Associated Recreation. Using Akaike Information Criterion and Bayesian Information Criterion, the zero-truncated negative binomial model was selected among other count data models better fitted in this count data for this study. Empirical results of this study provide insight into the determinants of saltwater recreational fishing trips, which can be used in analyzing the social and economic values of saltwater recreational fisheries management.