Optimal Inter-Temporal Management of a Renewable Resource: A Policy Analysis

Motivated by the problem of deer overabundance in many areas of the United States, this thesis investigates innovative incentive-compatible policy options to address the problem. Economists view deer populations as a renewable resource, a composite asset that provides both benefits and costs to humans over time. As with any other asset, the economic goal of deer management should be to achieve the deer population that optimizes the value of the asset over time. Specifically, the first essay investigates attitudinal differences among hunters using hunter survey data from north-central Pennsylvania. A latent-class model (LCM) with covariates is used to separate hunters by their attitudes toward deer hunting, deer damage, and their role as managers of the deer population. The results indicate that hunters can be separated into general attitudinal categories which wildlife management agencies should consider when designing harvest allocation schemes. The second essay investigates the feasibility of nonlinear pricing for deer harvest tags which is incentive compatible with hunters who vary by their willingness to pay for tags. The same hunter survey data from Pennsylvania is used in an ordered probit model to estimate hunter demand for three hunter categories. A subsequent nonlinear programming model allows a social-welfare comparison between the current licensing system and improved pricing schemes. The results indicate that welfare improvements of up to 10% are possible. The third essay investigates the specific policy option of paying hunters to harvest antlerless deer as an incentive. A bioeconomic model is developed, calibrated with Pennsylvania data, and solved as a dynamic programming problem. The results indicate that significant social welfare improvements are possible, but that the payments to hunters may exceed what is politically feasible under current conditions.