Dynamic Random Utility Modeling: A Monte Carlo Analysis
针对渔业中重复地点选择的动态优化问题，开发了动态随机效用模型，并通过蒙特卡洛分析比较其与静态模型的估计性能。
Applied studies of commercial fishing have largely ignored the intertemporal aspects of repeated site choices. For many fisheries, fishermen might choose a dynamically optimal cruise trajectory rather than myopic day‐to‐day strategies and a model that ignores these considerations will likely lead to biased parameter estimates and poor policy guidance. A dynamic random utility model is developed that utilizes the same information as static site‐choice models but is entrenched in the principles of dynamic optimization. Using Monte Carlo analysis, we evaluate the performance of this estimator as compared to the static model for a variety of simulated fishery types.