To measure economic impacts of natural resource management policy, we need good models that address harvesters' response to the policy change. My research is about developing models of harvester behavior, particularly focusing on the dynamic aspect of their decisions. We assume that harvesters maximize their objective functions, such as profit or utility, by choosing their decision variables. Harvesters have a wide range of margins, and the importance of each margin depends on fisheries and context. In my job market paper, I modeled harvesters’ choice on fishing trip duration using daily catch data and dynamic discrete choice model. In another project of mine, seasonal dynamics in quota use allocation in Alaskan pollock fishery is investigated.
As more seafood products are consumed all over the world, the overuse of transboundary fisheries stocks has become a serious issue. In general, such resources are under the management of regional fisheries management organizations (RFMOs), comprised by the countries harvesting the shared stock. Economic management of internationally shared fish stocks has faced difficulty due to their nature as common property at the international level and transboundary stock mobility. While many studies pay attention to supply side in shared fish stocks, consumers in different countries also “share” fish stocks through international trade. Accordingly, my research interest in this context is at the intersection of international trade and fisheries resources. In Abe et al. (2017), we show that the trade intensity of a country decreases the harvest. While this model adopts the country level capital and labor as a source of comparative advantage, I aim to develop the model by incorporating dynamic stock abundance as a source of comparative advantage.