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Economics & Social Sciences Research Program

Common Property, Information, Cooperation: Commercial Fishing in the Bering Sea

Substantial theoretical and experimental literature has focused on the conditions under which cooperative behavior among actors providing public goods or extracting common-property natural resources is likely to occur. The literature identifies the importance of coercion, small groups of actors, or the existence of social norms as being conducive to cooperation. We are investigating a natural experiment in which information on extractive activities with respect to a common property resource is relayed to all players. These players operate under an overall harvest total allowable catch (TAC), and consequently, one player’s actions can have a deleterious effect on all players.

The case we investigate is incidental catch (termed bycatch) of halibut by the Alaskan flatfish fishery, where participants voluntarily report bycatch information to an agent who then distributes data to the fleet. Consequently, fishermen know the extent to which other fishermen are avoiding bycatch, and are thereby able to observe efforts by other fishermen to avoid bycatch and to extend the fishing season for marketable fish species. Using a mixed logit model of spatial fishing behavior our results show that cooperative behavior is prevalent early in the season, but significant heterogeneity with respect to bycatch avoidance arises as bycatch TACs tighten.

By Alan Haynie


Examining Dynamic Impacts of Alaska Fisheries within Time Series Modeling Framework

Professor Sung Ahn (Washington State University) and Dr. Chang Seung (ESSR Program) are developing a vector autoregressive (VAR) time-series model to measure the time and magnitudes of the economic impacts of industries including seafood industry for Alaska. To validate the model, they have conducted out-of-sample forecasts for each of 17 aggregated industries. They have also developed procedures to generate impulse response functions (IRF) which measure the dynamic, temporal impacts of each industry.

The models employ various assumptions about the lag structure, and include exogenous variables such as landings by species. Because the Alaskan economy is dependent on the rest of the United States (RUS) economy, the models include total U.S. employment (as a proxy for Alaska’s exports to the RUS). With this exogenous variable, it was found out that the mean absolute percentage error (MAPE), which is one way of measuring the forecasting performance of the model, decreases for some sectors while the MAPE for other sectors increases slightly. Once completed, the VAR model will be able to calculate the temporal economic impacts of the seafood industry.

By Chang Seung
 

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