Catch more to catch less: Estimation of fishing timing choice as bycatch avoidance behavior in the Bering Sea Pollock fishery
This study develops a dynamic model of the harvesters’ choice of when to use individual fishing quota (IFQ), considering time-varying rates of potentially limiting bycatch, and a time-varying outside opportunity. The temporal allocation of IFQ over a season by harvesters has not been well-studied em...
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Format: | Conference Object |
Language: | English unknown |
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International Institute of Fisheries Economics & Trade
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Online Access: | https://ir.library.oregonstate.edu/concern/conference_proceedings_or_journals/4t64gt64w |
Summary: | This study develops a dynamic model of the harvesters’ choice of when to use individual fishing quota (IFQ), considering time-varying rates of potentially limiting bycatch, and a time-varying outside opportunity. The temporal allocation of IFQ over a season by harvesters has not been well-studied empirically due to complexity of the dynamic problem. In this paper, we focus on participation and target species as the harvester’s margin, which is flexibly chosen under IFQ management. To explore the incentive, we theoretically model harvesters’ seasonal profit maximizing behavior under constraints provided by regulations in the target, bycatch, and alternative fisheries. The solution motivates us to incorporate the dynamic quota use in a simple discrete choice model to estimate the harvesters’ choice. To link the shadow cost of quota in our theoretical model and harvester behavior in the data, we construct a variable which is the speed of quota usage relative to the remaining season weighted by the revenue opportunity and captures the harvesters’ forward-looking decision. The application of this empirical model is implemented with the AFA Alaskan pollock catcher-processor fleet. The result indicates that the harvesters are less likely to participate in the pollock fishery when the quota usage is too fast relative to the remaining time, suggesting that the dynamic planning plays a role, and the estimates of the coefficients on bycatch rate supports the dynamic avoidance behavior of bycatch. |
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