Estimation of Commercial Fishing Trip Costs Using Sea Sampling Data Public Deposited

http://ir.library.oregonstate.edu/concern/conference_proceedings_or_journals/ng451n608

Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, held July 11-15, 2016 at Aberdeen Exhibition and Conference Center (AECC), Aberdeen, Scotland, UK.

Suggested Bibliographic Reference: Challenging New Frontiers in the Global Seafood Sector: Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, July 11-15, 2016. Compiled by Stefani J. Evers and Ann L. Shriver. International Institute of Fisheries Economics and Trade (IIFET), Corvallis, 2016.

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  • Accurate cost estimation is crucial in fisheries economic analyses, but is often the least known component of many studies. For the past two decades, a systematic approach to collecting fishing cost data has been employed by the Northeast Fisheries Science Center through the sea sampling program, i.e., onboard observers collecting economic information in addition to bycatch information. However, the selection of trips to be observed is driven by biological concerns rather than cost assessment. The primary driver is the Standardized Bycatch Reporting Methodology which dictates what types of vessels (gear, species, area of operation, etc.) participating in various fisheries should be sampled and at what rate. There are other factors (weather and the condition of the vessel) that may introduce biases in terms of choice of vessels observed within a given time frame. This is compounded by the fact that both the optimal stratification and sampling rates for estimating bycatch discards are different from those for estimating vessel trip costs. We investigate the effects of sampling bias on trip cost model estimations through the estimation of weighted and unweighted least squares models, as well as Heckman Sample Selection Models, using a data set including both the subsample of fishing trips observed in the sea sampling program and unobserved trips. Results indicate that sampling bias is an issue that cannot be ignored, given that the uncorrected estimates have the potential to lead to erroneous conclusions, which in turn may negatively affect management decisions and regulatory outcomes.
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  • 0976343290

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