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Estimation of Commercial Fishing Trip Costs Using Sea Sampling Data

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  • Journal Title:
    Marine Resource Economics
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    When estimating commercial fishing costs, selection bias can impact any model derived from non-census sampling methodologies. In the northeastern United States, commercial fishing operating cost models may suffer from selection bias, as they are often estimated using data collected for biological, rather than economic, purposes. We investigate the effects of sampling bias on trip cost model estimations using weighted/unweighted least squares and Heckman sample selection models. Results suggest that (1) the propensity for a trip to carry an observer is not random with respect to costs and that (2) selection bias exists in the majority of cost models investigated. To gauge the magnitude of selection bias, we compare results of the unweighted least squares and Heckman models. The differences between models can lead to erroneous conclusions at the subfleet level and in estimating trip cost maxima. Results suggest that assessing and correcting for selection bias is necessary when using sampled fishing cost data.
  • Source:
    Marine Resource Economics, 35(4), 379-410
  • DOI:
  • ISSN:
    0738-1360 ; 2334-5985
  • Format:
    pdf
  • Publisher:
    University of Chicago Press
  • Document Type:
    Journal Article
  • Rights Information:
    Accepted Manuscript
  • Rights Statement:
    The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
  • Compliance:
    Submitted
  • Main Document Checksum:
    urn:sha-512:0987b0946b44c45b38dc71f8b9ec63e3dbf15f33e77746b458b5607fa8ec313c93fc611e9395af2365eeae00b869fe26e366f23c2413effd0d588af6ab0cec8c
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  • File Type:
    Filetype[PDF - 792.35 KB ]
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