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The Determinants of Fish Catch: A Quantile Regression Approach

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  • Pleños, Mary Cris F.

Abstract

The goal of this study is to use quantile regression (QR) to find predictors of fisher's catch and compare it with OLS regression. The heterogeneous association across the different quantiles of the catch distribution was investigated using QR analysis. The findings reveal that the effect changes depending on where you are in the catch distribution. In the OLS, there are several non-significant predictors that appear to be significant in quantile regression. By OLS regression, demographic variables have little effect on fisher's catch; but, in quantile regression, marital status, fishing hours, and use of motorized boats appeared to have a relatively high impact at the top of the distribution.

Suggested Citation

  • Pleños, Mary Cris F., 2021. "The Determinants of Fish Catch: A Quantile Regression Approach," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 21(2), June.
    • Handle: RePEc:ags:polpwa:317042
    DOI: 10.22004/ag.econ.317042
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