The Determinants of Fish Catch: A Quantile Regression Approach

Mary Cris F. Pleños

Problems of World Agriculture / Problemy Rolnictwa Światowego, 2021, vol. 21, issue 2

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.

Keywords: Agribusiness; Livestock Production/Industries (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/317042/files/PRS_2021_T21%2836%29_n2_s15.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:polpwa:317042

DOI: 10.22004/ag.econ.317042

Access Statistics for this article

More articles in Problems of World Agriculture / Problemy Rolnictwa Światowego from Warsaw University of Life Sciences Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().