The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch

I use longitudinal survey data from commercial fishing deckhands in the Alaskan Bering Sea to provide new insights on empirical methods commonly used to estimate compensating wage differentials and the value of statistical life (VSL). The unique setting exploits intertemporal variation in fatality r...

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Main Author: Lavetti, Kurt
Format: Text
Language:unknown
Published: Taylor & Francis 2018
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.6238979
https://tandf.figshare.com/articles/journal_contribution/The_Estimation_of_Compensating_Wage_Differentials_Lessons_from_the_Deadliest_Catch/6238979
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spelling ftdatacite:10.6084/m9.figshare.6238979 2023-05-15T15:43:47+02:00 The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch Lavetti, Kurt 2018 https://dx.doi.org/10.6084/m9.figshare.6238979 https://tandf.figshare.com/articles/journal_contribution/The_Estimation_of_Compensating_Wage_Differentials_Lessons_from_the_Deadliest_Catch/6238979 unknown Taylor & Francis https://dx.doi.org/10.1080/07350015.2018.1470000 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Medicine Genetics FOS Biological sciences Biotechnology Sociology FOS Sociology 19999 Mathematical Sciences not elsewhere classified FOS Mathematics Inorganic Chemistry FOS Chemical sciences Text article-journal Journal contribution ScholarlyArticle 2018 ftdatacite https://doi.org/10.6084/m9.figshare.6238979 https://doi.org/10.1080/07350015.2018.1470000 2021-11-05T12:55:41Z I use longitudinal survey data from commercial fishing deckhands in the Alaskan Bering Sea to provide new insights on empirical methods commonly used to estimate compensating wage differentials and the value of statistical life (VSL). The unique setting exploits intertemporal variation in fatality rates and wages within worker-vessel pairs caused by a combination of weather patterns and policy changes, allowing identification of parameters and biases that it has only been possible to speculate about in more general settings. I show that estimation strategies common in the literature produce biased estimates in this setting, and decompose the bias components due to latent worker, establishment, and job-match heterogeneity. The estimates also remove the confounding effects of endogenous job mobility and dynamic labor market search, narrowing a conceptual gap between search-based hedonic wage theory and its empirical applications. I find that workers’ marginal aversion to fatal risk falls as risk levels rise, which suggests complementarities in the benefits of public safety policies. Supplementary materials for this article are available online. Text Bering Sea DataCite Metadata Store (German National Library of Science and Technology) Bering Sea
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Medicine
Genetics
FOS Biological sciences
Biotechnology
Sociology
FOS Sociology
19999 Mathematical Sciences not elsewhere classified
FOS Mathematics
Inorganic Chemistry
FOS Chemical sciences
spellingShingle Medicine
Genetics
FOS Biological sciences
Biotechnology
Sociology
FOS Sociology
19999 Mathematical Sciences not elsewhere classified
FOS Mathematics
Inorganic Chemistry
FOS Chemical sciences
Lavetti, Kurt
The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch
topic_facet Medicine
Genetics
FOS Biological sciences
Biotechnology
Sociology
FOS Sociology
19999 Mathematical Sciences not elsewhere classified
FOS Mathematics
Inorganic Chemistry
FOS Chemical sciences
description I use longitudinal survey data from commercial fishing deckhands in the Alaskan Bering Sea to provide new insights on empirical methods commonly used to estimate compensating wage differentials and the value of statistical life (VSL). The unique setting exploits intertemporal variation in fatality rates and wages within worker-vessel pairs caused by a combination of weather patterns and policy changes, allowing identification of parameters and biases that it has only been possible to speculate about in more general settings. I show that estimation strategies common in the literature produce biased estimates in this setting, and decompose the bias components due to latent worker, establishment, and job-match heterogeneity. The estimates also remove the confounding effects of endogenous job mobility and dynamic labor market search, narrowing a conceptual gap between search-based hedonic wage theory and its empirical applications. I find that workers’ marginal aversion to fatal risk falls as risk levels rise, which suggests complementarities in the benefits of public safety policies. Supplementary materials for this article are available online.
format Text
author Lavetti, Kurt
author_facet Lavetti, Kurt
author_sort Lavetti, Kurt
title The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch
title_short The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch
title_full The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch
title_fullStr The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch
title_full_unstemmed The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch
title_sort estimation of compensating wage differentials: lessons from the deadliest catch
publisher Taylor & Francis
publishDate 2018
url https://dx.doi.org/10.6084/m9.figshare.6238979
https://tandf.figshare.com/articles/journal_contribution/The_Estimation_of_Compensating_Wage_Differentials_Lessons_from_the_Deadliest_Catch/6238979
geographic Bering Sea
geographic_facet Bering Sea
genre Bering Sea
genre_facet Bering Sea
op_relation https://dx.doi.org/10.1080/07350015.2018.1470000
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.6238979
https://doi.org/10.1080/07350015.2018.1470000
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