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Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey
This article investigates the causal links between health and employment status. To disentangle correlation from causality effects, the authors leverage a French panel survey to estimate a bivariate dynamic probit model that can account for the persistence effect, initial conditions, and unobserved...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6734420/ https://www.ncbi.nlm.nih.gov/pubmed/30706222 http://dx.doi.org/10.1186/s13561-019-0220-3 |
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author | Delattre, Eric Moussa, Richard K. Sabatier, Mareva |
author_facet | Delattre, Eric Moussa, Richard K. Sabatier, Mareva |
author_sort | Delattre, Eric |
collection | PubMed |
description | This article investigates the causal links between health and employment status. To disentangle correlation from causality effects, the authors leverage a French panel survey to estimate a bivariate dynamic probit model that can account for the persistence effect, initial conditions, and unobserved heterogeneity. The results highlight the crucial role of all three components and reveal strong dual causality between health and employment status. The findings clearly support demands for better coordination between employment and health public policies. |
format | Online Article Text |
id | pubmed-6734420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-67344202019-09-12 Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey Delattre, Eric Moussa, Richard K. Sabatier, Mareva Health Econ Rev Research This article investigates the causal links between health and employment status. To disentangle correlation from causality effects, the authors leverage a French panel survey to estimate a bivariate dynamic probit model that can account for the persistence effect, initial conditions, and unobserved heterogeneity. The results highlight the crucial role of all three components and reveal strong dual causality between health and employment status. The findings clearly support demands for better coordination between employment and health public policies. Springer Berlin Heidelberg 2019-01-31 /pmc/articles/PMC6734420/ /pubmed/30706222 http://dx.doi.org/10.1186/s13561-019-0220-3 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Delattre, Eric Moussa, Richard K. Sabatier, Mareva Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey |
title | Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey |
title_full | Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey |
title_fullStr | Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey |
title_full_unstemmed | Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey |
title_short | Health condition and job status interactions: econometric evidence of causality from a French longitudinal survey |
title_sort | health condition and job status interactions: econometric evidence of causality from a french longitudinal survey |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6734420/ https://www.ncbi.nlm.nih.gov/pubmed/30706222 http://dx.doi.org/10.1186/s13561-019-0220-3 |
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