Health Shocks, Human Capital, and Labor Market Outcomes

Parro, Francisco; Pohl, Reinhard

doi:10.17848/wp18-290

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…To capture both the pecuniary and non-pecuniary aspects of good health, we evaluate lifetime inequality by comparing the variation in lifetime utility in our baseline economy and in the counterfactual economy where everyone always (unexpectedly) draws good health realization while still receives all other shocks as in the baseline. 52 Let denote the lifetime utility of an individual i in the baseline economy as:…”

Section: Health and Lifetime Inequalitymentioning

confidence: 99%

The Lifetime Costs of Bad Health

Nardi

Pashchenko²,

Porapakkarm

2017

SSRN Journal

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Health shocks are an important source of risk. People in bad health work less, earn less, face higher medical expenses, die earlier, and accumulate much less wealth compared to those in good health. Importantly, the dynamics of health are much richer than those implied by a low-order Markov process. We first show that these dynamics can be parsimoniously captured by a combination of some lag-dependence and ex-ante heterogeneity, or health types. We then study the effects of health shocks in a structural life-cycle model with incomplete markets. Our estimated model reproduces the observed inequality in economic outcomes by health status, including the income-health and wealth-health gradients. Our model has several implications concerning the pecuniary and non-pecuniary effects of health shocks over the life-cycle. The (monetary) lifetime costs of bad health are very concentrated and highly unequally distributed across health types, with the largest component of these costs being the loss in labor earnings. The non-pecuniary effects of health are very important along two dimensions. First, individuals value good health mostly because it extends life expectancy. Second, health uncertainty substantially increases lifetime inequality by affecting the variation in lifespans.

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Section: Health and Lifetime Inequalitymentioning

confidence: 99%

The Lifetime Costs of Bad Health

Nardi

Pashchenko²,

Porapakkarm

2017

SSRN Journal

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“…, 2021; Özdoğan Özbal, 2021; Ranjan, 2020; Burgess, 2016; Adedeji and Campbell, 2013), in the growth literature some are regarding health as another fundamental element of human capital (Hatak and Zhou, 2021; Thinagar et al. , 2021; Zhao and Du, 2021; Currie, 2020; Parro and Pohl, 2018; Churchill et al. , 2015; Barro, 2013; Bloom et al.…”

Section: Introductionmentioning

confidence: 99%

“…Gruzina et al, 2021;Nathaniel, 2021;Tahir et al, 2020;Cuevas Ahumada and Calder on Villarreal, 2019;Pelinescu, 2015). Although the concept of human capital is limited to education (Adejumo et al, 2021;€ Ozdo gan € Ozbal, 2021;Ranjan, 2020;Burgess, 2016;Adedeji and Campbell, 2013), in the growth literature some are regarding health as another fundamental element of human capital (Hatak and Zhou, 2021;Thinagar et al, 2021;Zhao and Du, 2021;Currie, 2020;Parro and Pohl, 2018;Churchill et al, 2015;Barro, 2013;Bloom et al, 2001;Mushkin, 1962;Schultz, 1961). Researchers continued to study with the idea that a well-educated and healthy workforce could be a more productive factor in the economic growth process.…”

Section: Introductionmentioning

confidence: 99%

Health expenditures (total, public and private) and per capita income in the BRICS+T: panel bootstrap causality analysis

Canbay

Kırca

2022

JEFAS

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Purpose The study aims to determine whether there is a bidirectional causality relationship between health expenditures and per capita income in Brazil, Russia, India, China, South Africa and Turkey (BRICS+T). Design/methodology/approach For that purpose, the 2000–2018 period data of the variables were tested with the Kónya (2006) panel causality test. Additionally, the causality relationships between public and private health expenditures and per capita income were also investigated in the study. Findings According to the analysis results, there is no statistically significant causality relationship from total health expenditures and public health expenditures to per capita income in the relevant countries. Besides, there is a unidirectional causality relationship from private health expenditures to per capita income only in Turkey. On the other hand, a unidirectional causality relationship from per capita income to total health expenditures in China, Russia, Turkey and South Africa and from per capita income to public health expenditures in India, Russia, Turkey and South Africa were determined. Consequently, a causality relationship from per capita income to private health expenditures was found out in Russia and Turkey. Originality/value The variables are tested for the first time for BRICS+T countries, vis-à-vis the period under consideration and the method used.

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“…Finally, we contribute to the literature on the nexus among health, education, and economic outcomes. For example, Lundborg, Nilsson, and Vikström (2015) and Parro and Pohl (2018) show that the labor market effects of health shocks differ by education in Sweden and Chile. Heinesen and Kolodziejczyk (2013) find larger negative employment effects among less educated breast and colorectal cancer patients in Denmark.…”

Section: Introductionmentioning

confidence: 99%

Medical innovation, education, and labor market outcomes of cancer patients

Jeon

Pohl

2019

Journal of Health Economics

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Innovations in cancer treatment have lowered mortality, but little is known about their economic benefits. We assess the effect of two decades of improvements in cancer treatment options on the labor market outcomes of breast and prostate cancer patients. In addition, we compare this effect across cancer patients with different levels of educational attainment. We estimate the effect of medical innovation on cancer patients' labor market outcomes employing tax return and cancer registry data from Canada and measuring medical innovation by using the number of approved drugs and a quality-adjusted patent index. While cancer patients are less likely to work after their diagnosis, we find that the innovations in cancer treatment during the 1990s and 2000s reduced the negative employment effects of cancer by 63-70 percent. These benefits of medical innovation are limited to cancer patients with postsecondary education, raising concerns about unequal access to improved treatment options.

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Health Shocks, Human Capital, and Labor Market Outcomes

Cited by 4 publications

References 20 publications

The Lifetime Costs of Bad Health

The Lifetime Costs of Bad Health

Health expenditures (total, public and private) and per capita income in the BRICS+T: panel bootstrap causality analysis

Medical innovation, education, and labor market outcomes of cancer patients

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