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Smoking, Health Capital, and Longevity: Evaluation of Personalized Cessation Treatments in a Lifecycle Model with Heterogeneous Agents

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  • Li-Shiun Chen
  • Ping Wang
  • Yao Yao

Abstract

Cigarette smoking leads to large healthcare and morbidity costs, and mortality losses, and smoking cessation plays a key role in reducing health risk and economic costs. While medical evidence suggests that some smokers are more likely to respond to medication treatment than others depending on genetic markers, it remains unexplored whether pharmacogenetic testing is cost-effective in treating potential quitters of smoking. We address this knowledge gap by developing a lifecycle model in which individuals make smoking, health investment and consumption-savings decisions. Depending on an individual's genotype, smoking may bring enjoyment but deteriorates one's health, and the dynamic evolution of health capital determines life expectancy. In addition to heterogeneous genotypes, individuals also differ in demographics. We calibrate this model to fit key economic and medical observations in the U.S. We then propose three smoking cessation policies, two with standard treatments and one personalized depending on genetic markers, all under the same program costs. We construct two unified measures of effectiveness and subsequently compute the cost-effectiveness ratio. We find that personalized treatment is the most cost-effective: for each dollar of program cost, it generates $8.94 value in effectiveness, which is 22-45% higher than those under standard treatments.

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  • Li-Shiun Chen & Ping Wang & Yao Yao, 2017. "Smoking, Health Capital, and Longevity: Evaluation of Personalized Cessation Treatments in a Lifecycle Model with Heterogeneous Agents," NBER Working Papers 23820, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:23820
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    Cited by:

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    2. Titus Galama & Hans van Kippersluis, 2022. "Human Capital Formation: The Importance of Endogenous Longevity," Tinbergen Institute Discussion Papers 22-026/V, Tinbergen Institute.
    3. Siddhartha Sanghi, 2019. "Health Inequality: Role of Insurance and Technological Progress," 2019 Meeting Papers 703, Society for Economic Dynamics.
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    5. Ping Wang & Yin-Chi Wang, 2020. "Health and Economic Development from Cross-Country Perspectives," Review, Federal Reserve Bank of St. Louis, vol. 102(1), pages 79-98.
    6. Lutz Bellmann & Olaf Hübler, 2022. "Personality traits, working conditions and health: an empirical analysis based on the German Linked Personnel Panel, 2013–2017," Review of Managerial Science, Springer, vol. 16(2), pages 283-318, February.
    7. Makenzie Peake & Guillaume Vandenbroucke, 2020. "Worker Diversity and Wage Growth Since 1940," Review, Federal Reserve Bank of St. Louis, vol. 102(1), pages 1-18.

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    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • I10 - Health, Education, and Welfare - - Health - - - General

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