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Rational Addiction, Peer Externalities and Long Run Effects of Public Policy

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  • Donald S. Kenkel
  • Robert R. Reed III
  • Ping Wang

Abstract

The main purpose of this research is to understand the patterns of consumption of addictive goods, their economic and welfare consequences for society and the long-run effect of tax policy in a dynamic general equilibrium model of rational addiction. In contrast to prior research, we allow individuals to make their consumption decisions simultaneous with savings and labor supply. When addictive goods have a stronger habit formation effect (an addiction effect'), individuals choose to save less due to the anticipated adverse health consequences of addiction (a detrimental health effect'). This is particularly important since total savings pins down future productivity in the economy. We also consider the role of peer influence in the choice of addiction and find that more peer pressure' raises addictive consumption, lowers savings and reduces productivity. In light of the various distortions associated with addiction, we conclude by studying the long-run effects of an excise tax on addictive goods. Our calibration exercises suggest that incorporating capital formation and peer effects in a model of rational addiction are crucial for the design of public policy. In particular, accounting for peer externalities increases the optimal sin tax rate by more than 50 percent.

Suggested Citation

  • Donald S. Kenkel & Robert R. Reed III & Ping Wang, 2002. "Rational Addiction, Peer Externalities and Long Run Effects of Public Policy," NBER Working Papers 9249, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:9249
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    Cited by:

    1. Krauth, Brian V., 2007. "Peer and Selection Effects on Youth Smoking in California," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 288-298, July.
    2. Brian V. Krauth, 2005. "Peer effects and selection effects on smoking among Canadian youth," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 38(3), pages 735-757, August.
    3. Pierre Pestieau & Gregory Ponthiere, 2012. "Myopia, regrets, and risky behaviors," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(2), pages 288-317, April.
    4. Shooshan Danagoulian, 2018. "Taking the hassle out of wellness: Do peers and health matter?," International Journal of Health Economics and Management, Springer, vol. 18(1), pages 1-23, March.
    5. Sarah Brown & Mark N Harris & Preety Srivastava, 2013. "Modelling Illegal Drug Participation in Australia," Bankwest Curtin Economics Centre Working Paper series WP1303, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
    6. William Greene & Mark N. Harris & Preety Srivastava & Xueyan Zhao, 2018. "Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumption," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 372-389, February.
    7. William H Greene & Mark N Harris & Preety Srivastava & Xueyan Zhao, 2013. "Econometric Modelling of Social Bads," Bankwest Curtin Economics Centre Working Paper series WP1305, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.

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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
    • H20 - Public Economics - - Taxation, Subsidies, and Revenue - - - General

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