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Peers and Alcohol: Evidence from Russia

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Author Info

  • Evgeny Yakovlev

    ()
    (New Economic School and CEFIR)

Abstract

For the last twenty years Russia has confronted the Mortality Crisis- the life expectancy of Russian males has fallen by more than five years, and the mortality rate has increased by 50%. Alcohol abuse is widely agreed to be the main cause of this change. In this paper, I use a rich dataset on individual alcohol consumption to analyze the determinants for heavy drinking in Russia, such as the price of alcohol, peer effects and habits. I exploit unique location identifiers in my data and patterns of geographical settlement in Russia to measure peers within narrowly-defined neighborhoods. The definition of peers is validated by documenting a strong increase of alcohol consumption around the birthday of peers. With natural experiments I estimate the own price elasticity of the probability of heavy drinking. This price elasticity is identified using variation in alcohol regulations across Russian regions and over time. From these data, I develop a dynamic model of heavy drinking to quantify how changes in the price of alcohol would affect the proportion of heavy drinkers among Russian males and subsequently also affect mortality rates. I find that that higher alcohol prices reduce the probability of being a heavy drinker by a non-trivial amount. An increase in the price of vodka by 50% would save the lives of at least 40,000 males annually. Peers account for a quarter of this effect.

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Bibliographic Info

Paper provided by Center for Economic and Financial Research (CEFIR) in its series Working Papers with number w0182.

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Length: 45 pages
Date of creation: Sep 2012
Date of revision:
Handle: RePEc:cfr:cefirw:w0182

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  1. Brian Krauth, 2005. "Peer effects and selection effects on smoking among Canadian youth," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 735-757, August.
  2. Alexandre Mas & Enrico Moretti, 2009. "Peers at Work," American Economic Review, American Economic Association, vol. 99(1), pages 112-45, March.
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  7. Ariel Pakes & Michael Ostrovsky & Steven Berry, 2007. "Simple estimators for the parameters of discrete dynamic games (with entry/exit examples)," RAND Journal of Economics, RAND Corporation, vol. 38(2), pages 373-399, 06.
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  9. Christopher Auld & Paul Grootendorst, 2001. "An Empirical Analysis of Milk Addiction," Working Papers 2001-17, Department of Economics, University of Calgary, revised 05 Dec 2001.
  10. Jay Bhattacharya & Christina Gathmann & Grant Miller, 2013. "The Gorbachev Anti-alcohol Campaign and Russia's Mortality Crisis," American Economic Journal: Applied Economics, American Economic Association, vol. 5(2), pages 232-60, April.
  11. Hanming Fang & Yang Wang, 2010. "Estimating Dynamic Discrete Choice Models with Hyperbolic Discounting, with an Application to Mammography Decisions," PIER Working Paper Archive 10-033, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
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  15. Andrienko Yury & Nemtsov Aleksandr, 2005. "Estimation of individual demand for alcohol," EERC Working Paper Series 05-10e, EERC Research Network, Russia and CIS.
  16. Irina Slinko & Ekaterina Zhuravskaya & Evgeny Yakovlev, 2005. "Laws for Sale: Evidence from Russia," American Law and Economics Review, Oxford University Press, vol. 7(1), pages 284-318.
  17. Frank J. Chaloupka, 1991. "Rational Addictive Behavior and Cigarette Smoking," NBER Working Papers 3268, National Bureau of Economic Research, Inc.
  18. Yuri Andrienko & Sergei Guriev, 2004. "Determinants of interregional mobility in Russia," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 12(1), pages 1-27, 03.
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  20. Jane Cooley, 2010. "classroom peer effects," The New Palgrave Dictionary of Economics, Palgrave Macmillan.
  21. Michael Kremer & Dan Levy, 2008. "Peer Effects and Alcohol Use among College Students," Journal of Economic Perspectives, American Economic Association, vol. 22(3), pages 189-206, Summer.
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Cited by:
  1. Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2014. "Estimation of Treatment Effects from Combined Data: Identification versus Data Security," NBER Chapters, in: Economics of Digitization National Bureau of Economic Research, Inc.

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