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Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program

Author

Listed:
  • Alberto Abadie
  • Alexis Diamond
  • Jens Hainmueller

Abstract

Building on an idea in Abadie and Gardeazabal (2003), this article investigates the application of synthetic control methods to comparative case studies. We discuss the advantages of these methods and apply them to study the effects of Proposition 99, a large-scale tobacco control program that California implemented in 1988. We demonstrate that following Proposition 99 tobacco consumption fell markedly in California relative to a comparable synthetic control region. We estimate that by the year 2000 annual per-capita cigarette sales in California were about 26 packs lower than what they would have been in the absence of Proposition 99. Given that many policy interventions and events of interest in social sciences take place at an aggregate level (countries, regions, cities, etc.) and affect a small number of aggregate units, the potential applicability of synthetic control methods to comparative case studies is very large, especially in situations where traditional regression methods are not appropriate. The methods proposed in this article produce informative inference regardless of the number of available comparison units, the number of available time periods, and whether the data are individual (micro) or aggregate (macro). Software to compute the estimators proposed in this article is available at the authors' web-pages.

Suggested Citation

  • Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2007. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program," NBER Working Papers 12831, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:12831
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    References listed on IDEAS

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    1. Card, David & Krueger, Alan B, 1994. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania," American Economic Review, American Economic Association, vol. 84(4), pages 772-793, September.
    2. Jonathan Gruber, 2001. "Tobacco at the Crossroads: The Past and Future of Smoking Regulation in the United States," Journal of Economic Perspectives, American Economic Association, vol. 15(2), pages 193-212, Spring.
    3. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    4. Barro, Robert J & Lee, Jong-Wha, 2001. "International Data on Educational Attainment: Updates and Implications," Oxford Economic Papers, Oxford University Press, vol. 53(3), pages 541-563, July.
    5. Rajeev K. Goel & Michael A. Nelson, 2006. "The Effectiveness of Anti-Smoking Legislation: A Review," Journal of Economic Surveys, Wiley Blackwell, vol. 20(3), pages 325-355, July.
    6. Stephen G. Donald & Kevin Lang, 2007. "Inference with Difference-in-Differences and Other Panel Data," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 221-233, May.
    7. Dinan, John & Heckelman, Jac C., 2005. "The anti-tobacco movement in the Progressive Era: A case study of direct democracy in Oregon," Explorations in Economic History, Elsevier, vol. 42(4), pages 529-546, October.
    8. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, Oxford University Press, vol. 119(1), pages 249-275.
    9. Matthew C. Farrelly & William N. Evans & Edward Montgomery, 1999. "Do Workplace Smoking Bans Reduce Smoking?," American Economic Review, American Economic Association, vol. 89(4), pages 728-747, September.
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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law

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