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

  • Alberto Abadie
  • Alexis Diamond
  • Jens Hainmueller

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.

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File URL: http://www.nber.org/papers/t0335.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0335.

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Date of creation: Jan 2007
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Handle: RePEc:nbr:nberte:0335
Note: TWP
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  1. 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.
  2. Robert J. Barro & Jong-Wha Lee, 2000. "International Data on Educational Attainment: Updates and Implications," CID Working Papers 42, Center for International Development at Harvard University.
  3. David Card, 1990. "The impact of the Mariel boatlift on the Miami labor market," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 43(2), pages 245-257, January.
  4. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
  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, 07.
  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. David Card & Alan Krueger, 1993. "Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania," Working Papers 694, Princeton University, Department of Economics, Industrial Relations Section..
  8. 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.
  9. 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.
  10. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-in-Differences Estimates?," The Quarterly Journal of Economics, MIT Press, vol. 119(1), pages 249-275, February.
  11. 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.
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