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The Effect of Anti-Smoking Media Campaign on Smoking Behavior: The California Experience

Author

Listed:
  • Hong Liu

    (CEMA, Central University of Finance and Economics)

  • Wei Tan

    (Department of Economics, Stony Brook University)

Abstract

This paper evaluates the effectiveness of California anti-smoking media campaign in changing smoking behavior of adults and adolescents, in the short run as well as in the long run, through individual self-reported exposure to the media message. We construct pseudo panel data using repeated cross sections, and employ instrumental variables method to address the endogeneity problem. Overall, the results suggest that the anti-smoking media campaign not only significantly reduces the prevalence of smoking among adults and adolescents, but also brings significant long term benefits in smoking reduction, by inducing more future attempts to quit among adult smokers and deterring more initiating intentions among adolescents.

Suggested Citation

  • Hong Liu & Wei Tan, 2009. "The Effect of Anti-Smoking Media Campaign on Smoking Behavior: The California Experience," Annals of Economics and Finance, Society for AEF, vol. 10(1), pages 29-47, May.
  • Handle: RePEc:cuf:journl:y:2009:v:10:i:1:p:29-47
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    References listed on IDEAS

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    1. Verbeek, Marno & Vella, Francis, 2005. "Estimating dynamic models from repeated cross-sections," Journal of Econometrics, Elsevier, vol. 127(1), pages 83-102, July.
    2. Verbeek, Marno & Nijman, Theo, 1992. "Can Cohort Data Be Treated as Genuine Panel Data?," Empirical Economics, Springer, vol. 17(1), pages 9-23.
    3. Hu, Teh-Wei & Sung, Hai-Yen & Keeler, Theodore E, 1995. "The State Antismoking Campaign and the Industry Response: The Effects of Advertising on Cigarette Consumption in California," American Economic Review, American Economic Association, vol. 85(2), pages 85-90, May.
    4. Farrelly, M.C. & Healton, C.G. & Davis, K.C. & Messeri, P. & Hersey, J.C. & Haviland, M.L., 2002. "Getting to the truth: Evaluating national tobacco countermarketing campaigns," American Journal of Public Health, American Public Health Association, vol. 92(6), pages 901-907.
    5. Hsieh, Chee-Ruey & Yen, Lee-Lan & Liu, Jin-Tan & Chyongchiou Jeng Lin, 1996. "Smoking, health knowledge, and anti-smoking campaigns: An empirical study in Taiwan," Journal of Health Economics, Elsevier, vol. 15(1), pages 87-104, February.
    6. Hamilton, James L, 1972. "The Demand for Cigarettes: Advertising, the Health Scare, and the Cigarette Advertising Ban," The Review of Economics and Statistics, MIT Press, vol. 54(4), pages 401-411, November.
    7. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    8. Girma, Sourafel, 2000. "A quasi-differencing approach to dynamic modelling from a time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 98(2), pages 365-383, October.
    9. Siegel, M. & Biener, L., 2000. "The impact of an antismoking media campaign on progression to established smoking: Results of a longitudinal youth study," American Journal of Public Health, American Public Health Association, vol. 90(3), pages 380-386.
    10. Dolores Collado, M., 1997. "Estimating dynamic models from time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 82(1), pages 37-62.
    11. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Can cohort data be treated as genuine panel data?," Other publications TiSEM d4eada8f-b91c-4fe7-a58c-7, Tilburg University, School of Economics and Management.
    12. Hu, T.-W. & Sung, H.-Y. & Keeler, T.E., 1995. "Reducing cigarette consumption in California: Tobacco taxes vs an anti- smoking media campaign," American Journal of Public Health, American Public Health Association, vol. 85(9), pages 1218-1222.
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    Cited by:

    1. Christian Bünnings, 2013. "Does New Health Information Affect Health Behavior? The Effect of Health Events on Smoking Cessation," Ruhr Economic Papers 0459, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    2. repec:zbw:rwirep:0459 is not listed on IDEAS
    3. Anna Choi & Dhaval Dave & Joseph J. Sabia, 2019. "Smoke Gets in Your Eyes: Medical Marijuana Laws and Tobacco Cigarette Use," American Journal of Health Economics, MIT Press, vol. 5(3), pages 303-333, Summer.
    4. Christian Bünnings, 2017. "Does new health information affect health behaviour? The effect of health events on smoking cessation," Applied Economics, Taylor & Francis Journals, vol. 49(10), pages 987-1000, February.
    5. Harsman Tandilittin, 2016. "What should the Government do to Stop Epidemic of Smoking among Teenagers in Indonesia?," Asian Culture and History, Canadian Center of Science and Education, vol. 8(1), pages 140-140, March.
    6. Anna Choi & Dhaval Dave & Joseph J. Sabia, 2016. "Smoke Gets in Your Eyes: Medical Marijuana Laws and Tobacco Use," NBER Working Papers 22554, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    Anti-smoking media campaign; Smoking behavior; Program evaluation;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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