IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2601.08352.html

Impact of Tobacco Advertising Restrictions in Switzerland: A Quasi-Experimental Study on the Effect of Billboard Bans on Smoking

Author

Listed:
  • Andreas Stoller

Abstract

This study assesses the impact of tobacco billboard bans on smoking in Switzerland, exploiting their staggered adoption across regions, i.e., the cantons. Based on retrospective smoking histories from the Swiss Health Survey, a panel of individuals' annual smoking status is reconstructed, containing more than one million observations from 1993 to 2017. Estimation relies on staggered difference-in-differences as well as a complementary latent factor model, which relaxes the common trends assumption. The findings indicate that tobacco billboard bans lead to a reduction in smoking rates. Reductions of up to 0.9 percentage points correspond to an approximate 3% decline in the smoking rate. The effect is driven by women and individuals aged 25-44 and 65+. Overall, this evidence suggests that even partial tobacco advertising bans, such as billboard bans, can effectively reduce smoking rates and serve as a valuable policy tool within comprehensive tobacco prevention strategies.

Suggested Citation

  • Andreas Stoller, 2026. "Impact of Tobacco Advertising Restrictions in Switzerland: A Quasi-Experimental Study on the Effect of Billboard Bans on Smoking," Papers 2601.08352, arXiv.org.
  • Handle: RePEc:arx:papers:2601.08352
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2601.08352
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    2. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    3. Craig A. Gallet & John A. List, 2003. "Cigarette demand: a meta‐analysis of elasticities," Health Economics, John Wiley & Sons, Ltd., vol. 12(10), pages 821-835, October.
    4. Lechner, Michael, 2011. "The Estimation of Causal Effects by Difference-in-Difference Methods," Foundations and Trends(R) in Econometrics, now publishers, vol. 4(3), pages 165-224, November.
    5. Kirill Borusyak & Xavier Jaravel & Jann Spiess, 2024. "Revisiting Event-Study Designs: Robust and Efficient Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3253-3285.
    6. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    7. Xu, Yiqing, 2017. "Generalized Synthetic Control Method: Causal Inference with Interactive Fixed Effects Models," Political Analysis, Cambridge University Press, vol. 25(1), pages 57-76, January.
    8. Philip DeCicca & Donald Kenkel & Michael F. Lovenheim, 2022. "The Economics of Tobacco Regulation: A Comprehensive Review," Journal of Economic Literature, American Economic Association, vol. 60(3), pages 883-970, September.
    9. Laurent Gobillon & Thierry Magnac, 2016. "Regional Policy Evaluation: Interactive Fixed Effects and Synthetic Controls," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 535-551, July.
    10. James J. Heckman & Fredrick Flyer & Colleen Loughlin, 2008. "An Assessment Of Causal Inference In Smoking Initiation Research And A Framework For Future Research," Economic Inquiry, Western Economic Association International, vol. 46(1), pages 37-44, January.
    11. Jon P. Nelson, 2010. "What is Learned from Longitudinal Studies of Advertising and Youth Drinking and Smoking? A Critical Assessment," IJERPH, MDPI, vol. 7(3), pages 1-57, March.
    12. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    13. 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.
    14. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    15. Saffer, Henry & Chaloupka, Frank, 2000. "The effect of tobacco advertising bans on tobacco consumption," Journal of Health Economics, Elsevier, vol. 19(6), pages 1117-1137, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martin Huber & Sarina Joy Oberhansli, 2026. "Difference-in-differences for mediation analysis using double machine learning," Papers 2602.23877, arXiv.org.
    2. Arne Henningsen & Guy Low & David Wuepper & Tobias Dalhaus & Hugo Storm & Dagim Belay & Stefan Hirsch, 2024. "Estimating Causal Effects with Observational Data: Guidelines for Agricultural and Applied Economists," IFRO Working Paper 2024/03, University of Copenhagen, Department of Food and Resource Economics.
    3. Park, Minchul, 2025. "A selection correction method for heterogeneous treatment effects in staggered adoption settings," Economics Letters, Elsevier, vol. 254(C).
    4. Clément de Chaisemartin & Xavier D’Haultfœuille, 2023. "Two-way fixed effects and differences-in-differences with heterogeneous treatment effects: a survey," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 1-30.
    5. Hans-Bernd Schaefer & Rok Spruk, 2024. "Islamic Law, Western European Law and the Roots of Middle East's Long Divergence: a Comparative Empirical Investigation (800-1600)," Papers 2401.14435, arXiv.org, revised Mar 2024.
    6. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    7. Gregory Faletto, 2023. "Fused Extended Two-Way Fixed Effects for Difference-in-Differences With Staggered Adoptions," Papers 2312.05985, arXiv.org, revised Apr 2025.
    8. Rachel Scarfe & Daniel Schaefer & Tomasz Sulka, 2023. "The Incidence of Workplace Pensions: Evidence from the UK's Automatic Enrollment Mandate," Edinburgh School of Economics Discussion Paper Series 313, Edinburgh School of Economics, University of Edinburgh.
    9. Vinish Shrestha, 2025. "Revisiting the effects of cigarette taxation on smoking outcomes," Empirical Economics, Springer, vol. 68(3), pages 1429-1475, March.
    10. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
    11. Nyborg, Kjell G. & Woschitz, Jiri, 2025. "Robust difference-in-differences analysis when there is a term structure," Journal of Financial Economics, Elsevier, vol. 170(C).
    12. Kyunghoon Ban & D'esir'e K'edagni, 2022. "Robust Difference-in-differences Models," Papers 2211.06710, arXiv.org, revised Aug 2023.
    13. Dalia Ghanem & Pedro H. C. Sant'Anna & Kaspar Wüthrich, 2022. "Selection and Parallel Trends," CESifo Working Paper Series 9910, CESifo.
    14. Brown, Nicholas L. & Butts, Kyle, 2025. "Dynamic treatment effect estimation with interactive fixed effects and short panels," Journal of Econometrics, Elsevier, vol. 250(C).
    15. Ridwan Ah Sheikh & Sunil Kanwar, 2024. "Revisiting the Impact of TRIPS on IPR-intensive Export Flows: Evidence from Staggered Difference-in-Differences," Working papers 351, Centre for Development Economics, Delhi School of Economics.
    16. Auci, Sabrina & Coromaldi, Manuela & De Fraja, Gianni, 2025. "School autonomy and pupils’ performance: Academy conversion in English primary schools," Economics of Education Review, Elsevier, vol. 107(C).
    17. Yuhao Deng & Le Kang, 2026. "Doubly Robust Estimation of Treatment Effects in Staggered Difference-in-Differences with Time-Varying Covariates," Papers 2603.04080, arXiv.org.
    18. Callaway, Brantly & Li, Tong, 2023. "Policy evaluation during a pandemic," Journal of Econometrics, Elsevier, vol. 236(1).
    19. Wang, Yimin, 2025. "Links between COVID-19 lockdowns and drug overdose deaths, evidence from panel data," Economics & Human Biology, Elsevier, vol. 58(C).
    20. Mayberry, Anthony A., 2023. "Demilitarization and economic growth: Empirical evidence in support of a peace dividend," Journal of Comparative Economics, Elsevier, vol. 51(3), pages 960-988.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2601.08352. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.