IDEAS home Printed from https://ideas.repec.org/a/psc/journl/v12y2020i2p113-144.html
   My bibliography  Save this article

The Analysis of the Tobacco Product Bans Using a Random Coefficients Logit Model

Author

Listed:
  • Bartosz OlesiÅ„ski

    (Warsaw School of Economics
    EY Economic Analysis Team)

Abstract

The studies of tobacco demand accounting for product diversity have attracted much attention in the literature, but the ex ante measurements of the effects of product bans are relatively scarce. This paper aims to fill this gap and considers the 2020 EU-induced ban on menthol cigarettes as an example, focusing on the Polish market. In the proposed approach, a 2004-2017 productlevel dataset for Poland is used to estimate a random coefficients logit model and simulate the effects of the menthol ban and, for comparison, a cigarette excise hike. The dataset is unique as it encompassess substantial changes in the tobacco tax level and structure that took place in Poland over the sample period. The simulations suggest that the ban, despite switching of consumers towards non-menthol cigarettes, results in relatively strong reduction in demand for duty-paid cigarettes, stronger than in the case of the excise hike.

Suggested Citation

  • Bartosz OlesiÅ„ski, 2020. "The Analysis of the Tobacco Product Bans Using a Random Coefficients Logit Model," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(2), pages 113-144, June.
    • Handle: RePEc:psc:journl:v:12:y:2020:i:2:p:113-144
    as

    Download full text from publisher

    File URL: http://cejeme.org/publishedarticles/2020-18-18-637280903151243154-2970.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William N. Evans & Matthew C. Farrelly, 1998. "The Compensating Behavior of Smokers: Taxes, Tar, and Nicotine," RAND Journal of Economics, The RAND Corporation, vol. 29(3), pages 578-595, Autumn.
    2. Aviv Nevo, 2000. "Mergers with Differentiated Products: The Case of the Ready-to-Eat Cereal Industry," RAND Journal of Economics, The RAND Corporation, vol. 31(3), pages 395-421, Autumn.
    3. Steve Berry & Oliver B. Linton & Ariel Pakes, 2004. "Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(3), pages 613-654.
    4. Ciliberto Federico & Kuminoff Nicolai V, 2010. "Public Policy and Market Competition: How the Master Settlement Agreement Changed the Cigarette Industry," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-46, July.
    5. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    6. Timothy B. Armstrong, 2016. "Large Market Asymptotics for Differentiated Product Demand Estimators With Economic Models of Supply," Econometrica, Econometric Society, vol. 84, pages 1961-1980, September.
    7. Ackerberg, Daniel & Lanier Benkard, C. & Berry, Steven & Pakes, Ariel, 2007. "Econometric Tools for Analyzing Market Outcomes," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 63, Elsevier.
    8. Florkowski, Wojciech J. & McNamara, Kevin T., 1992. "Policy implications of alcohol and tobacco demand in Poland," Journal of Policy Modeling, Elsevier, vol. 14(1), pages 93-98, February.
    9. Christopher R. Knittel & Konstantinos Metaxoglou, 2014. "Estimation of Random-Coefficient Demand Models: Two Empiricists' Perspective," The Review of Economics and Statistics, MIT Press, vol. 96(1), pages 34-59, March.
    10. Levy, D.T. & Pearson, J.L. & Villanti, A.C. & Blackman, K. & Vallone, D.M. & Niaura, R.S. & Abrams, D.B., 2011. "Modeling the future effects of a menthol ban on smoking prevalence and smoking-attributable deaths in the United States," American Journal of Public Health, American Public Health Association, vol. 101(7), pages 1236-1240.
    11. Barzel, Yoram, 1976. "An Alternative Approach to the Analysis of Taxation," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1177-1197, December.
    12. M.C. Farrelly & C.T. Nimsch & A. Hyland & M. Cummings, 2004. "The effects of higher cigarette prices on tar and nicotine consumption in a cohort of adult smokers," Health Economics, John Wiley & Sons, Ltd., vol. 13(1), pages 49-58, January.
    13. Brunner, Daniel & Heiss, Florian & Romahn, André & Weiser, Constantin, 2017. "Reliable estimation of random coefficient logit demand models," DICE Discussion Papers 267, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    14. Hong Liu & John A. Rizzo & Qi Sun & Fang Wu, 2015. "How Do Smokers Respond to Cigarette Taxes? Evidence from China's Cigarette Industry," Health Economics, John Wiley & Sons, Ltd., vol. 24(10), pages 1314-1330, October.
    15. Jérôme Adda & Francesca Cornaglia, 2006. "Taxes, Cigarette Consumption, and Smoking Intensity," American Economic Review, American Economic Association, vol. 96(4), pages 1013-1028, September.
    16. 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.
    17. Heechul Min, 2011. "Reform in a Differentiated-Product Industry: The Case of the Korean Cigarette Manufacturing Industry," Korean Economic Review, Korean Economic Association, vol. 27, pages 57-74.
    18. Wei Tan, 2006. "The Effects of Taxes and Advertising Restrictions on the Market Structure of the U.S. Cigarette Market," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 28(3), pages 231-251, May.
    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. Hong Liu & John A. Rizzo & Qi Sun & Fang Wu, 2015. "How Do Smokers Respond to Cigarette Taxes? Evidence from China's Cigarette Industry," Health Economics, John Wiley & Sons, Ltd., vol. 24(10), pages 1314-1330, October.
    2. Hyunchul Kim & Dongwon Lee, 2021. "Racial demographics and cigarette tax shifting: evidence from scanner data," Empirical Economics, Springer, vol. 61(2), pages 1011-1037, August.
    3. Ketz, Philipp, 2019. "On asymptotic size distortions in the random coefficients logit model," Journal of Econometrics, Elsevier, vol. 212(2), pages 413-432.
    4. Laura Grigolon, 2021. "Blurred boundaries: A flexible approach for segmentation applied to the car market," Quantitative Economics, Econometric Society, vol. 12(4), pages 1273-1305, November.
    5. Moon, Hyungsik Roger & Shum, Matthew & Weidner, Martin, 2018. "Estimation of random coefficients logit demand models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 613-644.
    6. Iaria, Alessandro & ,, 2020. "Identification and Estimation of Demand for Bundles," CEPR Discussion Papers 14363, C.E.P.R. Discussion Papers.
    7. Kenchington, David G. & Shohfi, Thomas D. & Smith, Jared D. & White, Roger M., 2022. "Do sin tax hikes spur cheating in interpersonal exchange?," Accounting, Organizations and Society, Elsevier, vol. 96(C).
    8. Escobari, Diego, 2017. "Airport, airline and departure time choice and substitution patterns: An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 198-210.
    9. Ciliberto Federico & Kuminoff Nicolai V, 2010. "Public Policy and Market Competition: How the Master Settlement Agreement Changed the Cigarette Industry," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-46, July.
    10. Lu, Zhentong & Shi, Xiaoxia & Tao, Jing, 2023. "Semi-nonparametric estimation of random coefficients logit model for aggregate demand," Journal of Econometrics, Elsevier, vol. 235(2), pages 2245-2265.
    11. Christopher Conlon & Julie Holland Mortimer, 2021. "Empirical properties of diversion ratios," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 693-726, December.
    12. Lesley Chiou & Erich Muehlegger, 2014. "Consumer Response to Cigarette Excise Tax Changes," National Tax Journal, National Tax Association;National Tax Journal, vol. 67(3), pages 621-650, September.
    13. Mattia Girotti & Richard Meade, 2017. "U.S. Savings Banks' Demutualization and Depositor Welfare," Working Papers 2017-08, Auckland University of Technology, Department of Economics.
    14. Steven T. Berry & Philip A. Haile, 2021. "Foundations of Demand Estimation," Cowles Foundation Discussion Papers 2301, Cowles Foundation for Research in Economics, Yale University.
    15. Friberg, Richard & Romahn, André, 2015. "Divestiture requirements as a tool for competition policy: A case from the Swedish beer market," International Journal of Industrial Organization, Elsevier, vol. 42(C), pages 1-18.
    16. Hyungsik Roger Moon & Matthew Shum & Martin Weidner, 2017. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 12/17, Institute for Fiscal Studies.
    17. Vivienne Pham & David Prentice, 2010. "An empirical Analysis of the Counter-factual: A Merger and Divestiture in the Australian Cigarette Industry," Working Papers 2010.08 EDIRC Provider-In, School of Economics, La Trobe University.
    18. Filistrucchi, L. & Gerardin, D. & van Damme, E.E.C. & Keunen, S. & Klein, T.J. & Michielsen, T.O. & Wileur, J., 2010. "Mergers in Two-Sided Markets - A Report to the NMa," Other publications TiSEM f901d1fe-8878-444e-a685-8, Tilburg University, School of Economics and Management.
    19. Weifang Lou & David Prentice & Xiangkang Yin, 2008. "The Effects of Product Ageing on Demand: The Case of Digital Cameras," Working Papers 2008.06, School of Economics, La Trobe University.
    20. Byrne, David P. & Imai, Susumu & Jain, Neelam & Sarafidis, Vasilis, 2022. "Instrument-free identification and estimation of differentiated products models using cost data," Journal of Econometrics, Elsevier, vol. 228(2), pages 278-301.

    More about this item

    Keywords

    tobacco policy analyses; discrete choice models; substitution effects; BLP;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • H22 - Public Economics - - Taxation, Subsidies, and Revenue - - - Incidence
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    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:psc:journl:v:12:y:2020:i:2:p:113-144. 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: Damian Jelito (email available below). General contact details of provider: http://cejeme.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.