IDEAS home Printed from https://ideas.repec.org/a/bla/asiaec/v24y2010i3p221-234.html
   My bibliography  Save this article

Who Are the Potential Smokers of Smuggled Cigarettes?

Author

Listed:
  • Hsin‐Fan Chen
  • Sheng‐Hung Chen
  • Jie‐Min Lee
  • Huei‐Yann Jeng

Abstract

Although smuggled cigarettes have been a prevalent problem and a severe challenge to public health and welfare around the world, little is known about the behavior associated with smoking smuggled cigarettes and the issue is difficult to study due to data limitations. By means of a population‐based tobacco survey conducted in Taiwan, the present paper applies a latent class model to identify potential smokers who are either currently or will at some point in the future be consuming smuggled cigarettes. This methodology, in contrast to the traditional discrete models, allows potential smokers who are more inclined to smoke smuggled cigarettes to be endogenously classified. The empirical results indicate that socio‐demographic factors do increase the inclination to smoke smuggled cigarettes after unobserved heterogeneity has been accounted for.

Suggested Citation

  • Hsin‐Fan Chen & Sheng‐Hung Chen & Jie‐Min Lee & Huei‐Yann Jeng, 2010. "Who Are the Potential Smokers of Smuggled Cigarettes?," Asian Economic Journal, East Asian Economic Association, vol. 24(3), pages 221-234, September.
    • Handle: RePEc:bla:asiaec:v:24:y:2010:i:3:p:221-234
    DOI: 10.1111/j.1467-8381.2010.02040.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-8381.2010.02040.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-8381.2010.02040.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. T. Anderson, 1954. "On estimation of parameters in latent structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(1), pages 1-10, March.
    2. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    3. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
    4. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    5. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Provencher, Bill & Bishop, R.C.Richard C., 2004. "Does accounting for preference heterogeneity improve the forecasting of a random utility model? A case study," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 793-810, July.
    8. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-126, April.
    9. Gruber, Jonathan & Sen, Anindya & Stabile, Mark, 2003. "Estimating price elasticities when there is smuggling: the sensitivity of smoking to price in Canada," Journal of Health Economics, Elsevier, vol. 22(5), pages 821-842, September.
    10. Jha, Prabhat & Chaloupka, Frank (ed.), 2000. "Tobacco Control in Developing Countries," OUP Catalogue, Oxford University Press, number 9780192632463.
    11. Heckman, James J. & Singer, Burton, 1984. "Econometric duration analysis," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 63-132.
    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. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.
    2. Arnstein Øvrum, 2011. "Socioeconomic status and lifestyle choices: evidence from latent class analysis," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 971-984, August.
    3. Peter Sivey, 2012. "The effect of waiting time and distance on hospital choice for English cataract patients," Health Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 444-456, April.
    4. Emmanouil Mentzakis & Mandy Ryan & Paul McNamee, 2011. "Using discrete choice experiments to value informal care tasks: exploring preference heterogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 930-944, August.
    5. Alegre, Joaquín & Mateo, Sara & Pou, Llorenç, 2011. "A latent class approach to tourists’ length of stay," Tourism Management, Elsevier, vol. 32(3), pages 555-563.
    6. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    7. Marit E. Kragt & Brendan Lynch & Rick S. Llewellyn & Wendy J. Umberger, 2019. "What farmer types are most likely to adopt joint venture farm business structures?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), pages 881-896, October.
    8. Daniele Fabbri & Chiara Monfardini, 2003. "Public vs. Private Health Care Services Demand in Italy," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 62(1), pages 93-123, April.
    9. Hendrik Schmitz, 2012. "More health care utilization with more insurance coverage? Evidence from a latent class model with German data," Applied Economics, Taylor & Francis Journals, vol. 44(34), pages 4455-4468, December.
    10. Pradnya Naik-Panvelkar & Carol Armour & John Rose & Bandana Saini, 2012. "Patient Preferences for Community Pharmacy Asthma Services," PharmacoEconomics, Springer, vol. 30(10), pages 961-976, October.
    11. Catalina M. Torres & Sergio Colombo & Nick Hanley, 2014. "Incorrectly accounting for preference heterogeneity in choice experiments: what are the implications for welfare measurement?," DEA Working Papers 65, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    12. Angel Bujosa & Antoni Riera & Robert Hicks, 2010. "Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 47(4), pages 477-493, December.
    13. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
    14. Stephane Hess, 2014. "Latent class structures: taste heterogeneity and beyond," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 14, pages 311-330, Edward Elgar Publishing.
    15. Milon, J. Walter & Scrogin, David, 2006. "Latent preferences and valuation of wetland ecosystem restoration," Ecological Economics, Elsevier, vol. 56(2), pages 162-175, February.
    16. Sagebiel, Julian, 2017. "Preference heterogeneity in energy discrete choice experiments: A review on methods for model selection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 804-811.
    17. Yoo, James & Ready, Richard C., 2014. "Preference heterogeneity for renewable energy technology," Energy Economics, Elsevier, vol. 42(C), pages 101-114.
    18. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    19. Brown, Sarah & Greene, William H. & Harris, Mark N. & Taylor, Karl, 2015. "An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donations," Economic Modelling, Elsevier, vol. 50(C), pages 228-236.
    20. D Rigby & M Burton, 2003. "Capturing Preference Heterogeneity in Stated Choice Models: A Random Parameter Logit Model of the Demand for GM Food," Economics Discussion Paper Series 0319, Economics, The University of Manchester.

    More about this item

    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:bla:asiaec:v:24:y:2010:i:3:p:221-234. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/eaeaaea.html .

    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.