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Is response to price equal for those with higher alcohol consumption?



To determine if taxation policies that increase the price of alcohol differentially reduce alcohol consumption for heavy drinkers in Australia.


A two-part demand model for alcohol consumption is used to determine the price elasticity of alcohol. Quantile regression is used to determine the price elasticity estimates for various levels of consumption.


The study uses Australian data collected by the National Drug Strategy Household Survey for the years 2001, 2004 and 2007.


Measures of individual annual alcohol consumption were derived from three waves of the National Drug Strategy Household Survey; alcohol prices were taken from market research reports.


For the overall population of drinkers, a 1 % increase in the price of alcohol was associated with a 0.96 % (95 % CI −0.35 %, −1.57 %) reduction in alcohol consumption. For those in the highest 10 % of drinkers by average amount consumed, a 1 % increase in the price of alcohol was associated with a 1.26 % (95 % CI 0.82 %, 1.70 %) reduction in consumption.


Within Australia, policies that increase the price of alcohol are about equally effective in relative terms for reducing alcohol consumption both for the general population and among those who drink heavily.

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  1. Begg, S., Vos, T., Barker, B., Stevenson, C., Stanley, L., Lopez, A.D.: The burden of disease and injury in Australia 2003. AIHW, Canberra (2007)

    Google Scholar 

  2. Collins, D., Lapsley, H.: The costs of tobacco, alcohol and illicit drug abuse to Australian society in 2004/05. Department of Health and Ageing, Canberra (2008)

    Book  Google Scholar 

  3. Laslett AM, Catalano P, Chikritzhs T, Dale C, Doran C, Ferris J, et al. The range and magnitude of alcohol’s harm to others. Fitzroy: AER Centre for Alcohol Policy Research, Turning Point Alcohol and Drug Centre, Eastern Health 2010

  4. Freebairn, J.: Special taxation of alcoholic beverages to correct market failures. Econ. Pap. 29(2), 200–214 (2010)

    Article  Google Scholar 

  5. Byrnes, J.M., Cobiac, L.J., Doran, C.M., Vos, T., Shakeshaft, A.P.: Cost-effectiveness of volumetric alcohol taxation in Australia. Med. J Australia. 192(8), 439–443 (2010)

    PubMed  Google Scholar 

  6. Cnossen S, editor. Excise Taxation in Australia. Melbourne Institute–Australia’s future tax and transfer policy conference; 2009 2010; University of Melbourne. Melbourne: Melbourne Institute of Applied Economic and Social Research; 2010

  7. Preventative Health Taskforce: National preventative health strategy—the road map for action. Preventative Health Taskforce, Canberra (2009)

    Google Scholar 

  8. Treasury. Australia’s future tax system: report to the Treasurer. Canberra: Commonwealth of Australia 2009

  9. Cobiac, L., Vos, T., Doran, C., Wallace, A.: Cost-effectiveness of interventions to prevent alcohol-related disease and injury in Australia. Addiction. 104(10), 1646–1655 (2009)

    Article  PubMed  Google Scholar 

  10. Petrie, D., Doran, C., Shakeshaft, A.: Willingness to pay to reduce alcohol-related harm in Australian rural communities. Expert. Rev. Pharmacoeconomics. Outcomes. Res. 3, 351–363 (2011)

    Article  Google Scholar 

  11. Cook, P.J., Tauchen, G.: The effect of liquor taxes on heavy drinking. Bell. J. Econ. 13(2), 379–390 (1982)

    Article  Google Scholar 

  12. Richardson, J., Crowley, S.: Optimum alcohol taxation: balancing consumption and external costs. Health. Econ. 3(2), 73–87 (1994)

    Article  PubMed  CAS  Google Scholar 

  13. Wagenaar, A.C., Salois, M.J., Komro, K.A.: Effects of beverage alcohol price and tax levels on drinking: a meta-analysis of 1003 estimates from 112 studies. Addiction. 104(2), 179–190 (2009)

    Article  PubMed  Google Scholar 

  14. Byrnes, J., Shakeshaft, A., Petrie, D., Doran, C.: Can harms associated with high-intensity drinking be reduced by increasing the price of alcohol? Drug. Alcohol. Rev. 32, 27–30 (2013)

    Article  PubMed  Google Scholar 

  15. Manning, W.G., Blumberg, L., Moulton, L.H.: The demand for alcohol: the differential response to price. J. Health. Econ. 14(2), 123–148 (1995)

    Article  PubMed  CAS  Google Scholar 

  16. Purshouse, R.C., Meier, P.S., Brennan, A., Taylor, K.B., Rafia, R.: Estimated effect of alcohol pricing policies on health and health economic outcomes in England: an epidemiological model. Lancet. 375(9723), 1355–1364 (2010)

    Article  PubMed  Google Scholar 

  17. Cragg, J.G.: Some statistical models for limited dependent variables with application to the demand for durable goods. Econometrica. 39(5), 829–844 (1971)

    Article  Google Scholar 

  18. Haines, P.S., Guilkey, D.K., Popkin, B.M.: Modeling food consumption decisions as a two-step process. Am. J. Agric. Econ. 70(3), 543–552 (1988)

    Article  Google Scholar 

  19. Reynolds, A.: Analyzing fresh vegetable consumption from household survey data. South. J. Agric. Econ. 22(2), 31–38 (1990)

    Google Scholar 

  20. Wang, Q., Jensen, H.H.: Do consumers respond to health information in food choices? Models and evaluation of egg consumption. In: Mauldin, T.A. (ed.) Consumer interests annual, pp. 57–64. ACCI, Combia (1994)

    Google Scholar 

  21. Burton, M., Dorsett, R., Young, T.: Changing preferences for meat: evidence from UK household data, 1973–93. Eur. Rev. Agric. Econ. 23(3), 357–370 (1996)

    Article  Google Scholar 

  22. Yen, S.T., Huang, C.L.: Household demand for finfish: a generalized double-hurdle model. J. Agric. Resour. Econ. 21(2), 220–234 (1996)

    Google Scholar 

  23. Newman, C., Henchion, M., Matthews, A.: Infrequency of purchase and double-hurdle models of Irish households’ meat expenditure. Eur. Rev. Agric. Econ. 28(4), 393–420 (2001)

    Article  Google Scholar 

  24. Moffatt, P.G.P.: Hurdle models of loan default. J. Oper. Res. Soc. 56(9), 1063–1071 (2005)

    Article  Google Scholar 

  25. Martínez-Espiñeira, R.: A Box-Cox double-hurdle model of wildlife valuation: the citizen’s perspective. Ecol. Econ. 58(1), 192–208 (2006)

    Article  Google Scholar 

  26. Blaylock, J.R., Blisard, W.N.: Women and the demand for alcohol: estimating participation and consumption. J. Consumer. Affairs. 27(2), 319–334 (1993)

    Article  Google Scholar 

  27. Yen, S.T.: Cross-section estimation of U.S. demand for alcoholic beverage. Appl. Econ. 26(4), 381–392 (1994)

    Article  Google Scholar 

  28. Yen, S.T., Jensen, H.H.: Determinants of household expenditures on alcohol. J. Consumer. Aff. 30(1), 48–67 (1996)

    Article  Google Scholar 

  29. Angulo, A.M., Gil, J.M., Gracia, A.: The demand for alcoholic beverages in Spain. Agric. Econ. 26(1), 71–83 (2001)

    Article  Google Scholar 

  30. Godfrey, C.: Factors influencing the consumption of alcohol and tobacco: the use and abuse of economic models. Br. J. Addict. 84(10), 1123–1138 (1989)

    Article  PubMed  CAS  Google Scholar 

  31. Zhao, X., Harris, M.N.: Demand for marijuana, alcohol and tobacco: participation, levels of consumption and cross-equation correlations. Econ. Record. 80(251), 394–410 (2004)

    Article  Google Scholar 

  32. Blundell, R., Meghir, C.: Bivariate alternatives to the Tobit model. Journal of Econometrics. 34(1/2), 179–200 (1987)

    Article  Google Scholar 

  33. Pudney, S.: Modeling individual choice, the econometrics of corners, kinks and holes. Blackwell, New York (1989)

    Google Scholar 

  34. Labeaga, J.M.: A double-hurdle rational addiction model with heterogeneity: estimating the demand for tobacco. J. Econometrics. 93(1), 49–72 (1999)

    Article  Google Scholar 

  35. Jones, A.M.: A double-hurdle model of cigarette consumption. J. Appl. Econom. 4(1), 23–39 (1989)

    Article  Google Scholar 

  36. Aristei, D., Peieroni, L.: A double-hurdle approach to modelling tobacco consumption in Italy. Appl. Econ. 40, 2463–2476 (2008)

    Article  Google Scholar 

  37. Koenker, R., Bassett Jr, G.: Regression quantiles. Econometrica. 46(1), 33–50 (1978)

    Article  Google Scholar 

  38. Bassett Jr, G., Koenker, R.: An empirical quantile function for linear models with iid errors. J. American. Stat. Assoc. 77(378), 407 (1982)

    Google Scholar 

  39. Fawcett, J., Shakeshaft, A., Harris, M., Wodak, A., Mattick, R.P., Richmon, R.: Using AUDIT to classify patients into Australian alcohol guideline categories. Med. J. Australia. 180, 598 (2004)

    PubMed  Google Scholar 

  40. Euromonitor International. Alcoholic drinks in Australia. Euromonitor international; 2008 [April 2008]; Available from:

  41. Australian bureau of statistics. Consumer price index, Australia. [cited June 2010]; Available from:

  42. Cameron, L., Williams, J.: Cannabis, alcohol and cigarettes: substitutes or complements? Econ. Rec. 77(236), 19 (2001)

    Article  Google Scholar 

  43. Hall, W.D., Chikritzhs, T., d’Abbs, P.H.N., Room, R.: Alcohol sales data are essential for good public policies towards alcohol. Med. J. Australia. 189(4), 188–189 (2008)

    PubMed  Google Scholar 

  44. Selvanathan, E.A., Selvanathan, S.: Economic and demographic factors in Australian alcohol demand. Appl. Econ. 36(21), 2405–2417 (2004)

    Article  Google Scholar 

  45. Frankfort-Nachmias, C., Nachmias, D.: Research methods in the social sciences. Worth Publishers, New York (2008)

    Google Scholar 

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Correspondence to Joshua Byrnes.

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Byrnes, J., Shakeshaft, A., Petrie, D. et al. Is response to price equal for those with higher alcohol consumption?. Eur J Health Econ 17, 23–29 (2016).

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  • Alcohol
  • Price
  • Tax
  • Policy

JEL Classification

  • D120
  • I120
  • I180