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Gambling participation in Australia: findings from the national Household Expenditure Survey

Author

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  • Andrew Worthington
  • Kerry Brown
  • Mary Crawford
  • David Pickernell

Abstract

Regression modeling is used to predict gambling patterns in Australia on the basis of the unit record files underlying the Australian Bureau of Statistics’ Household Expenditure Survey of 6,892 households. The four largest categories of gambling expenditure are examined, namely: lottery tickets, lotto-type games and instant lottery (scratch cards), TAB (pari-mutuel wagering) and related on course betting, and poker (slot) machines and ticket machines. Determining factors analyzed include the source and level of household income, family composition and structure, welfare status, gender, age, ethnicity and geographic location. Apart from the determinants of expenditure varying widely across the different types of gambling activity, the results generally indicate that the source of household income is more important than the level of income and that household composition and regional location are likewise significant in determining gambling expenditure. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Andrew Worthington & Kerry Brown & Mary Crawford & David Pickernell, 2007. "Gambling participation in Australia: findings from the national Household Expenditure Survey," Review of Economics of the Household, Springer, vol. 5(2), pages 209-221, June.
    • Handle: RePEc:kap:reveho:v:5:y:2007:i:2:p:209-221
    DOI: 10.1007/s11150-007-9006-1
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Tim Friehe & Mario Mechtel, 2017. "Gambling to leapfrog in status?," Review of Economics of the Household, Springer, vol. 15(4), pages 1291-1319, December.
    2. S. Capacci & E. Randon & A. E. Scorcu, 2014. "Luck vs Skill in Gambling over the Recession. Evidence from Italy," Working Papers wp918, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. John Eakins, 2016. "Household gambling expenditures and the Irish recession," International Gambling Studies, Taylor & Francis Journals, vol. 16(2), pages 211-230, August.
    4. Giuliano Resce & Raffaele Lagravinese & Elisa Benedetti & Sabrina Molinaro, 2019. "Income-related inequality in gambling: evidence from Italy," Review of Economics of the Household, Springer, vol. 17(4), pages 1107-1131, December.
    5. Po-Chin Wu & Shiao-Yen Liu & Kou-Bau Wang, 2017. "Does Unemployment Matter for Lottery Sales and their Persistence? A New Estimation Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(2), pages 581-592, January.
    6. Brad R. Humphreys & Yang Seung Lee & Brian P. Soebbing, 2010. "Consumer behaviour in lottery: the double hurdle approach and zeros in gambling survey data," International Gambling Studies, Taylor & Francis Journals, vol. 10(2), pages 165-176, August.
    7. Levi Pérez & Brad R. Humphreys, 2011. "The Income Elasticity of Lottery: New Evidence from Micro Data," Public Finance Review, , vol. 39(4), pages 551-570, July.
    8. Sara Capacci & Emanuela Randon & Antonello Eugenio Scorcu, 2017. "Are Consumers More Willing to Invest in Luck During Recessions?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(1), pages 25-38, March.
    9. Humphreys, Brad & Lee, Yang Seung & Soebbing, Brian, 2009. "Consumer Behaviour in Lotto Markets: The Double Hurdle Approach and Zeros in Gambling Survey Data," Working Papers 2009-27, University of Alberta, Department of Economics.
    10. Page, Lionel & Savage, David A. & Torgler, Benno, 2014. "Variation in risk seeking behaviour following large losses: A natural experiment," European Economic Review, Elsevier, vol. 71(C), pages 121-131.
    11. Giebeler, Constanze & Rebeggiani, Luca, 2019. "Who Loves to Gamble? Socio-Economic Factors Determining Gambling Behaviour in Germany," MPRA Paper 94735, University Library of Munich, Germany.
    12. James Rude & Yves Surry & Robert Kron, 2014. "A generalized double-hurdle model of Swedish gambling expenditures," Applied Economics, Taylor & Francis Journals, vol. 46(34), pages 4151-4163, December.
    13. Po-Chin Wu & Hsiao & I-Chung & Tsai & Meng-Hua, 2018. "Nonlinear Effect of Business Cycle on Lottery Sales Stability," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 8(4), pages 1-3.

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    More about this item

    Keywords

    Gambling expenditure; Socioeconomic and demographic characteristics; Cross-sectional analysis; C31; C35; D12; H22;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • H22 - Public Economics - - Taxation, Subsidies, and Revenue - - - Incidence

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