Governments world-wide increasingly rely on gambling revenues, increasing the importance of understanding who gambles and why. Previous literature used Tobit and Heckman models to statistically analyse participation in gambling. These models make strong assumptions about the nature of gambling participation. We examine the double hurdle model as an alternative to other statistical approaches to modelling gambling participation and spending for lotteries in the province of Alberta, Canada. Our results for lotteries, based on data from a 2002 survey of gambling prevalence in Alberta, clearly prefer the double hurdle model, which yields different results than the commonly used Tobit model. This has important implications for governments who rely on revenues from lottery to fund many different programs in their jurisdictions.
Survey data on participation in gambling typically contain many zeros. The presence of many zeros presents methodological problems for the analysis of participation in gambling markets and gambling expenditure. The most common techniques for handling zeros in gambling data have been the Tobit estimator and the Heckman selectivity estimator. Recent research indicates that hurdle models (Jones 1989, 2000) and the Cragg (1971) model, are better suited to analyze participation in gambling. We apply these models to gambling participation in Canada and find that the double hurdle model is preferred in two of the three forms of gambling examined.
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