Probability of purchase, amount of purchase, and the demographic incidence of the lottery tax

Scott, Frank A.; Garen, John

doi:10.1016/0047-2727(94)90073-6

Cited by 109 publications

(131 citation statements)

References 14 publications

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“…8. Some econometric studies model the decision to participate and the amount of expenditures simultaneously, employing a Tobit model, or in two steps by means of a Heckman correction (see, for example, Sawkins and Dickie, 2002;Scott and Garen, 1994;see Tobin, 1958 andHeckman, 1979 regarding the methodology in general). In our approach, we are interested in estimating the structure of each process influence individually, which is why we estimate-independent of one another-the decision to participate by means of a logit model, on the one hand, and the amount of expenditures by means of OLS regression for the group of Lotto gamblers, on the other hand.…”

mentioning

confidence: 99%

The Inequality of Fair Play: Lottery Gambling and Social Stratification in Germany

Beckert¹,

Lutter²

2008

European Sociological Review

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confidence: 99%

The Inequality of Fair Play: Lottery Gambling and Social Stratification in Germany

Beckert¹,

Lutter²

2008

European Sociological Review

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“…Whilst few studies have employed more than a single expenditure classification as the dependent variable, the definitions adopted are consistent with Frank Scott and John Garen's (1994) and Harry Kitchen and Scott Powell's (1991) The set of socio-economic and demographic variables upon which the household gambling expenditures are regressed are also included in Table 1. Whilst there is no unequivocal rationale for predicting the direction and statistical significance of many of these independent variables, their inclusion is consistent with both past studies of gambling-taxation and demographic/socioeconomic incidence and the presumed interests of policy-makers and other parties.…”

Section: Star City Casino In Sydney Crown Casino In Melbourne Treasmentioning

confidence: 90%

“…Borg and Paul M. Mason (1988), Mary O. Borg, Paul M. Mason and Stephen L. Shapiro (1991;1993), Frank Scott and John Garen (1994), J. Ronnie Davis, John E. Filer and Donald L. Moak (1992), Raymond Jackson (1994), Ann Hansen (1995), Samuel Cooper and Elchanan Cohn (1994), William M. Rodgers and Charles Stuart (1995), John F. Scoggins (1995), Allan Layton and Andrew Worthington (1999) and Andrew Worthington (2001) are examples of this type of work. More recently, research has focused on a wider interpretation as a means of providing some policy input into the potential for problem gambling and other undesirable consequences of expansion in the gambling industry.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2007

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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. GPO Box 2434, Brisbane, QLD 4001, Australia. m.crawford@qut.edu.au DAVID PICKERNELLBusiness School, University of Glamorgan, Pontypridd, Wales CF37 1DL, United Kingdom. dgpicker@glam.ac.uk 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.

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“…Note that Scott and Garen (1994) and estimated the parameters of the latent variable model given by Eqs. 1 and 2 using the Heckman selectivity model and survey data from the U.S. state of Kentucky and the United Kingdom, respectively.…”

Section: The Empirical Analysis Of Consumer Spending On Lotteriesmentioning

confidence: 99%

“…The second strand of literature uses crosssectional data from surveys of consumers to analyze the determinants of expenditure on gaming goods like lotteries. Studies of consumer spending on gambling goods using micro-data from detailed surveys generally focus on a single lottery product and include Scott and Garen (1994), , Worthington (2001) and Kearney (2005).…”

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confidence: 99%

Network externalities in consumer spending on lottery games: evidence from Spain

Humphreys

Pérez

2010

Empir Econ

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We use data from two nationally representative Spanish surveys in 2005 and 2006 to investigate spending on lottery games. Estimates from Tobit and double hurdle models of participation in lottery markets and spending on lottery tickets find that frequent participation in one game is not associated with an increased or decreased probability of participating in other games, but is associated with increased spending on other games. Consumer spending on different lottery games exhibits inter-related consumption decisions. Also, the assumptions underlying the double hurdle model, but not the Tobit model, better describe consumer spending on lottery tickets in Spain.

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Probability of purchase, amount of purchase, and the demographic incidence of the lottery tax

Cited by 109 publications

References 14 publications

The Inequality of Fair Play: Lottery Gambling and Social Stratification in Germany

The Inequality of Fair Play: Lottery Gambling and Social Stratification in Germany

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

Network externalities in consumer spending on lottery games: evidence from Spain

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