Australia's Gambling Industries - Productivity Commission

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Table I.3 Weighted estimation Relationship between Median weekly income and the number of gaming machines Average annual expenditure on gaming machines and the number of gaming machines Equations Y × W = β + β ( NGM × W ij ij 1 j 2 j ij ij GE × W = β + β ( NGM × W ij ij 1 j 2 j ij ij ) ) Median weekly income and average annual expenditure on gaming machines where: Y median weekly income per person in region i in state j; ij NGM ij number of gaming machines in region i in state j; GE ij Y × W = β + β ( GE × W ij ij 1 j 2 j ij ij average annual expenditure on gaming machines in region i in state j; and W ij the population in region i in state j, divided by the population of all regions with gaming machines in state j. ) I.3 Results The unweighted and weighted analysis yields similar results for the selected states. The weighted results are a better estimation of the relationships, but the unweighted provide an indication of the results that can also be shown graphically. The statistical significance of the results have been assessed at the 5 per cent level. Unweighted results The unweighted results provide an indication of the relationship between income, gaming expenditure and the number of gaming machines in selected states. This analysis has only been provided to show the nature of the relationship diagrammatically. The results from the weighted analysis, presented in the following section, are a better indicator of these relationships, but are unable to be shown graphically because of their three dimensional nature. The <strong>Commission</strong>’s unweighted analysis suggests that there is: • a negative and statistically significant relationship between median weekly income and the number of gaming machines in New South Wales and South Australia — at lower income levels there were a greater the number of gaming REGIONAL DATA ANALYSIS I.5
machines. There is no statistically significant relationship in Queensland and Victoria; • a positive and statistically significant relationship between average annual expenditure on gaming machines and the number of gaming machines in all states examined — at higher levels of expenditure on gaming machines there were a greater the number of machines; and • no statistically significant relationship between median weekly income and average annual expenditure on gaming machines for all states examined (table I.4 and figures I.1 to I.3). Table I.4 Unweighted results for selected states ab Unweighted coefficient (t statistic) Relationship between NSW Vic cde Qld SA f Median weekly income and the number of gaming machines Average annual expenditure on gaming machines and the number of gaming machines Median weekly income and average annual expenditure on gaming machines Negative and significant -0.71 (-3.48) No significant relationship -0.05 (-0.62) No significant relationship 0.10 (0.52) Negative and significant -0.52 (-2.82) Positive and significant 2.12 (7.51) na Positive and significant 2.76 (8.81) Positive and significant 1.66 (5.69) No significant relationship -0.69 (-1.10) na No significant relationship 0.50 (0.72) No significant relationship -0.51 (-0.98) na not available a The data used for median weekly income, the number of gaming machines and average annual expenditure on gaming machines are explained in section I.1. b The results are statistically significant at the 5 per cent level. c Data are unavailable on average annual expenditure on gaming machines in Victoria. d Data for the City of Melbourne produces an outlier that has been removed from the analysis. This region has a large number of gaming machines and high median incomes. Including the City of Melbourne yields the following results: median weekly income and the number of gaming machines 0.01 (0.08). e Analysis was also undertaken for metropolitan and non-metropolitan regions. The results for metropolitan regions (excluding the City of Melbourne) are -0.35 (-3.98) and for non-metropolitan regions are 0.07 (0.32). f Data for the City of Adelaide and Roxby Downs produce two outliers that have been removed from the analysis. These regions have a large number of gaming machines and high median incomes. Including the City of Adelaide and Roxby Downs yields the following results: median weekly income and the number of gaming machines 0.06 (0.32), average annual expenditure on gaming machines and the number of gaming machines 2.09 (10.30) and median weekly income and average expenditure on gaming machines 1.48 (2.17). I.6 GAMBLING
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Australia’s Gambling Industries I
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Contents of other volumes Volume 1
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Australian Capital Territory Federa
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Tasmania Wrest Point Casino New Zea
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Marianne James Prof Jan McMillen Pe
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Canberra, 30 November 1998 Senator
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Sydney, 16-17 September 1999 Rev Fr
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N Ward 28 Evelyn Jago 29 Territory
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Australian Hotels Association (SA)
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Women’s Health West 176 Norfolk I
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BetSafe Group - Paul Symond Consult
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B Participation in gambling: data t
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Table B.2 Participation in gambling
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Table B.4 Participation in gambling
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product in excess of the price paid
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C.2 Consumer surplus in the gamblin
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from increased consumption resultin
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Figure C.2 Tax and consumer surplus
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Table C.3 Price elasticities of dem
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Figure C.3 Consumer surplus for pro
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Box C.1 continued (e) That part of
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Table C.4 continued Wagering Lotter
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s n = share of gambling expenditure
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Figure C.6 Demand for gambling by p
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• the triangular area ’g’ whi
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The Commission’s treatment falls
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Box C.4 Explaining the lack of vari
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demand may become elastic, as peopl
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There are a number possible explana
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• Firstly, there has been extraor
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E Gambling in indigenous communitie
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The pattern of institutionally-base
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chase the “miracles” offered by
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F National Gambling Survey F.1 Intr
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F.2 The questionnaire Development o
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The use of this sampling approach m
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Box F.1 List of gambling activities
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• Big spending regular or less fr
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Questions asked of all respondents
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Comparisons of aggregate expenditur
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elated to their gambling — all
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Interview duration As with any ques
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ecause of non-payment), while there
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• post-weighting the sample data
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particular area/age/gender cell fro
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esult in turn reflects the survey p
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F.11 Contact and participation rate
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Being aware of the need to minimise
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NATIONAL GAMBLING SURVEY F.31
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F.52 GAMBLING
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F.54 GAMBLING
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F.56 GAMBLING
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F.58 GAMBLING
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F.60 GAMBLING
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F.62 GAMBLING
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F.64 GAMBLING
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F.66 GAMBLING
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G Survey of Clients of Counselling
Page 137 and 138: G.3 Question by question A1 to A3
Page 139 and 140: D23 — is concerned with the mecha
Page 141 and 142: of problem gambling (eg how many ch
Page 143 and 144: CLIENT SURVEY G.9
Page 161 and 162: Problem gamblers may subsequently b
Page 163 and 164: For a subset of 856 clients in 1996
Page 165 and 166: Table H.3 Variable Logistic estimat
Page 167 and 168: Prison, South Australia’s main re
Page 169 and 170: • “Has your gambling ever led y
Page 171 and 172: elicit information on vocational, f
Page 173 and 174: This finding is consistent with the
Page 175 and 176: H.5 What crimes do problem gamblers
Page 177 and 178: Other more violent crimes such as b
Page 179 and 180: But as noted above, police statisti
Page 181 and 182: H.8 Problem gambling and loan shark
Page 183 and 184: epayments were required — but mos
Page 185 and 186: State Gaming Authorities data The s
Page 187: Table I.2 Unweighted estimation Med
Page 191 and 192: Figure I.2 Expenditure on gaming ma
Page 193 and 194: Weighted results The Commission’s
Page 195 and 196: Table I.7 Summary of Victorian metr
Page 197 and 198: Table I.9 Summary of Queensland reg
Page 199 and 200: it is likely to represent the more
Page 201 and 202: Table J.1 presents the information
Page 203 and 204: suffer from some of the adverse con
Page 205 and 206: • costs of gambling counselling s
Page 207 and 208: To the extent that borrowed money i
Page 209 and 210: This fee is only taken in estates w
Page 211 and 212: • for a higher estimate, the numb
Page 213 and 214: The Commission has assumed that the
Page 215 and 216: • to estimate the income lost ove
Page 217 and 218: the Commission has used this estima
Page 219 and 220: • 336 people receiving a jail sen
Page 221 and 222: states offer up to $50 000 each for
Page 223 and 224: As indicated in table J.6, where pr
Page 225 and 226: seen as part of the informal contra
Page 227 and 228: Almost all divorce cases are uncont
Page 229 and 230: of their gambling during the period
Page 231 and 232: Suicide ideation The Commission’s
Page 233 and 234: Table J.10 continued People a Per p
Page 235 and 236: Table J.12 Value of annual transfer
Page 237 and 238: pathological and problem gamblers a
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Table K.2 Summary of cost estimates
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L Survey of Counselling Services Th
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Several academics working in the ar
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L.4 Survey results Nature of agenci
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Number of clients The survey includ
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Characteristics of gambling clients
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counselling because of someone else
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Table L.17 Full time equivalent pai
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Table L.20 Approaches used to help
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Table L.24 Gambling clients ending
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More specifically, agencies said fu
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Centacare (Whyalla) Centre for Anxi
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SURVEY OF COUNSELLING SERVICES L.23
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Table M.1 Major forms of gambling t
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and sport development fund. In some
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Tax on keno In New South Wales, the
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Poker machines In most states, lice
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Table M3: Gaming machine taxation b
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Table M3: (continued) Hotels: Levie
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Table M4: (continued) NSW VIC QLD W
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Table M5: (continued) OTHER GAMBLIN
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N.1 Characteristics of machines of
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Table N.1 Australia, Japan, United
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Table N.2 Australia, Indiana, Conne
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The following discussion of gaming
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Canada Broadly speaking, Canada has
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Figure N.4 Japanese pachislo machin
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Winnings Progressive jackpots are p
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Bets and losses Bets and losses on
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In Japan, the minimum amount requir
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N.2 Market segments As with many ot
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Box N.4 Comments on market segments
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O Displacement of illegal gambling?
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survive together because they cater
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P Spending by problem gamblers The
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Table P.1 Outlays, player losses an
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Table P.3 Concentration of outlays
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Figure P.2 Distribution of outlay b
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Table P.4 Expenditure shares of pro
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is adjusted for biases in its estim
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ACIL (sub. D233. p. 48) claimed tha
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P.5 Estimating the expenditure shar
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expenditures shares are shown in ta
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of counselling agencies is necessar
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Table Q.2 Employment status of prob
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Table Q.3 continued Study Average a
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Relationship status The greater inv
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Table Q.6 Gender of problem gambler
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The pattern of an increased feminis
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R Bankruptcy and gambling This appe
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Table R.2 Age profile of bankrupts,
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Table R.5 New bankruptcies per mill
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Figure R.2 continued Western Austra
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• The penalty has become less sev
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S State and territory gambling data
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Table S.4 Real government revenue f
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Table S.8 Real government revenue,
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Table S.12 Real government revenue
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Dickerson et al (1998, p. 79) for e
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However, the survey used a set of p
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T.3 The logistic approach The NORC
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Table T.3 Method Various estimates
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such as France and the US (Casino I
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Table U.2 An example of an outcome
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intensity on the 85.15 per cent Cas
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considers that the machine price
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egular playing (30 years) the proba
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for an amount of time that is less
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U.6 The gambler’s fallacy Gambler
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This does not mean that a person ca
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V Use of the SOGS in Australian gam
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Differences in question wording and
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References AADAC (Alberta Alcohol a
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—— 1998, Efficient Tobacco Taxa
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Bickerdyke, I. and Lattimore, R. 19
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——, Dickerson, M. and Harley, B
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Campbell, C. and Smith G. 1998, Can
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—— and Winefield, A.H. 1996, Co
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——, Baxter, P., Boreham, P., Ha
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Ferguson, B. 1996, A Note on the In
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—— 1997, Legalised Gambling as
Page 419 and 420:
Horner, T. and Bradfield, G. 1998,
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——, Marston, A., Singer, R., Wi
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Gambling Studies, ‘Towards 2000:
Page 425 and 426:
—— 1995b, Social impacts of urb
Page 427 and 428:
—— and Ohtsuka, K. 1999, ‘The
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NT Select Committee (Select Committ
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Prosser, G., Breen, H., Weeks, P. a
Page 433 and 434:
Single, E., Collins, D., Easton, B.
Page 435 and 436:
Thomas, S., Jackson, A., Thomason,
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—— 1997, Gambling and Problem G
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Australia's Gambling Industries - Productivity Commission

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