Australia's Gambling Industries - Productivity Commission

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I Regional data analysis In chapter 10, the Commission discussed the results from a basic analysis of estimating the relationships between income levels, number of gaming machines and expenditure on gaming machines in different regions within New South Wales, Victoria, Queensland and South Australia. The econometric analysis involves the regression of cross-sectional data to provide an indication of the relationships between these variables. Chapter 10 presented a summary of the results weighted by the adult population in each region. This appendix outlines the data and methodology underlying those results, as well as presenting similar results, on an unweighted basis — that is, not adjusting for the population in a region. The results from the analyses show correlation and not causation between the variables. I.1 Data sources and issues The data are sourced from the Australian Bureau of Statistics (ABS) and the state gaming authorities (table I.1) for New South Wales, Victoria, Queensland and South Australia. The Commission did not undertake analyses of other jurisdictions because of data limitations and, in the case of Western Australia, its prohibition on gaming machines outside the casino. Australian Bureau of Statistics data The ABS data is the median weekly income and adult population for regions. It is sourced from 1996 Census of Population and Housing — State Summaries (ABS 1996a). Regional median weekly income per person is the median personal weekly income and the regional adult population is the sum of people aged over 18. The only income data provided by the ABS for regions is median weekly income. The data is as recorded on 1996 census night for each statistical local area (SLA), as defined by the ABS. REGIONAL DATA ANALYSIS I.1
State Gaming Authorities data The state gaming authorities data mainly includes: • the number of venues — mainly, hotels and clubs — in each region; • the number of gaming machines in each region; and • data to calculate the average annual expenditure on gaming machines per person in each region (total profit, total metered wins and net revenue). In Victoria, data was unavailable to calculate the average annual expenditure on gaming machines. Table I.1 Data sources and calculations New South Wales Victoria a Queensland South Australia Year 1997-98 1997-98 1997-98 Year ended 31 August 1999 Data sources Data Estimated average expenditure on gaming machines per person per region Department of Gaming and Racing (DGR 1999b) Number of venues per region Number of gaming machines per region Total profit on gaming machines per region (table I.6) Total profit on gaming machines divided by adult population Victorian Casino and Gaming Authority (VCGA 1998a) Number of venues per Local Government Area (LGA) Number of gaming machines per LGA (tables I.7 and I.8) na Queensland Office of Gaming Regulation (QOGR 1998b) Adult population per region Average metered win per gaming machine per region Number of venues per region Number of gaming machines per region (table I.9) Total metered wins b divided by divided by adult population South Australian Liquor and Gaming Commission Number of gaming machines per region Net revenue from gaming machines per region Net revenue from gaming machines divided by adult population na not available a Data was not available for Victoria to estimate average annual expenditure on gaming machines per person in each region. b Total metered wins is the average metered win per venue for each region multiplied by the number of venues in each region. Adjustments and calculations While there was a reasonable, but not perfect, concordance between the data sourced from the state gaming authorities and the ABS, a number of adjustments and calculations were made to the data to improve this: I.2 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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Page 135 and 136: 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: epayments were required — but mos
Page 187 and 188: Table I.2 Unweighted estimation Med
Page 189 and 190: machines. There is no statistically
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
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Table J.12 Value of annual transfer
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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
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Horner, T. and Bradfield, G. 1998,
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——, Marston, A., Singer, R., Wi
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Gambling Studies, ‘Towards 2000:
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—— 1995b, Social impacts of urb
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—— 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
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Single, E., Collins, D., Easton, B.
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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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