Australia's Gambling Industries - Productivity Commission

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— based on excessive expenditure — is questionable, when concentrated spending seems to be a recurrent pattern across many consumer goods. However, lotteries (and to a lesser extent scratchies) show a quite different pattern to other gambling products. They exhibit some concentration of spending — as in all consumer goods — but nothing as extreme as that applying to other gambling forms. The top 10 per cent of spenders in Australian lotteries account for just under 40 per cent of total expenditure. In contrast, such a group accounts for around 80 per cent of total outlays for wagering, gaming machines and casino table games. Furthermore, the average annual outlay of heavy lottery players (the top 10 per cent) is about $1 500, which is not prohibitive as a share of most average incomes, whereas the average spends for the top 10 per cent of spenders in modes such as gaming machines ($7 750) and wagering ($10 011) looms much larger. 2 Accordingly, while expenditure concentration is characteristic of many consumer products, it appears to be more extreme and to involve large absolute amounts in some gambling forms. Problem gamblers, as diagnosed using the SOGS, are strongly represented among heavy gamblers (figure P.2), and people with higher SOGS scores tend to spend more on average than those with lower scores (figure P.3). Problem gamblers account for about 0.4 per cent of gamblers who outlay less than $500 a year on gambling, but for around 40 per cent of those who outlay more than $4 500 annually. Of course, this does not mean that heavy spending equates with excessive spending or with problem gambling — indeed it is still true that a majority of heavy gamblers are not problem gamblers (using the SOGS criterion of 5+). P.3 Problem gambling expenditure by gambling mode Using the methodology described in box P.1, the Commission calculated the expenditure levels and shares of problem gamblers in Australia by gambling mode (table P.4). Problem gamblers figure prominently in the overall expenditure of gaming machines, wagering and ‘other’ commercial gambling, but are much less significant for lotteries and casino table games. 2 Although note that this is outlay, not player losses. Absolute values of player losses will tend to be smaller. On the other hand, these estimates have not been corrected for the sampling bias — all estimates would rise, bar lotteries, after such adjustment. P.6 GAMBLING
Figure P.2 Distribution of outlay by problem and recreational gamblers Frequency (%) 70.0 60.0 50.0 40.0 30.0 20.0 Problem gamblers Non-problem gamblers 10.0 0.0 >7000 >6500 to 7000 >6000 to 6500 >5500 to 6000 >5000 to 5500 >4500 to 5000 >4000 to 4500 >3500 to 4000 >3000 to 3500 >2500 to 3000 >2000 to 2500 >1500 to 2000 >1000 to 1500 >500 to 1000 >0 to 500 Outlay ($) a See note for above figure. Data source: PC National Gambling Survey. Figure P.3 Average annual outlays by SOGS score 30000 25000 Gross outlay ($) 20000 15000 10000 5000 0 NC 0 1 2 3 4 5 6 7 8 9 10+ SOGS score a These data are not adjusted so that they are consistent with aggregate gambling expenditure data. That would tend to increase the average spending amount, but by a variable amount for each SOGS grouping depending on the areas where the people concerned were gambling (see section P.3). NC denotes the group of non-regular gamblers who were not asked the SOGS. Data source: PC National Gambling Survey. SPENDING BY PROBLEM GAMBLERS P.7
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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
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G.3 Question by question A1 to A3
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D23 — is concerned with the mecha
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of problem gambling (eg how many ch
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CLIENT SURVEY G.9
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CLIENT SURVEY G.11
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CLIENT SURVEY G.13
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CLIENT SURVEY G.15
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CLIENT SURVEY G.17
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CLIENT SURVEY G.19
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CLIENT SURVEY G.21
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CLIENT SURVEY G.23
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CLIENT SURVEY G.25
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Problem gamblers may subsequently b
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For a subset of 856 clients in 1996
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Table H.3 Variable Logistic estimat
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Prison, South Australia’s main re
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• “Has your gambling ever led y
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elicit information on vocational, f
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This finding is consistent with the
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H.5 What crimes do problem gamblers
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Other more violent crimes such as b
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But as noted above, police statisti
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H.8 Problem gambling and loan shark
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epayments were required — but mos
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State Gaming Authorities data The s
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Table I.2 Unweighted estimation Med
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machines. There is no statistically
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Figure I.2 Expenditure on gaming ma
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Weighted results The Commission’s
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Table I.7 Summary of Victorian metr
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Table I.9 Summary of Queensland reg
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it is likely to represent the more
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Table J.1 presents the information
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suffer from some of the adverse con
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• costs of gambling counselling s
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To the extent that borrowed money i
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This fee is only taken in estates w
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• for a higher estimate, the numb
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The Commission has assumed that the
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• to estimate the income lost ove
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the Commission has used this estima
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• 336 people receiving a jail sen
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states offer up to $50 000 each for
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As indicated in table J.6, where pr
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seen as part of the informal contra
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Almost all divorce cases are uncont
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of their gambling during the period
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Suicide ideation The Commission’s
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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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SURVEY OF COUNSELLING SERVICES L.25
Page 267 and 268: SURVEY OF COUNSELLING SERVICES L.27
Page 269 and 270: SURVEY OF COUNSELLING SERVICES L.29
Page 271 and 272: Table M.1 Major forms of gambling t
Page 273 and 274: and sport development fund. In some
Page 275 and 276: Tax on keno In New South Wales, the
Page 277 and 278: Poker machines In most states, lice
Page 279 and 280: Table M3: Gaming machine taxation b
Page 281 and 282: Table M3: (continued) Hotels: Levie
Page 283 and 284: Table M4: (continued) NSW VIC QLD W
Page 285 and 286: Table M5: (continued) OTHER GAMBLIN
Page 287 and 288: N.1 Characteristics of machines of
Page 289 and 290: Table N.1 Australia, Japan, United
Page 291 and 292: Table N.2 Australia, Indiana, Conne
Page 293 and 294: The following discussion of gaming
Page 295 and 296: Canada Broadly speaking, Canada has
Page 297 and 298: Figure N.4 Japanese pachislo machin
Page 299 and 300: Winnings Progressive jackpots are p
Page 301 and 302: Bets and losses Bets and losses on
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Page 305 and 306: N.2 Market segments As with many ot
Page 307 and 308: Box N.4 Comments on market segments
Page 309 and 310: O Displacement of illegal gambling?
Page 311 and 312: survive together because they cater
Page 313 and 314: P Spending by problem gamblers The
Page 315 and 316: Table P.1 Outlays, player losses an
Page 317: Table P.3 Concentration of outlays
Page 321 and 322: Table P.4 Expenditure shares of pro
Page 323 and 324: is adjusted for biases in its estim
Page 325 and 326: ACIL (sub. D233. p. 48) claimed tha
Page 327 and 328: P.5 Estimating the expenditure shar
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Page 331 and 332: of counselling agencies is necessar
Page 333 and 334: Table Q.2 Employment status of prob
Page 335 and 336: Table Q.3 continued Study Average a
Page 337 and 338: Relationship status The greater inv
Page 339 and 340: Table Q.6 Gender of problem gambler
Page 341 and 342: The pattern of an increased feminis
Page 343 and 344: R Bankruptcy and gambling This appe
Page 345 and 346: Table R.2 Age profile of bankrupts,
Page 347 and 348: Table R.5 New bankruptcies per mill
Page 349 and 350: Figure R.2 continued Western Austra
Page 351 and 352: • The penalty has become less sev
Page 353 and 354: S State and territory gambling data
Page 355 and 356: Table S.4 Real government revenue f
Page 357 and 358: Table S.8 Real government revenue,
Page 359 and 360: Table S.12 Real government revenue
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Table S.32 Real government revenue
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Table S.36 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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