Australia's Gambling Industries - Productivity Commission

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Table Q.1 Incomes of problem gamblers Study Percentage on low income a Nature of group Location and time period Jackson et al. (1997) Jackson et al. (1999b) Elliot Stanford and Associates (1998) Dickerson, Allcock, Blaszczynski, Nicholls, Williams and Maddern (1996a) Eckhardt (1998) Relationships Australia Queensland (sub. 62) Lorenz and Politzer (1990) National Council of Welfare (1996) Gerstein et al. (1999) 48.2% had incomes below $20 000 Clients of Break per year; 27.5% had incomes Even services below $10 000. b 37.5% were on fixed incomes. c 57% reported incomes of less than $20,800 per year; and 33% were in receipt of pensions or benefits. But the income distribution of clients is similar to that of all Victorians. 57.8% earned less than $20 000 per annum; 28.3% earned less than $10 000. 33.3% of those scoring 5+ on the SOGS earned less than $20 000 and 14.8% had incomes below $10 000. 49% earned less than $20 000 and 18% less than $10 000. 37% of gambling clients had income below $10 000 and 57% were below $20 000. 27% reported incomes of less than US$10 000 and another 21.8% between US$10 000 and $20 000. 28% of household income under $25 000 cf 20% for non-problem groups Found that people earning less than US $24 000 had a 40% higher risk of being a ‘pathological’ gambler Clients of Break Even services Clients of problem gambling counselling services General population survey Clients of gambling counselling services Clients of gambling counselling services Patients of 3 Maryland problem gambling treatment centres General population General population Victoria, 1996-97 Victoria, 1997-98 South Australia, November 1996 to March/May 1998 NSW 1995 Tasmania July 1997 – Sept 1998 Break Even Gold Coast May 1993 - Oct 1998 Maryland, US, 1983–1989 Alberta Canada US 1998 a Note, however, that household income might be higher than this. b Jackson, et al. 1999a (pp. 15–16) found that problem gamblers are apparently under-represented among the lowest income group when compared with Victorians as a whole. However, the researchers emphasised that many problem gamblers did not disclose their income, and that the concepts of income used were vague and so could severely bias the results. c Fixed incomes include pensions and benefits (eg unemployment benefits). Source: See column 1 for the sources of data. Employment status Delfabbro (1998, p. 180) conjectures that the unemployed are more likely to gamble problematically because it allows them an escape from their worries and raises the possibility of a win to supplement their benefit income. WHO ARE THE PROBLEM GAMBLERS? Q.3
Table Q.2 Employment status of problem gamblers Study Link to employment status Nature of group Location and time period Jackson et al. (1997) Jackson, et al. (1999b) Abbott and Volberg (1991) Elliot Stanford and Associates (1998) Dickerson, Allcock, Blaszczynski, Nicholls, Williams and Maddern (1996a) 14.8% were unemployed (cf Victoria rate of 9.1%), 52.5% were employed 16.9% were unemployed (cf Victoria rate of 8.5%), 59.7% were employed Unemployed were over-represented among those betting on instant lotteries (18% play weekly), horses/dogs and gaming machines. One in 5 people unemployed had had a gambling problem at some time. 15.4 per cent were unemployed and 48.5% were employed. None unemployed; 64.5 per cent employed Eckhardt (1998) 10.6% unemployed and 64.7% employed Relationships Australia Queensland (sub. 62) Lorenz and Politzer (1990) Clients of Break Even services Clients of Break Even services General population Clients of problem gambling counselling services General population survey Clients of problem gambling counselling services 10.8% unemployed Clients of problem gambling counselling services 13% unemployed and 80 per cent employed. Patients of 3 Maryland problem gambling treatment centres Victoria, 1996-97 Victoria, 1997-98 New Zealand 1991 South Australia, November 1996 to March/May 1998 NSW 1995 Tasmania 1997– 98 Break Even Gold Coast May 1993–October 1998 Maryland, US, 1983–1989 Source: See column 1 for the sources of data. Q.4 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
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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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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
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
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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 and 318: Table P.3 Concentration of outlays
Page 319 and 320: Figure P.2 Distribution of outlay b
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 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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Page 377 and 378: T.3 The logistic approach The NORC
Page 379 and 380: Table T.3 Method Various estimates
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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:
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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
Page 433 and 434:
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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