Australia's Gambling Industries - Productivity Commission

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C.2 Consumer surplus in the gambling industries Legalising gambling is equivalent to the introduction of a new good or service. Once the price has been set (in a competitive market this would be determined by the costs of production), the area under the (compensated) demand schedule above that price is the consumer surplus resulting from the introduction of the new product. Consumers have received this benefit by shifting consumption to gambling and away from less preferred goods and services. The key information needed to estimate consumer surplus in the gambling industry comprises: • estimates of the price and income elasticities of the demand for gambling; • the significance of gambling expenditure in consumers’ total spending (budget shares); and • information on current consumption of gambling — quantity and price. Estimates of price elasticities There is a paucity of up-to-date estimates of the price elasticity of gambling, and Australian estimates are even more scarce. There are a number of reasons for this, notably the difficulty of making an accurate measure from the data available. In Australia, as in other countries, access to gambling has been heavily restricted. The large changes in the quantity of gambling products purchased have been driven primarily by changes in regulations rather than changes in price. Changes in market shares between different forms of gambling are largely a result of the sequencing of the deregulation process, rather than changes in the relative prices of gambling products offered. In Australia, the decline in the average price of gambling that has been associated with the rapid rise in consumption is a result of the sequencing of liberalisation, with high priced forms of gambling such as lotteries being introduced before lower priced forms such as gaming machines and casinos. The <strong>Commission</strong> has come across a range of elasticity estimates in the literature, which are presented in table C.1. C.4 GAMBLING
Table C.1 Elasticities of demand for different types of gambling Author Period Area Preferred price elasticity Horse racing Suits (1979) 1949-71 24 US states -1.36 to -1.82 Suits (1979) 1974 Nevada -1.64 Gruen (1976) 1940-69 New York City -1.57 Morgan and Vasche (1979) 1958-78 California -1.48 Berl (1997) New Zealand -0.7 Bookmakers Suits (1979) 1974-75 Nevada -1.64 Sports betting Suits (1979) 1974-75 Nevada -2.17 Lotteries Clotfelter and Cook (1990) -2.55 (lotto) Clotfelter and Cook (1990) -3.05 (numbers game) Farrel and Walker, 1998, 1997 UK -1.55 to -2.6 Berl, (1997) (Lotto and New Zealand -1.054 Instant Kiwi) Access Economics (1998) Tattslotto - low turnover Australia -2.19 Tattslotto - high turnover Australia -0.24 Ozlotto Australia -0.2 to -0.8 Powerball Australia -0.03 to -0.2 Other Swan (1992) All gambling NSW -1.6 Poker machines NSW -1.7 Casino NSW -1.9 Berl (1997) (EGMs and casino) New Zealand -0.8 While there is some variability in the estimates of the price elasticity of gambling, most studies indicate that the demand for gambling is quite sensitive to changes in price. The <strong>Commission</strong>, nevertheless, finds it difficult to believe that they provide an accurate picture of the price sensitivity of demand for gambling. The main reasons for suggesting that the literature overstates the price sensitivity of demand for gambling are: • price (the odds of winning) is difficult for gamblers to observe, particularly for low probability games such as lotteries; • there seems to be little substitution between various forms of gambling, indicating that consumers do not have abundant alternatives if prices rise; and • gambling has been significantly deregulated over the last two decades, both in Australia and in other countries. It is difficult to disentangle the effects of price changes, which are typically falling as availability and competition increases, ESTIMATING CONSUMER SURPLUS C.5
Page 1 and 2: Australia’s Gambling Industries I
Page 3: Contents of other volumes Volume 1
Page 6 and 7: Australian Capital Territory Federa
Page 8 and 9: Tasmania Wrest Point Casino New Zea
Page 10 and 11: Marianne James Prof Jan McMillen Pe
Page 12 and 13: Canberra, 30 November 1998 Senator
Page 14 and 15: Sydney, 16-17 September 1999 Rev Fr
Page 16 and 17: N Ward 28 Evelyn Jago 29 Territory
Page 18 and 19: Australian Hotels Association (SA)
Page 20 and 21: Women’s Health West 176 Norfolk I
Page 22 and 23: BetSafe Group - Paul Symond Consult
Page 24 and 25: B Participation in gambling: data t
Page 26 and 27: Table B.2 Participation in gambling
Page 28 and 29: Table B.4 Participation in gambling
Page 30 and 31: product in excess of the price paid
Page 34 and 35: from increased consumption resultin
Page 36 and 37: Figure C.2 Tax and consumer surplus
Page 38 and 39: Table C.3 Price elasticities of dem
Page 40 and 41: Figure C.3 Consumer surplus for pro
Page 42 and 43: Box C.1 continued (e) That part of
Page 44 and 45: Table C.4 continued Wagering Lotter
Page 46 and 47: s n = share of gambling expenditure
Page 48 and 49: Figure C.6 Demand for gambling by p
Page 50 and 51: • the triangular area ’g’ whi
Page 52 and 53: The Commission’s treatment falls
Page 54 and 55: Box C.4 Explaining the lack of vari
Page 56 and 57: demand may become elastic, as peopl
Page 58 and 59: There are a number possible explana
Page 60 and 61: • Firstly, there has been extraor
Page 62 and 63: E Gambling in indigenous communitie
Page 64 and 65: The pattern of institutionally-base
Page 66 and 67: chase the “miracles” offered by
Page 68 and 69: F National Gambling Survey F.1 Intr
Page 70 and 71: F.2 The questionnaire Development o
Page 72 and 73: The use of this sampling approach m
Page 74 and 75: Box F.1 List of gambling activities
Page 76 and 77: • Big spending regular or less fr
Page 78 and 79: Questions asked of all respondents
Page 80 and 81: 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
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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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