Competition and Monopoly in the Market for Pari-mutuel Bets - a theoretical Approach

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Herbert Walther

Abstract

An intertemporal state dependent expected utility model (generating S-shaped probability weighting by incorporating anticipated flows of utility from elation and disappointment) is used as a framework for analyzing the demand for various gambles. The analysis is extended to compare pari-mutuel bets under competitive and monopolistic conditions. The following conclusions can be drawn: (1) A monopoly fosters the `skeweness' of the pari-mutual bet: In equilibrium, the wager and the demand for probability to win are lower, while the wager per unit of probability to win and the prize are higher. (3) If prize expectations are endogenous, rollovers might be a necessary device to prevent instability. (4) Rational gamblers will be indifferent between `wager tax' and `bank holder' type methods of raising monopoly profits.I am grateful for helpful comments received from the participants at the `Conference on Gambling and Prediction Markets', organized by `Economica' and held at UCLA Riverside (20.-22 May 2007).

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References

Anderhub, V., Gneezy, U., Güth, W. and Vogt, B. (1998). On the interaction of risk and time preferences: An experimental study. German Economic Review, 2, 239-253.

Beenstock, M. and Haitovsky, Y. (2001). Lottomania and other anomalies in the market for lotto. Journal of Economic Psychology, 22, 721-744.

Bleichrodt. H. and Pinto, J.L. (2000). A parameter-free elicitation of the probability weighting function in medical decision making. Management Science, 46, 1485-1496.

Brickman, P., Coates, D., and Janoff-Bulman, R. (1968). Lottery winners and accident victims: Is happiness relative? Journal of Personality and Social Psychology, 36, 917-27.

Clotfelter, C.T. and Cook, P. J., (1990). On the economics of state lotteries. Journal of Economic Perspectives, 4, 105-119.

Conlisk, J., (1993). The utility of gambling. Journal of Risk and Uncertainty, 6, 225-275.

Cook, P.J. and Clotfelter, C.T., (1993). The peculiar scale economies of lotto. American Economic Review, 83, 634-643.

Farrel, L., Morgenroth, E. and Walker, I. (1999). A time series analysis of U.K. lottery sales: Long and short-run price elasticities. Oxford Bulletin of Economics and Statistics, 61, 513-526.

Gilbert, D., Wilson, T.D., Pinel, E.C., Blumberg, St.J. and Wheatley, T.P., (1998). Immune neglect: A source of durability bias in affective forecasting. Journal of Personality and Social Psychology, 57, 617-638.

Fehr-Duda, H., de Gennaro M. and Schubert, R., 2006. Gender, financial risk, and probability. Theory and Decision, 60, 283-313.

Forrest, D. Gulley, O.D., and Simmons, R. (2000a). Testing for rational expectations in the UK national lottery. Applied Economics, 32, 315-326.

Forrest, D. Gulley, O.D., and Simmons, R. (2000b). Elasticity of demand for UK national lottery tickets. National Tax Journal, 53, 852-863

Forrest, D., Simmons, R. and Chesters, N. (2002). Buying a dream: alternative models of demand for lotto. Economic Inquiry, 40, 485-496.

Gul, F. (1991). A theory of disappointment aversion. Econometrica, 59, 667-686.

Gonzales, R. and Wu, G., (1999). On the shape of the probability weighting function. Cognitive Psychology, 38, 129-166.

Harbaugh, W.T., Krause, K., Vesterlund, L. (2002). Risk attitudes of children and adults: Choices over small and large probability gains and losses. Experimental Economics, 5, 53-84.

Lattimore, P.K., Joanna, K. and Witte, A. D. (1992). The influence of probability on risky choice: A parametric examination. Journal of Economic Behavior and Organization, 17, pp. 377-400.

Paton, D. Siegel, D. S., Williams, L.V. (2004). Taxation and the demand for gambling: New evidence from the United Kingdom. National Tax Journal, 57, pp 847-861.

Paton, D. Siegel, D. Vaughan Williams, L.V. (2002). A policy response to the E-commerce revolution: The case of betting taxation in the UK. Economic Journal, 112, 296-314.

Prelec, D. (1998). The probability weighting function. Econometrica, 66, 497-527.

Quiggin, J. (1982). A theory of anticipated utility. Journal of Economic Behavior and Organization, 3, 323-343.

Quiggin, J. (1991). On the optimal design of lotteries. Economica, 58, 1-16.

Quiggin, J. (1993). Generalized expected Utility Theory: The Rank-dependent Model. London: Kluwer.

Sprowls, C.R., (1970). On the terms of the New York State Lottery. National Tax Journal, 48, 61-70.

Scoggins, J.F., (1995). The lotto and the expected net revenue. National Tax Journal, 48, 61-70.

Starmer, C. (2000). Developments in non-expected utility theory. Journal of Economic Literature, 38 (2), 332-383.

Tversky, A. and Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of Uncertainty. Journal of Risk and Uncertainty, 5, 297-323.

Walker, I. and Young, J. (2001). An economist's guide to lottery design. The Economic Journal, 111, 700-722.

Walther, H. (2003). Normal randomness expected utility, time preference and emotional distortions. Journal of Economic Behavior and Organization, 52, 253-266.