DECISION COSTS AND BETTING MARKET EFFICIENCY

Abstract

In this research we examine empirically the linkage between decision costs and market efficiency in the context of racetrack betting markets. We analyze more than 10,000 horse races and demonstrate that metrics of non-optimizing behavior are inversely related to the volume of betting: we are less likely to observe evidence of non-optimizing behavior when examining data from racetracks with larger betting pools. The analysis provides empirical support for the decision-cost model in which departures from the predictions of rational economic behavior are explained in terms of the cost of non-optimizing decisions. The decision-cost model reconciles the disparate findings on the efficiency of racetrack betting markets reported in previous research.