Who really wants to be a millionaire: estimates of risk aversion from game show data

There is a considerable variation in estimates of the degree of risk aversion in the literature. This paper analyses the behaviour of contestants in one of the most popular TV gameshows ever to estimate a CRRA model of behaviour. This gameshow has a number of features that makes it well suited for our analysis: the format is extremely straightforward, it involves no strategic decision-making, we have a large number of observations, and the prizes are cash and paid immediately, and cover a large range - up to ?1 million. Our data sources have the virtue that we are able to check the representativeness of the gameshow participants. While the game requires skill, which complicates our analysis, the structure of the game is very simple so that complex probability calculations are not required of the participants. The CRRA model is complex despite its restrictiveness because of the sequential nature of this game - answering a question correctly opens the option to hear the next question and this has a value that depends on the stage of the game and the player's view about the difficulty of subsequent questions. We use the data to estimate the degree of risk aversion and how it varies across individuals. We investigate a number of departures from this simple model including allowing the RRA parameter to vary by gender and age. Even though the model is extremely restrictive, in particular, it features a single RRA parameter we find that it fits the data across a wide range of wealth remarkably well and yields very plausible parameter values.