Many experimental economists have been interested in measuring the level of risk aversion as well as the determinants of risk aversion. These studies often take place in a controlled, laboratory setting and designing an experiment which will elicit responses which are true to life is essential.
In “ Risk Aversion in the Laboratory ,” Harrison and Rutström review some of the techniques used to elicit risk aversion preferences. We will review 5 of these techniques: multiple price list (MPL), random lottery pairs (RLP), ordered lottery selection (OLS), Becker-DeGrot-Marschak (BDM) and trade-off (TO).
Multiple price list (MPL) . In this type of lottery, subjects are given a list of binary lottery choices to make all at once. The most famous example of MPL is the Holt and Laury (2002) study. MPL is probably the most widely used method to elicit risk preferences, but do suffer from the problem of framing. In the Holt & Laury study, subjects may have tended to choose a switching point in the middle of lottery list even if their actions in the real world would not have reflected this choice.
Random lottery pairs (RLP) . Under RLP, subjects face binary lottery choices in a sequence and must choose the preferred lottery. Hey and Orme (1994) used this methodology to test expected utility predictions. The experimenters’ elicited the subjects preferences over 100 pairs of lotteries, where the outcome values were fixed (£0, £10, £20, £30) but the probabilities for each outcome changed among the 100 lottery pairs.
Ordered lottery selection (OLS) . In this methodology, the subject chooses one lottery from an ordered set. For instance, Barr (2003) allowed villagers in Zimbabwe to choose from the following 50/50 lotteries: (100; 100); (90, 190); (80, 240); (60, 300); (20, 380); (0, 400). The OLS structure can help to answer questions about risk preferences, but since all lotteries are 50-50, they can not answer questions regarding higher order risk preferences (e.g., prudence, temperance). Further, this method does not allow for the analysis of any Kahneman and Tversky-style probability weighting.
Becker-DeGrot-Marschak (BDM) . In the words of Blavatsky & Köhler (2007) , “Under the BDM procedure, individuals are asked to state their minimum selling price for a risky lottery. The experimenter then draws a random number between the lowest and the highest outcome of the lottery. If the price that the individual states is lower than or equal to the drawn number, she receives the drawn number as her payoff. Otherwise she has to play the risky lottery.” The benefit of BDM is that if preferences satisfy the independence axiom, then the bid will be the individuals exact certainty equivalent. However, it assumes that individuals do not make errors and understand the fairly complex nature of the game.
Trade-off (TO) . The trade off design gives subjects choices over lotteries and these lotteries are endogenously defined in real-time by prior responses of the same subject. This can lead to a more precise measure of the certainty equivalent, but does the lotteries played will vary by subject.
With any of these experiments it is important to pay real money for the subjects answers. Otherwise, many of the results will suffer from hypothetical bias (see Camerer and Hogarth, 1999 ).