In many experiments, particularly individual choice experiments, experimenters ask many questions to the subjects and use the random lottery incentive mechanism to give an incentive to the subjects. That is, the experimenter, at the end of the experiment, picks just one of the questions, plays out that question, and pays the subject on the basis of this one question. The idea is that subjects should separate the various questions and reply to each as if it were a separate question—in isolation from all the other questions in the experiment. This procedure is methodologically sound if the subjects behave in accordance with Expected Utility (EU) theory, since this theory says that the best procedure for the subjects is to separate the various questions. However, if there is any doubt as to whether the subjects obey EU theory, and particularly if the experiment is designed to test whether the behaviour of the subjects is in accordance with EU, this incentive mechanism is open to criticism. Indeed many referees use this argument against the research. The response that the subjects may not respect EU, yet still separate the various questions, is obviously open to objection and generally it is not clear whether this response is valid or not. There have been two direct tests of this separation hypothesis (by Starmer and Sugden (1991) and by Cubitt et al. (1998), which suggest that it is valid, but further evidence is required. This paper provides a further, stronger, test of this hypothesis: we confront the two stories—(1) that the subjects answer the various questions separately, and (2) that the subjects respond to the experiment as a whole—using experimental data from an experiment in which the random lottery incentive mechanism was used. Our analysis shows that it would appear that subjects do answer as if they were separating the questions. This should be considered reassuring for those experimenters who use the random lottery incentive mechanism.
random lottery incentive mechanismseparation hypothesisstrategiesSelten’s measure of predictive success