Aurélien Baillon

Relative concave utility for risk and ambiguity

This paper presents a general technique for comparing the concavity of different utility functions when probabilities need not be known. It generalizes: (a) Yaariʼs comparisons of risk aversion by not requiring identical beliefs; (b) Kreps and Porteusʼ information-timing preference by not requiring known probabilities; (c) Klibanoff, Marinacci, and Mukerjiʼs smooth ambiguity aversion by not using subjective probabilities (which are not directly observable) and by not committing to (violations of) dynamic decision principles; (d) comparative smooth ambiguity aversion by not requiring identical second-order subjective probabilities. Our technique completely isolates the empirical meaning of utility. It thus sheds new light on the descriptive appropriateness of utility to model risk and ambiguity attitudes.

A Tailor-Made Test of Intransitive Choice

This paper reports a new test of intransitive choice using individual measurements of regret-and similarity-based intransitive models of choice under uncertainty. Our test is tailor-made and uses subject-specific stimuli. Despite these features, we observed only a few intransitivities. A possible explanation for the poor predictive performance of intransitive choice models is that they only allow for interactions between acts. They exclude within-act interactions by retaining the assumption that preferences are separable over states of nature. Prospect theory, which relaxes separability but retains transitivity, predicted choices better. Our data suggest that descriptively realistic models must allow for within-act interactions but may retain transitivity.

Prince: An Improved Method for Measuring Incentivized Preferences

This paper introduces the Prince incentive system for measuring preferences. Prince clarifies consequences of decisions and incentive compatibility of experimental choice questions to subjects. It combines the efficiency and precision of matching with the improved clarity and validity of choice questions. It helps distinguish between (a) genuine deviations from classical economic theories (such as the endowment effect) and (b) preference anomalies due to fallible measurements (such as preference reversals). Prince avoids the opaqueness in Becker-DeGroot Marschak and strategic behavior in adaptive experiments. It helps reducing violations of isolation in the random incentive system. Using Prince we shed new light on willingness to accept and the major components of decision making under uncertainty: utilities, subjective beliefs, and ambiguity attitudes.

Prudence With Respect To Ambiguity

Under expected utility, prudence is equivalent to a positive third derivative of utility and plays a crucial role in precautionary saving behaviour. Eeckhoudt and Schlesinger (2006) proposed behavioural definitions of prudence and of higher order risk preferences. The present article proposes a similar definition for prudence with respect to ambiguity, i.e. situations in which objective probabilities are not available. Implications for several ambiguity models are derived. Ambiguity prudence is implied by Hansen and Sargent’s (2001) multiplier preferences, empirically correlates with financial behaviour and plays a key role in prevention behaviour.

Combining imprecise or conflicting probability judgments: A choice-based study

Sources of uncertainty appear to affect attitude towards ambiguity. For instance, when two advisors agree on a range of probabilities and, when they disagree - one advisor predicting the upper bound of the range while the other predicts the lower bound of the range †decision-makers might have different beliefs about the risk although in both case the mean probability is the same. This study draws upon prospect theory and ambiguity research to empirically test how sources of uncertainty affect decision-makers†beliefs. It contrasts revealed beliefs †the precise probability leading to the same choice as an uncertain probability forecast †with judged beliefs †decision-makers†best estimate of the probability of the risk. It also equips beliefs with two properties - pessimism and likelihood sensitivity†to allow them to vary as a function of the source of uncertainty. Two experiments compare beliefs across sources of uncertainty and across elicitation methods (judged vs. revealed beliefs). Findings support the predictions that the source of ambiguity matters in particular for low and high probability events and that revealed and judged beliefs differ.

Measuring higher order ambiguity preferences

We report the results from an experiment designed to measure attitudes towards ambiguity beyond ambiguity aversion. In particular, we implement recently-proposed model-free preference conditions of ambiguity prudence and ambiguity temperance. Ambiguity prudence has been shown to play an important role in precautionary behavior and the mere presence of ambiguity averse agents in markets. We observe that the majority of individuals’ decisions are consistent with ambiguity aversion, ambiguity prudence and ambiguity temperance. This finding confirms the prediction of many popular (specifications of) ambiguity models and has important implications for models of prevention behavior.

Bayesian markets to elicit private information

Significance People’s private information can be revealed by the way in which they trade specifically designed assets in a new type of market. People trade an asset whose value is the proportion of affirmative answers to a question. Their trading position then reveals their own answer to the question. In Bayesian markets, people can be rewarded for telling the truth even when the truth is not verifiable. Bayesian markets are simpler and more transparent than alternative methods, avoiding the measurements of metabeliefs about others and prior beliefs. Financial markets reveal what investors think about the future, and prediction markets are used to forecast election results. Could markets also encourage people to reveal private information, such as subjective judgments (e.g., “Are you satisfied with your life?”) or unverifiable facts? This paper shows how to design such markets, called Bayesian markets. People trade an asset whose value represents the proportion of affirmative answers to a question. Their trading position then reveals their own answer to the question. The results of this paper are based on a Bayesian setup in which people use their private information (their “type”) as a signal. Hence, beliefs about others’ types are correlated with one’s own type. Bayesian markets transform this correlation into a mechanism that rewards truth telling. These markets avoid two complications of alternative methods: they need no knowledge of prior information and no elicitation of metabeliefs regarding others’ signals.

Sadder But Wiser: The Effects of Affective States and Weather on Ambiguity Attitudes

Many important decisions are made without precise information about the probabilities of the outcomes. In such situations, individual ambiguity attitudes influence decision making. The present study identifies affective states as a transient cause of ambiguity attitudes. We conducted two random-assignment, incentive-compatible laboratory experiments, varying subjects’ affective states. We find that sadness induces choices that are closer to ambiguity-neutral attitudes compared with the joy, fear, and control groups, where decision makers deviate more from payoff-maximizing behaviors and are more susceptible to likelihood insensitivity. We also find a similar pattern in a representative population sample where cloudy weather conditions on the day of the survey - a proxy for sad affect - correlate with more ambiguity-neutral attitudes. Our results may help explain re al-world phenomena such as financial markets that react to regular fluctuations in weather conditions.