Mohammed Abdellaoui

Experienced vs. Described Uncertainty: Do We Need Two Prospect Theory Specifications?

This paper reports on the results of an experimental elicitation at the individual level of all prospect theory components (i.e., utility, loss aversion, and weighting functions) in two decision contexts: situations where alternatives are described as probability distributions and situations where the decision maker must experience unknown probability distributions through sampling before choice. For description-based decisions, our results are fully consistent with prospect theorys empirical findings under risk. Furthermore, no significant differences are detected across contexts as regards utility and loss aversion. Whereas decision weights exhibit similar qualitative properties across contexts typically found under prospect theory, our data suggest that, for gains at least, the subjective treatment of uncertainty in experience-based and description-based decisions is significantly different. More specifically, we observe a less pronounced overweighting of small probabilities and a more pronounced underweighting of moderate and high probabilities for experience-based decisions. On the contrary, for losses, no significant differences were observed in the evaluation of prospects across contexts. This paper was accepted by George Wu, decision analysis.

Risk Preferences at Different Time Periods: An Experimental Investigation

Intertemporal decision making under risk involves two dimensions: time preferences and risk preferences. This paper focuses on the impact of time on risk preferences, independent of the intertemporal trade-off of outcomes, i.e., time preferences. It reports the results of an experimental study that examines how delayed resolution and payment of risky options influence individual choice. We used a simple experimental design based on the comparison of two-outcome monetary lotteries with the same delay. Raw data clearly reveal that subjects become more risk tolerant for delayed lotteries. Assuming a prospect theory--like model under risk, we analyze the impact of time on utility and decision weights, independent of time preferences. We show that the subjective treatment of outcomes (i.e., utility) is not significantly affected by time. In fact, the impact of time is completely absorbed by the probability weighting function. The effect of time on risk preferences was found to generate probabilistic optimism resulting in a higher risk tolerance for delayed lotteries. This paper was accepted by Teck Ho, decision analysis.

Eliciting Prospect Theory When Consequences Are Measured in Time Units: “Time Is Not Money”

We elicited the prospect theory components utility, probability weighting, and loss aversion when consequences are expressed as the time dedicated to a specific task or activity. A similar elicitation was performed for monetary consequences to allow an across-attribute time/money comparison of the elicited components at the individual level. We obtained less concave utility and smaller loss aversion for time than for money. Moreover, while the probability weighting was predominantly inverse S-shaped for both attributes, it was less sensitive to probabilities and more elevated for time than for money. This finding implies more optimism for gains and more pessimism for losses. This paper was accepted by Peter Wakker, decision analysis.

Experiments on Compound Risk in Relation to Simple Risk and to Ambiguity

We conduct experiments measuring individual behavior under compound risk, simple risk, and ambiguity. We focus on 1 treatment of compound risks relative to simple risks and 2 the relationship between compound risk attitudes and ambiguity attitudes. We find that compound risks are valued differently than corresponding reduced simple risks. These differences measure compound risk attitudes. These attitudes display more aversion as the reduced probability of the winning event increases. Like Halevy [Halevy Y 2007 Ellsberg revisited: An experimental study. Econometrica 75:503-536], we find an association between compound risk reduction and ambiguity neutrality. However, in contrast to the almost perfect identification in Halevys data, we find a substantially weaker relation in both directions. First, a majority of our ambiguity-neutral subjects fail to reduce compound risk. Second, almost a quarter of our subjects who reduce compound risk are nonneutral to ambiguity. All of the latter come from the more quantitatively sophisticated part of our subject pool. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1953 . This paper was accepted by Peter Wakker, decision analysis.

The risk-structure dependence effect:Experimenting with an eye to decision-aiding

In this paper, we aim at obtaining, from an experimental design in decision makingunder risk, richer and more appropriate information for management scientists involved indecision7dash;aiding. We design a method of direct elicitation of individual indifference curvesin the Marschak Machina triangle (i.e., the set of all probability distributions over threefixed outcomes). Our results show that indifference curves clearly take quite different typesof shape according to their location within the triangle, i.e. that preferences under risk fundamentallydepend on the risk-structure (as defined in the paper) faced by the decision maker.Furthermore, the risk-structure dependence effect explains the indecisive results of previousexperimental/econometric studies trying to rank different models according to theirdescriptive power.

The “Closing In” Method: An Experimental Tool to Investigate Individual Choice Patterns under Risk

In view of the considerable evidence of systematic violations of expected utility by individual subjects, a number of alternative models generalizing expected utility have been developed. As P.Fishburn put it once [1988], we have entered “a new era” in the domain of decision under risk, but “we shall have to wait and see” during the “time of shakedown and sifting” ahead of us, i.e. until one or possibly several of the models put forward until now can attract a clear consensus. Most of these models weaken the independence axiom. But some of them retain some linearity properties, like Chew’s weighted utility theory [1983] or Fishburn’s skew-symmetric bilinear utility theory [1988]. Machina provided a quite general frame of reference, by dispensing altogether with the independence axiom and allowing one to envision different alternative hypotheses — among which his Hypothesis II [1982] is only one possibility. Other models emphasize the idea that decumulative probability distributions straightforwardly undergo a (necessarily nonlinear) cognitive transformation, like Quiggin [1982], Yaari [1987], Allais [1988], Segal [1989], Wakker [1993].

Rational Choice under Uncertainty

As the standard theory of rational choice under uncertainty, expected utility represents a key building block of the economic theory. This rational choice theory has the advantage of resting on solid axiomatic foundations. The present chapter reviews these foundations from normative and descriptive point of views. Then, some of the most promising generalizations of expected utility are reviewed.

How Consistent Are Probability Tradeoffs in Individual Preferences under Risk

Experimental research has shown that preference functionals which describe individual choices under risk vary according to which particular type of lottery individuals have to consider. A « risk-structure » can thus be defined as a subset of prospects sufficiently ‘close’ from each other to trigger the same procedural search from the individual and thus to be described by the same preference functional. In a Marschak-Machina triangle, they are subsets of the triangle with a given indifference field in each of them. Four such risk-structures can be shown to emerge from experiments and be roughly stylized. These results seem to be fairly robust with respect to the protocol and the hypotheses used (Abdellaoui and Munier, 1994,1998). They provide experimental evidence and some potentially significant frame of reference to theories based on lottery dependent preferences (Becker and Sarin, 1987,1989) or, more generally, on local utility preferences (Machina, 1982). According to these results, it would be surprising that a given estimate of a known decision model could accommodate observations scattered throughout the whole Marschak-Machina triangle. With such a sample of data, necessarily mediocre results would thus emerge from econometric testing of any model. This is certainly not rejected by the results of such econometric testing (Hey and Orme, 1994, Harless and Camerer, 1994).