Schedule - Parallel Session 5 - Experiments and Ambiguity 3WMG IDL03 (IDL Auditorium) - 14:00 - 15:30
Information Gaps for Risk and Ambiguity
We apply a model of preferences for information to the domain of decision making under risk and ambiguity. An uncertain prospect exposes an individual to an information gap. Gambling makes the missing information more important, attracting more attention to the information gap. To the extent that the uncertainty (or other circumstances) makes the information gap unpleasant to think about, an individual tends to be averse to risk and ambiguity. Yet in circumstances in which thinking about an information gap is pleasant, an individual may exhibit risk- and ambiguity-seeking. The model provides explanations for source preference regarding uncertainty, the comparative ignorance effect under conditions of ambiguity, aversion to compound risk, and a variety of other phenomena. We present an empirical test of one of the model’s novel predictions. Imagine a choice between a gamble and a sure thing. Deciding to play the gamble naturally focuses attention on the question: what will be the outcome of the gamble? Of course, deciding to not play the gamble does not stop an individual from paying some attention to the question but playing the gamble makes the question more important, and that brings about an increase in attention to the question. Whether this encourages risk taking or risk aversion will depend on whether thinking about the information gap is pleasurable or aversive. When thinking about the missing information is pleasurable, then the individual will be motivated to increase attention on the question, which entails betting on it. Conversely, when thinking about the missing information is aversive, the individual will prefer to not bet on it. This may help to explain why, for example, people generally prefer to bet on their home teams than on other teams, especially in comparison to a team their home team is playing against. A preference for betting on uncertainties that one likes thinking about shares much overlap with, but is distinguishable from, a preference for betting on uncertainties that one has expertise about (Heath and Tversky, 1991). Decision making involving uncertainties that are ambiguous is similar to the case with known risks, but with an additional wrinkle: with ambiguity, there are additional information gaps. In a choice between a sure thing and an ambiguous gamble, for example, a second relevant question is: what is the probability of winning with the ambiguous gamble? Again, betting on the ambiguous gamble makes this question more important and thus increases attention to it. So, desire to play the gamble will be increasing with the degree to which thinking about the gamble is pleasurable. To the extent that abstract uncertainties are not pleasurable to think about, this model provides a novel account of ambiguity aversion in Ellsberg choices.
A Brief Experiment on Attitudes Toward Ambiguous Time
Anisa Shyti; Corina Paraschiv
Many entrepreneurs and managers make business decisions based on transactions that involve cash inflows and outflows, which timing is uncertain. This paper focuses on the uncertainty aspect of the timing in which expected outcomes materialize. We isolate the effect of ambiguous time on individual preferences, and we theoretically justify the simplification of utility over time.
In this paper we report results of a field experiment with MBA students, who were assigned a term-long class project in Spring 2015 at a top European business school. Students were asked to make decisions on financing options that would provide them cash in the future to develop their term-project on a larger scale. Students faced binary options that consisted in a precise-time and a time interval, or ambiguous time, for the same cash inflow. Specifically, a precise-time financing option meant that the cash would be received at the stated future date, and an ambiguous-time option meant that the cash would be received at a future unknown date within a known time interval. Students were randomly assigned to two between-subject experimental conditions, one in which the timing of the cash inflow was determined by chance, and one in which the timing of the cash inflow was determined by the quality of the project. Students were explained that better quality projects would receive the cash inflow earlier than worse quality projects. Subsequently, students made decisions on precise-time or ambiguous-time financing options before receiving formal feedback on their projects. Two additional experimental treatments included distance from the present (i.e., near or far), and duration (i.e., short or long time intervals). Given the nature of the class project and the duration of the term (14 weeks), the time unit used in the experiment was in days.
Preliminary results show that when the timing of cash inflows depend on project’s quality, decision makers prefer ambiguous time. For short time intervals, disregarding distance from the present, decision makers are indifferent between precise or ambiguous time options, hence exhibiting ambiguity neutrality. However, for long time intervals, decision makers for whom outcomes depend on the quality of their projects, exhibit strong preferences for ambiguous time, or ambiguity seeking. Decision makers for whom outcomes are randomly determined exhibit strong aversion to ambiguous time. To summarize, decision makers for whom quality matters are most ambiguity seeking for outcomes located further from the present; whereas, decision makers in the control group are ambiguity averse, and more so for long time intervals. These findings shed light on how the feeling of control over outcomes may impact time-related decisions. Time preferences of entrepreneurs or managers and elements that influence decisions over time are under-investigated topics in current research.
Job Search Behaviors Under Risk and Ambiguity: An Experimental Test
Isabelle Vialle; May Attalah; Olivier L’Haridon
Most of the experimental literature on job search deals with decisions under risk (Braustein and Schotter, 1981, 1982, Cox and Oaxaca, 1989, 1992). Nishimura and Osaki (2004) show however that ambiguity might have non-trivial effect on search decisions. In this paper we use a laboratory experiment to study how risk and ambiguity impact search decisions. Our within-subject design is based on the standard job search model (Lippman and McCall (1976) and aims at eliciting both search durations and reservation wages. In order to explore job search behaviors under risk and ambiguity, we run two treatments that differ in the information about the probability of receiving an offer. For decisions under Risk subjects perfectly know this probability, while under Ambiguity there is an uncertainty about the probability of receiving an offer. By comparing behaviors between both treatments, we are able to determine if subjects behave differently under Ambiguity and under Risk. On average, we find subjects behave as ambiguity neutral agents, suggesting that ambiguity has not a strong impact on search decisions.
Testing Manski's Theory of Satisficing
Nuttaporn Rochanahastin; Yudistira Permana; John Hey
Way back in 1955 Herbert Simon made a call for a new kind of economics stating that: “the task is to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environment in which such organisms exist”. Since this call, many economists have tried to produce theories of ‘satisficing’ behaviour – as Simon called it – but most have failed. The trouble is that the expression ‘rational behaviour’ covers virtually all forms of behaviour, as long as it is motivated by some ‘rational’ objective function, and the decision-maker has all relevant information available to him or her. A ‘rational’ objective function is one that is not internally inconsistent, though it may not be complete. In recent years economics has started seeing theories of behaviour with incomplete preferences; these are a step in the right direction. There has also been an outburst of theoretical work on decision-making under ambiguity – which is a situation where probabilities do not exist or are not known. Some of these make the decision-makers task complicated – for example the Smooth Model of decision-making under ambiguity assumes that, while the decision-maker (DM) does not know the probabilities, he or she can specify the set of possible probabilities and can attach probabilities to each member of the set. The computational problems are enormous – but usually economics assume that the DM can solve any task, however complex. But this is not true: numerous experiments have shown that there is noise in human behavior (Caplin et al., 2011; Guth and Weiland, 2011; Reutskaja et al., 2011): that given the same problem more than once, decisions change. Is this simple error in decision-making, or is it a sign that the decision-maker cannot or does not want to find the best decision? The problem may simply be too complicated. The economist would argue that the DM realises that it is not worth thinking about the problem, and that he or she is simply trading off costs and benefits. But we have to be careful here: if we want to argue that there are costs of working out the optimal solution, we need to admit that there must also be costs associated with working out whether it is worth working out the optimal solution, and that there must be also costs associated with working out whether it is worth working out whether it is worth working out the optimal solution, and so on ad infinitum. There is no end to this infinite regression. But admitting that there are costs to thinking is a first step in the right direction. Such costs are the crucial component of a new theory advanced by Charles Manski in “Optimise, Satisfice or Choose Without Deliberation?”. In this he incorporates the first cost – the cost of thinking. It is just the first step as these costs are given. We report on an experiment testing Manski’s theory.