Schedule - Parallel Session 5 - Experiments and Ambiguity 3

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.

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.