Bayesian markets to elicit private information

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. Bayes

Subjective Truths

__Abstract__ On the one hand, economists heavily rely on hard numbers: GDP, growth rate, and exchange rates. On the other hand, their explanations often rely on soft factors: executive confidence in the economy, consumer sentiment, and investor expectations. The hard numbers are objective, but the soft factors are subjective and depend on each individual. Economists increasingly recognize the need to study subjective factors. The first part of the lecture illustrates the key role of subjective truths in modern economics. For instance, measures of subjective well-being are now being proposed to replace or at least complement GDP. Economic policies often rely on subjective forecasting by experts. The second part of the lecture will show that even though they are subjective, the soft factors can still be studied objectively. We will see how to incentivize people to reveal their expectations about future events but also their confidence in their expectations. Finally, I will show how to make people reveal truths that are completely unverifiable

Searching for the reference point

Although reference dependence plays a central role in explaining behavior, little is known about the way that reference points are selected. This paper identifies empirically which reference point people use in decision under risk. We assume a comprehensive reference-dependent model that nests the main reference-dependent theories, including prospect theory, and that allows for isolating the reference point rule from other behavioral parameters. Our experiment involved high stakes with payoffs up to a week's salary. We used an optimal design to select the choices in the experiment and Bayesian hierarchical modeling for estimation. The most common reference points were the status quo and a security level (the maximum of the minimal outcomes of the prospects in a choice). We found little support for the use of expectations-based reference points

Signal perception and belief updating

This paper introduces a theory of signal perception to study how people update their beliefs. By allowing perceived signals to deviate from actual signals, we identify the probability that people miss or misread signals, giving indices of conservatism and confirmatory bias. In an experiment, we elicited perceived signals from choices and obtained a structural estimation of the indices. The subjects were conservative and acted as if they missed 65% of the signals they received. Also they exhibited confirmatory bias by misreading 17% of the signals contradicting their prior beliefs

Testing constant absolute and relative ambiguity aversion

Recent applications have demonstrated the crucial role of decreasing absolute ambiguity aversion in financial and saving decisions. Yet, most ambiguity models predict that ambiguity aversion remains constant when individuals become better off overall. We propose the first tests of constant absolute and relative ambiguity aversion, using simple variations of the Ellsberg paradoxes. Our tests are axiomatically founded and grounded in the theoretical literature. We implemented these tests in an experiment. Our results call for the use of ambiguity models that can accommodate decreasing aversion toward ambiguity

Web-Appendix of: The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation.

ABSTRACT. In economic decisions we often have to deal with uncertain events for which no probabilities are known. Several normative models have been proposed for such decisions. Empirical studies have usually been qualitative, or they estimated ambiguity aversion through one single number. This paper introduces the source method, a tractable method for quantitatively analyzing uncertainty empirically that can capture the richness of ambiguity attitudes. The theoretical key in our method is the distinction between different sources of uncertainty, within which subjective (choice-based) probabilities can still be defined. Source functions convert those subjective probabilities into willingness to bet. We apply our method in an experiment, where we do not commit to particular ambiguity attitudes but let the data speak

Measuring ambiguity attitude: (Extended) multiplier preferences for the American and the Dutch population

Empirical studies of ambiguity aversion often use measures that are not grounded in theory. This paper shows how a theoretically-founded measure of ambiguity aversion can be derived from Hansen and Sargent’s theory of multiplier preferences. Multiplier preferences are used in macroeconomics to capture model uncertainty. At the micro level, they have not been applied yet, because they do not permit ambiguity seeking, which is usually observed for a substantial proportion of subjects. We give a preference foundation for (extended) multiplier preferences accommodating both ambiguity aversion and ambiguity seeking and we propose a simple method to measure them using matching probabilities. We illustrate our method in two large representative samples (Dutch and American) and obtain the first micro estimates of multiplier preferences

Sadder but wiser: The Effects of Affective States and Weather on Ambiguity Attitudes

__Abstract__ Many important decisions are made without precise information about the probabilities of the outcomes. In such situations, individual ambiguity attitudes infl

Informing, simulating experience, or both: A field experiment on phishing risks

Cybersecurity cannot be ensured with mere technical solutions. Hackers often use fraudulent emails to simply ask people for their password to breach into organizations. This technique, called phishing, is a major threat for many organizations. A typical prevention measure is to inform employees but is there a better way to reduce phishing risks? Experience and feedback have often been claimed to be effective in helping people make better decisions. In a large field experiment involving more than 10,000 employees of a Dutch ministry, we tested the effect of information provision, simulated experience, and their combination to reduce the risks of falling into a phishing attack. Both approaches substantially reduced the proportion of employees giving away their password. Combining both interventions did not have a larger impact