D81 Criteria for Decision-Making under Risk and Uncertainty
Stochastic differential utility as the continuous-time limit of recursive utility
Frank Thomas Seifried
- We establish a convergence theorem that shows that discrete-time recursive utility, as developed by Kreps and Porteus (1978), converges to stochastic differential utility, as introduced by Dufffie and Epstein (1992), in the continuous-time limit of vanishing grid size.
Are risk preferences dynamic? : Within-subject variation in risk-taking as a function of background music
Marja Liisa Halko
- This paper investigates whether preference interactions can explain why risk preferences change over time and across contexts. We conduct an experiment in which subjects accept or reject gambles involving real money gains and losses. We introduce within-subject variation by alternating subjectively liked music and disliked music in the background. We find that favourite music increases risk-taking, and disliked music suppresses risk-taking, compared to a baseline of no music. Several theories in psychology propose mechanisms by which mood affects risktaking, but none of them fully explain our results. The results are, however, consistent with preference complementarities that extend to risk preference.
Hidden insurance in a moral hazard economy
- We consider an economy where individuals privately choose effort and trade competitively priced securities that pay off with effort-determined probability. We show that if insurance against a negative shock is sufficiently incomplete, then standard functional form restrictions ensure that individual objective functions are optimized by an effort and insurance combination that is unique and satisfies first- and second-order conditions. Modeling insurance incompleteness in terms of costly production of private insurance services, we characterize the constrained inefficiency arising in general equilibrium from competitive pricing of nonexclusive financial contracts.
Manipulating reliance on intuition reduces risk and ambiguity aversion
Jeffrey V. Butler
- Prior research suggests that those who rely on intuition rather than effortful reasoning when making decisions are less averse to risk and ambiguity. The evidence is largely correlational, however, leaving open the question of the direction of causality. In this paper, we present experimental evidence of causation running from reliance on intuition to risk and ambiguity preferences. We directly manipulate participants’ predilection to rely on intuition and find that enhancing reliance on intuition lowers the probability of being ambiguity averse by 30 percentage points and increases risk tolerance by about 30 percent in the experimental sub-population where we would a priori expect the manipulation to be successful(males).
Measuring ambiguity aversion: a systematic experimental approach
Jan Pieter Krahnen
- This paper provides a systematic analysis of individual attitudes towards ambiguity, based on laboratory experiments. The design of the analysis allows to capture individual behavior across various levels of ambiguity, ranging from low to high. Attitudes towards risk and attitudes towards ambiguity are disentangled, providing pure measures of ambiguity aversion. Ambiguity aversion is captured in several ways, i.e. as a discount factor net of a risk premium, and as an estimated parameter in a generalized utility function. We find that ambiguity aversion varies across individuals, and with the level of ambiguity, being most prominent for intermediate levels. Around one third of subjects show no aversion, one third show maximum aversion, and one third show intermediate levels of ambiguity aversion, while there is almost no ambiguity seeking. While most theoretical work on ambiguity builds on maxmin expected utility, our results provide evidence that MEU does not adequately capture individual attitudes towards ambiguity for the majority of individuals. Instead, our results support models that allow for intermediate levels of ambiguity aversion. Moreover, we find risk aversion to be statistically unrelated to ambiguity aversion on average. Taken together, the results support the view that ambiguity is an important and distinct argument in decision making under uncertainty.
Asset pricing under rational learning about rare disasters : [Version 28 Juli 2011]
- This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors’ information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the likelihood of rare disasters drop to a much more pessimistic level once a disaster has occurred. Such a shift in beliefs can trigger massive declines in price-dividend ratios. Pessimistic beliefs persist for some time. Thus, belief dynamics are a source of apparent excess volatility relative to a rational expectations benchmark. Due to the low frequency of disasters, even an infinitely-lived investor will remain uncertain about the exact probability. Our analysis is conducted in continuous time and offers closed-form solutions for asset prices. We distinguish between rational and adaptive Bayesian learning. Rational learners account for the possibility of future changes in beliefs in determining their demand for risky assets, while adaptive learners take beliefs as given. Thus, risky assets tend to be lower-valued and price-dividend ratios vary less under adaptive versus rational learning for identical priors. Keywords: beliefs, Bayesian learning, controlled diffusions and jump processes, learning about jumps, adaptive learning, rational learning. JEL classification: D83, G11, C11, D91, E21, D81, C61