We study the effect of democratization on stock market liquidity across Spanish political regimes between 1914 and 1936. We use press news related to mass mobilization in favor of political and redistributive reforms to build a monthly index of political uncertainty, and test its impact on different measures of stock liquidity based on daily data for the Madrid Stock Exchange. Our findings suggest that shifts in political uncertainty decreased trading and increased its price impact after the transition to democracy in 1931, but not in the socio-political mobilization that shook the monarchic regime during World War I and its aftermath. The results are robust to controls for other sources of political, economic and international uncertainty. Our evidence suggests that potential challenges to the socio-economic status quo became more credible after the regime change of 1931 and increased the perceived cost of democratization for wealthy elites. This generated a situation of radical uncertainty about future asset returns, leading to a persistent deterioration of investor participation and market liquidity. Contemporary financial chronicles support this interpretation.

We demonstrate how the standard usage of the random incentive system in ambiguity experiments eliciting certainty and probability equivalents might not be incentive compatible if the decision-maker is ambiguity averse. We propose a slight modification of the procedure in which the randomization takes place before decisions are made and the state is realized, and prove that if subjects evaluate the experimental environment in that way (first-risk, second-uncertainty), incentive compatibility may be restored.

We present an experimental design where uncertainty is generated from the advice of experts with conflicts of interest. In this experiment clients are faced with a variant of a multi-armed bandit problem with a random end-time. On the known arm (the “task screen”), clients can earn a certain payment per completion of a decoding task. However, clients may also opt for the unknown arm where they earn an uncertain amount if they end the experiment on this “expert screen”. The amount is uncertain to the clients because the value is being communicated through an “expert” with conflicted incentives. A control session provides for direct transmission of the value to the clients. Our results show that ambiguity aversion is alive-and-well in this environment. Also, when we vary the wage rate on the known arm we find that higher opportunity cost clients are less likely to heed the advice of conflicted experts.

The consequences of most economic decisions are uncertain; they are conditional on events with unknown probabilities that decision makers evaluate based on their beliefs. In addition to consequences and beliefs, the context that generates events—the source of uncertainty—can also impact preferences, a pattern called source dependence. Despite its importance, there is currently no definition of source dependence that allows for comparisons across individuals and sources. This paper presents a tractable definition of source dependence by introducing a function that matches the subjective probabilities of events generated by two sources. It also presents methods for estimating such functions from a limited number of observations that are compatible with commonly-used choice-based approaches for separating attitudes from beliefs. As an illustration, we implement these methods on three datasets, including two original experiments, and show that they consistently capture clear, albeit heterogeneous, patterns of source dependence between natural sources. Our approach provides a framework for future research to explore how source dependence varies across individuals and situations.

Law enforcement officials face numerous decisions regarding their enforcement choices. One important decision, that is often controversial, is the amount of knowledge that law enforcement distributes to the community regarding their policing strategies. Assuming the goal is to minimize criminal activity (alternatively, maximize citation rates), our theoretical analysis suggests that agencies should reveal (shroud) their resource allocation if criminals are uncertainty seeking, and shroud (reveal) their allocation if criminals are uncertainty averse. We run a laboratory experiment to test our theoretical framework, and find that enforcement behavior is approximately optimal given the observed non-expected utility uncertainty preferences of criminals.

We report a series of experiments investigating the influence of feeling lucky or unlucky on people’s choice of known-risk or ambiguous options using the traditional Ellsberg Urns decision-making task. We induced a state of feeling lucky or unlucky in subjects by using a rigged wheel-of-fortune game, which just missed either the bankrupt or the jackpot outcome. In the first experiment a large reversal of the usual ambiguity aversion effect was shown, indicating that feeling lucky made subjects significantly more ambiguity seeking than usual. However, this effect failed to replicate in five refined and larger follow-up experiments. Thus we conclude that there is no evidence that feeling lucky reliably influences ambiguity aversion. Men were less ambiguity averse than women when there were potential gains to be had, but there were no gender differences when the task was negatively framed in terms of losses.

This research explores the preference for playing order in games in which each ofseveral players draws a random event (e.g., a ball from an urn), with andwithout replacement after each draw. Three studies show that people tend toprefer to draw early regardless of whether the game is with or withoutreplacement, although the expected probability of winning is the sameirrespective of the draw order. The reasons for preferring earlier draws differdepending on the game type. For games without replacement, the biased preferencefor earlier draws is related to multiple motivational factors such as aversionto uncertainty, ambiguity, and uncontrollability. Game valence also affects draworder preference through the misestimation of winning probabilities: people tendto prefer earlier draws in a gain-dominant game (i.e., a higher probability ofwinning) but prefer later draws in a loss-dominant game (i.e., a higherprobability of losing). For games with replacement, preference for earlier drawsis mainly explained by uncertainty aversion, with little bias in probabilityestimations.

Ambiguity aversion has been widely observed in individuals’ judgments. Using scenarios that are typical in decision analysis, we investigate ambiguity aversion for pairs of individuals. We examine risky and cautious shifts from individuals’ original judgments to their judgments when they are paired up in dyads.

In our experiment the participants were first asked to specify individually their willingness-to-pay for six monetary gambles. They were then paired at random into dyads, and were asked to specify their willingness-to-pay amount for the same gambles. The dyad’s willingness-to-pay amount was to be shared equally by the two individuals. Of the six gambles in our experiment, one involved no ambiguity and the remaining five involved different degrees of ambiguity. We found that dyads exhibited risk aversion as well as ambiguity aversion. The majority of the dyads exhibited a cautious shift in the face of ambiguity, stating a smaller willingness-to-pay than the two individuals’ average. Our study thus confirms the persistence of ambiguity aversion in a group setting and demonstrates the predominance of cautious shifts for dyads.

This study examined framing effects in decisions concerning public health. Tversky and Kahneman’s famous Asian Disease Problem served as experimental paradigm. Subjects chose between a sure and a risky option either presented as gains (saving lives) or as losses (dying). The amount of risk varied in terms of different probabilities. The number of affected people was either small (low need) or large (high need). Additionally, the decisions were linked to three different types of diseases (unusual infection, AIDS, leukemia). We also implemented two different time constraints during which the subjects had to give a response. Finally, we tested a within-subject design. The data analysis assuming a linear mixed effects model revealed significant effects of framing, probabilities, and need. Furthermore, the type of disease and time constraints were moderating the framing effect. Across the different diseases, framing effects were amplified when decision time was short.

We study an intertemporal consumption and portfolio choice problem under Knightian uncertainty in which agent’s preferences exhibit local intertemporal substitution. We also allow for market frictions in the sense that the pricing functional is nonlinear. We prove existence and uniqueness of the optimal consumption plan, and we derive a set of sufficient first-order conditions for optimality. With the help of a backward equation, we are able to determine the structure of optimal consumption plans. We obtain explicit solutions in a stationary setting in which the financial market has different risk premia for short and long positions.

Effective altruism (EA) requires that when we donate to charity, we maximize the beneficial impact of our donations. While we are in broad sympathy with EA, we raise a practical problem for EA, which is that there is a crucial empirical presupposition implicit in its charity assessment methods which is false in many contexts. This is the presupposition that the magnitude of the benefits (or harms) generated by some charity vary continuously in the scale of the intervention performed. We characterize a wide class of cases where this assumption fails, and then draw out the normative implications of this fact.

Low probability risks create challenges for individual decisions and potential pressures for government regulation. This article reports original survey evidence regarding the public’s perception and valuation of water-related risks from plastic bottles with bisphenol A, residues in drinking water of the herbicide atrazine, and trace amounts of prescription drugs in water. People who believe that they face high water-related risks generally believe that the risks apply and, given that belief, are willing to pay more to limit the risk. However, the expressed willingness to pay for risk reductions is inordinately high even among those who are unsure of whether they are even exposed to the risk, and therefore may not be reliable as values for the actual benefits.

This paper presents analytical representations for an optimal insurance contract under distortion risk measure and in the presence of model uncertainty. We incorporate ambiguity aversion and distortion risk measure through the model of Robert and Therond [(2014) ASTIN Bulletin: The Journal of the IAA, 44(2), 277–302.] as per the framework of Klibanoff et al. [(2005) A smooth model of decision making under ambiguity. Econometrica, 73(6), 1849–1892.]. Explicit optimal insurance indemnity functions are derived when the decision maker (DM) applies Value-at-Risk as risk measure and is ambiguous about the loss distribution. Our results show that: (1) under model uncertainty, ambiguity aversion results in a distorted probability distribution over the set of possible models with a bias in favor of the model which yields a larger risk; (2) a more ambiguity-averse DM would demand more insurance coverage; (3) for a given budget, uncertainties about the loss distribution result in higher risk level for the DM.

We determine the optimal robust strategy of an individual who seeks to maximize the (penalized) probability of reaching a bequest goal when she is uncertain about the drift of the risky asset and her hazard rate of mortality. We assume the individual can invest in a Black–Scholes market. We solve two optimization problems with ambiguity. The first is to maximize the penalized probability of reaching a bequest goal without life insurance in the market. In the second problem, in addition to investing in the financial market, the individual is allowed to purchase term life insurance to help her reach her bequest goal. As the individual becomes more ambiguity averse concerning the drift of the risky asset, she becomes more conservative with her investment strategy. Also, as she becomes more ambiguity averse about her hazard rate of mortality, numerical work indicates she is more likely to buy life insurance when the ambiguity towards the return of the risky asset is not too large.

What value should we put on our chances of obtaining a good? This paper argues that, contrary to the widely accepted theory of von Neumann and Morgenstern, the value of a chance of some good G may be a non-linear function of the value of G. In particular, chances may have diminishing marginal utility, a property that is termed chance uncertainty aversion. The hypothesis that agents are averse to uncertainy about chances explains a pattern of preferences often observed in the Ellsberg paradox. While these preferences have typically been taken to refute Bayesian decision theory, it is shown that chance risk aversion is perfectly compatible with it.

We consider the class of concave distortion risk measures to study how choice is influenced by the decision-maker's attitude to risk and provide comparative statics results. We also assume ambiguity about the probability distribution of the risk and consider a framework à la Klibanoff, Marinacci and Mukerji (2005; A smooth model of decision making under ambiguity. Econometrica, 73, 1849–1892) to study the value of information that resolves ambiguity. We show that this value increases with greater ambiguity, with greater ambiguity aversion, and in some cases with greater risk aversion. Finally, we examine whether a more risk-averse and a more ambiguity-averse individual will invest in more effort to shift his initial risk distribution to a better target distribution.

Recent developments of neuroimaging technology enable us to investigate the brain network implicated in economical decision making (Glimcher et al. 2004; Camerer 2008). One of the fascinating topic is “ambiguity aversion” where people tend to avoid unknown options as demonstrated by Ellsberg paradox. Although “ambiguity aversion” has been consistently observed in a variety of situations, uncertainty due to incomplete knowledge can be resolved by obtaining missing information, and people explore the ambiguous options as well.

Here, we review a number of neuroimaging studies on “ambiguity aversion” and associated works. It has been shown that the affective OFC and the cognitive prefrontal cortex play a crucial role in decision making under uncertainty. We discuss what kinds of cognitive function are involved in the decision making process by overviewing neuroimaing studies on higher cognitive processes in general including exploratory behavior.

In this article, we focus on two types of “aversion” which we deem essential aspects of the notion of trust: betrayal aversion (social) and ambiguity aversion (a special case of aversion to uncertainty). Based on trust-games studies in experimental economics and neuroeconomics, our main goal is to assess the conceptual, behavioral and neurobiological connections between betrayal and ambiguity aversions.

From a social and individual psychological point of view the bottom line of our trusting behavior could be our general aversion to ambiguous signals. We approach social trust in the terms of a phenomenon based on uncertainty aversion. Specifically, a reduction of the perceived uncertainty of a social interaction tends to build up a trusting climate conducive to trade by decreasing betrayal aversion. We hypothesize that betrayal aversion and ambiguity aversion bear such a negative correlation.

Focusing on this potential negative correlation our approach clearly differs from more positive accounts of trust centred on altruism.