Revealed Altruism1

This paper develops a nonparametric theory of preferences over one's own and others' monetary payoffs. We introduce “more altruistic than” (MAT), a partial ordering over such preferences, and interpret it with known parametric models. We also introduce and illustrate “more generous than” (MGT), a partial ordering over opportunity sets. Several recent studies focus on two‐player extensive form games of complete information in which the first mover (FM) chooses a more or less generous opportunity set for the second mover (SM). Here reciprocity can be formalized as the assertion that an MGT choice by the FM will elicit MAT preferences in the SM. A further assertion is that the effect on preferences is stronger for acts of commission by FM than for acts of omission. We state and prove propositions on the observable consequences of these assertions. Finally, empirical support for the propositions is found in existing data from investment and dictator games, the carrot and stick game, and the Stackelberg duopoly game and in new data from Stackelberg mini‐games.     

Comparing Expressed and Revealed Preferences for Risk Reduction: Different Hazards and Question Frames

Studies often note the wide differences that exist in costs per death avoided across U.S. federal programs and regulatory contexts. This paper explores two new, related explanations for these differences. First, it argues that the patterns of revealed preferences (public allocations) may be related to public values, which are measured here through subjects' expressed preference responses to a contingent valuation survey regarding risk reduction. Subjects' expressed values are compared to actual (and proposed) costs of safety regulations for a similar set of hazards. We discover strong congruence in the ranking of expressed values and actual values. Second, the paper presents the results of a subsequent survey that investigates why the patterns observed in the first survey might occur. It suggests that one reason for the observed similarities between revealed and expressed preferences may be in how choices are framed. The paper hypothesizes that both subjects and decision makers may frame valuation decisions in the same way: as percentage changes from the reference point provided by the base rate of deaths for that hazard.     

The Dynamic Nature of Risk Perceptions After a Fatal Transit Accident

In 2009, two trains of Washington, DC's Metrorail system collided, resulting in nine deaths and 50 serious injuries. Based on a multiwave survey of Metrorail users in the months after the crash, this article reports how the accident appears to have (1) changed over time the tradeoffs among safety, speed, frequency of service, cost, and reliability that the transit users stated they were willing to make in the postaccident period and (2) altered transit users’ concerns about safety as a function of time and distance from the accident site. We employ conditional logit models to examine tradeoffs among stated preferences for system performance measures after the accident, as well as the influence that respondent characteristics of transit use, location, income, age, and gender have on these preference tradeoffs. As expected, respondents appear averse to longer headways between trains, longer travel durations, higher travel costs, a higher number of late trains, and a higher number of fatalities. The models also show evidence of higher aversion to fatalities from transit system operation among females compared to males. In addition, respondents less experienced with Metrorail travel and those with lower household incomes show higher aversion to fatalities, and this aversion increases as a subject's psychological distance from the accident site decreases. Contrary to expectations shaped by previous studies, aversion to fatalities appears to have increased between the early months after the accident and the end of the survey period, and the expected relationship between age and aversion to fatalities is not statistically significant.     

Robustness and Separation in Multidimensional Screening

A principal wishes to screen an agent along several dimensions of private information simultaneously. The agent has quasilinear preferences that are additively separable across the various components. We consider a robust version of the principal's problem, in which she knows the marginal distribution of each component of the agent's type, but does not know the joint distribution. Any mechanism is evaluated by its worst‐case expected profit, over all joint distributions consistent with the known marginals. We show that the optimum for the principal is simply to screen along each component separately. This result does not require any assumptions (such as single crossing) on the structure of preferences within each component. The proof technique involves a generalization of the concept of virtual values to arbitrary screening problems. Sample applications include monopoly pricing and a stylized dynamic taxation model.     

Identifying and Structuring the Objectives of Terrorists

The risk of terrorism is of great concern to many countries and significant resources are spent to counter this threat. A better understanding of the motivation of terrorists and their reasons for selecting certain modes and targets of attack can help improve the decisions to allocate resources in the fight against terrorism. The fundamental question addressed in this article is: “What do terrorists want?” We take the view that terrorists’ preferences for actions are based on their values and beliefs. An important missing piece in our knowledge of terrorists’ preferences is an understanding of their values. This article uses a novel approach to determine these values and state them as objectives, using principles from decision analysis and value‐focused thinking. Instead of interviewing decisionmakers and stakeholders, as would be normal in decision analysis, we extract the values of terrorists by examining their own writings and verbal statements. To illustrate the approach, we extract the values of Al‐Qaeda and structure them in terms of strategic, fundamental, and means objectives. These objectives are interrelated through a means‐ends network. This information is useful for understanding terrorists’ motivations, intent, and likely actions, as well as for developing policies to counter terrorism at its root causes.     

CAN WE INFER HOSPITAL QUALITY FROM MEDICAL GRADUATES’ RESIDENCY CHOICES?

This paper uses a novel approach to infer hospital technical quality from revealed preferences over residency programs. Specifically, we use Spanish medical graduates’ residency choices made from 1995 to 2000. We start by estimating a model of medical graduates preferences that controls for hospital, proximity, specialty, and gender effects. We interpret the coefficients on the hospital dummy variables as measures of medical graduates’ preferences over hospitals. Our results show that graduates do indeed discriminate between hospitals and that their preferences correlate with hospital‐specific covariates arguably related to hospital training quality. We then show that preferences from medical graduates are positively and statistically significantly correlated with risk‐adjusted hospital rankings based on five alternative outcome measures. Finally, we construct reputation scores for each hospital using news story counts in three media outlets and find that medical graduates’ preferences are especially valuable for inference of hospital technical quality of care as they do not simply reflect well known reputation.     

Illustration of a Method to Incorporate Preference Uncertainty in Benefit–Cost Analysis

Benefit–cost analysis is widely used to evaluate alternative courses of action that are designed to achieve policy objectives. Although many analyses take uncertainty into account, they typically only consider uncertainty about cost estimates and physical states of the world, whereas uncertainty about individual preferences, thus the benefit of policy intervention, is ignored. Here, we propose a strategy to integrate individual uncertainty about preferences into benefit–cost analysis using societal preference intervals, which are ranges of values over which it is unclear whether society as a whole should accept or reject an option. To illustrate the method, we use preferences for implementing a smart grid technology to sustain critical electricity demand during a 24‐hour regional power blackout on a hot summer weekend. Preferences were elicited from a convenience sample of residents in Allegheny County, Pennsylvania. This illustrative example shows that uncertainty in individual preferences, when aggregated to form societal preference intervals, can substantially change society's decision. We conclude with a discussion of where preference uncertainty comes from, how it might be reduced, and why incorporating unresolved preference uncertainty into benefit–cost analyses can be important.     

Preferences for One‐Shot Resolution of Uncertainty and Allais‐Type Behavior

Experimental evidence suggests that individuals are more risk averse when they perceive risk that is gradually resolved over time. We address these findings by studying a decision maker who has recursive, nonexpected utility preferences over compound lotteries. The decision maker has preferences for one‐shot resolution of uncertainty if he always prefers any compound lottery to be resolved in a single stage. We establish an equivalence between dynamic preferences for one‐shot resolution of uncertainty and static preferences that are identified with commonly observed behavior in Allais‐type experiments. The implications of this equivalence on preferences over information systems are examined. We define the gradual resolution premium and demonstrate its magnifying effect when combined with the usual risk premium.     

When Are Local Incentive Constraints Sufficient?

We study the question of whether local incentive constraints are sufficient to imply full incentive compatibility in a variety of mechanism design settings, allowing for probabilistic mechanisms. We give a unified approach that covers both continuous and discrete type spaces. On many common preference domains—including any convex domain of cardinal or ordinal preferences, single‐peaked ordinal preferences, and successive single‐crossing ordinal preferences—local incentive compatibility (suitably defined) implies full incentive compatibility. On domains of cardinal preferences that satisfy a strong nonconvexity condition, local incentive compatibility is not sufficient. Our sufficiency results hold for dominant‐strategy and Bayesian Nash solution concepts, and allow for some interdependence in preferences.     

On Monotone Recursive Preferences

We explore the set of preferences defined over temporal lotteries in an infinite horizon setting. We provide utility representations for all preferences that are both recursive and monotone. Our results indicate that the class of monotone recursive preferences includes Uzawa–Epstein preferences and risk‐sensitive preferences, but leaves aside several of the recursive models suggested by Epstein and Zin (1989) and Weil (1990). Our representation result is derived in great generality using Lundberg's (1982, 1985) work on functional equations.     

Combinatorial Voting

We study elections that simultaneously decide multiple issues, where voters have independent private values over bundles of issues. The innovation is in considering nonseparable preferences, where issues may be complements or substitutes. Voters face a political exposure problem: the optimal vote for a particular issue will depend on the resolution of the other issues. Moreover, the probabilities that the other issues will pass should be conditioned on being pivotal. We prove that equilibrium exists when distributions over values have full support or when issues are complements. We then study large elections with two issues. There exists a nonempty open set of distributions where the probability of either issue passing fails to converge to either 1 or 0 for all limit equilibria. Thus, the outcomes of large elections are not generically predictable with independent private values, despite the fact that there is no aggregate uncertainty regarding fundamentals. While the Condorcet winner is not necessarily the outcome of a multi‐issue election, we provide sufficient conditions that guarantee the implementation of the Condorcet winner.     

Dominance intensity measure within fuzzy weight oriented MAUT: An application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers' preferences, and imprecise weights are represented by trapezoidal fuzzy weights. The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights.     

Forgotten travelers: Adjustment and career implications of international business travel for expatriates

In this study, we demonstrate the importance of assessing international business travel in the context of expatriation. Based on the Job Demands-Resources theory, we suggest that engaging in international business travel is beneficial for expatriates when certain conditions are in place and detrimental when they are not. We propose that expatriates who have adequate job resources will reap the benefits of international business travel and achieve better adjustment to living and working in the host country and have greater career satisfaction. Survey results based on a sample of 161 expatriates provide support that engaging in international business travel is positively and indirectly related to expatriates' career satisfaction through expatriate adjustment when job resources are abundant, and it has a negative indirect association when resources are low. We further find that job resources play a role in the relationship between international business travel and career satisfaction primarily when the host-country culture is similar to that of the home country.     

Predicting followers' preferences for charismatic leadership: the influence of follower values and personality

Existing research on charismatic leadership focuses primarily on the traits and behaviors of charismatic leaders and the effects of charismatic leaders on their followers. One issue that has been neglected, and others, is the disposition of the followers who form charismatic relationships with their leaders. To investigate this topic, we conducted a laboratory study in which participants' values and personality dimensions were used to predict participants' preferences for charismatic leadership vs. two other leadership styles: relationship-oriented and task-oriented leadership. The results showed that values and personality were useful in predicting leadership preferences. More research is needed to gain further insights into the active role of followers in the formation of charismatic relationships.     

Stability and Preference Alignment in Matching and Coalition Formation

We study matching and coalition formation environments allowing complementarities and peer effects. Agents have preferences over coalitions, and these preferences vary with an underlying, and commonly known, state of nature. Assuming that there is substantial variability of preferences across states of nature, we show that there exists a core stable coalition structure in every state if and only if agents' preferences are pairwise‐aligned in every state. This implies that there is a stable coalition structure if agents' preferences are generated by Nash bargaining over coalitional outputs. We further show that all stability‐inducing rules for sharing outputs can be represented by a profile of agents' bargaining functions and that agents match assortatively with respect to these bargaining functions. This framework allows us to show how complementarities and peer effects overturn well known comparative statics of many‐to‐one matching.     

Are Large Differences in “Lifesaving” Costs Justified? A Psychometric Study of the Relative Value Placed on Preventing Deaths

Government actions to reduce risks to health have varied greatly in their cost per death prevented, frequently by 10-fold or even 100-fold. This research asks whether disparities of this magnitude are justified by citizens' preferences abut the relative value of reducing deaths from different hazards. Four samples were asked to rank the relative priority of preventing deaths through 8 realistic programs, each addressed to a different hazard, and then to rate how large the differences in spending should be. Subjects were not asked to give absolute values on preventing deaths and were asked only for their relative valuation of the benefits of preventing a death, not to weigh the benefits and costs or to determine an optimal spending level. We found that in all samples the median respondent valued his top-rated program 5 to 6 times more than his bottom-rated program. However, because individuals disagreed upon the relative priority for different programs, the aggregated rankings barely showed more than a 2-fold difference in the amounts that should be spent. Thus, for the important programs considered by these samples, a large variation in spending does not appear to be justified on the basis of differentials in the values placed on preventing different types of deaths. A more deliberative methodology like the one used here appears fruitful for providing insights to policymakers about preferences in this sensitive area.     

RISK AVERSION,WEALTH, AND BACKGROUND RISK

We use household survey data to construct a direct measure of absolute risk aversion based on the maximum price a consumer is willing to pay for a risky security. We relate this measure to consumer's endowments and attributes and to measures of background risk and liquidity constraints. We find that risk aversion is a decreasing function of the endowment—thus rejecting CARA preferences. We estimate the elasticity of risk aversion to consumption at about 0.7, below the unitary value predicted by CRRA utility. We also find that households' attributes are of little help in predicting their degree of risk aversion, which is characterized by massive unexplained heterogeneity. We show that the consumer's environment affects risk aversion. Individuals who are more likely to face income uncertainty or to become liquidity constrained exhibit a higher degree of absolute risk aversion, consistent with recent theories of attitudes toward risk in the presence of uninsurable risks. (JEL: D1, D8)     

Behavioral Economics and Regulatory Analysis

Behavioral economics has captured the interest of scholars and the general public by demonstrating ways in which individuals make decisions that appear irrational. While increasing attention is being focused on the implications of this research for the design of risk‐reducing policies, less attention has been paid to how it affects the economic valuation of policy consequences. This article considers the latter issue, reviewing the behavioral economics literature and discussing its implications for the conduct of benefit‐cost analysis, particularly in the context of environmental, health, and safety regulations. We explore three concerns: using estimates of willingness to pay or willingness to accept compensation for valuation, considering the psychological aspects of risk when valuing mortality‐risk reductions, and discounting future consequences. In each case, we take the perspective that analysts should avoid making judgments about whether values are “rational” or “irrational.” Instead, they should make every effort to rely on well‐designed studies, using ranges, sensitivity analysis, or probabilistic modeling to reflect uncertainty. More generally, behavioral research has led some to argue for a more paternalistic approach to policy analysis. We argue instead for continued focus on describing the preferences of those affected, while working to ensure that these preferences are based on knowledge and careful reflection.     

What Can Decision Analysis Do for Invasive Species Management?

Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.     

Choice Without Beliefs

We provide an axiomatic foundation for decision making in a complex environment. We do not assume that the decision maker has complete structural knowledge of the environment. Instead the agent knows the set of actions he can take, he formulates preferences directly on the actions, and chooses according to these preferences. On the basis of experience he modifies these preferences according to a systematic procedure. Our axioms are imposed on this procedure, rather than directly on the choice itself. The axioms consist of a group of natural structural restrictions and a group of independence axioms. Our main result is an axiomatic foundation for a set of simple adaptive learning procedures that include the replicator dynamic.