Loewenstein, George, David Hagmann, Janet Schwartz, Keith Ericson, Judd B. Kessler, Saurabh Bhargava, Jennifer Blumenthal-Barby, Thomas D’Aunno, Ben Handel, Jonathan Kolstad, David Nussbaum, Victoria Shaffer, Jonathan Skinner, Peter Ubel, & Brian J. Zikmund-Fisher. 2017. “A Behavioral Blueprint For Improving Health Care Policy.” Behavioral Science & Policy 3 (1): 53–66.
Golman, Russell, David Hagmann, and George Loewenstein. 2017. “Information Avoidance.” Journal of Economic Literature 55 (1): 96–135.
Golman, Russell, David Hagmann, and John H. Miller. 2015. “Polya’s Bees: A Model of Decentralized Decision Making.” Science Advances 1 (8), e1500253.
Loewenstein, George, Cindy Bryce, David Hagmann, and Sachin Rajpal. 2015. “Warning: You Are About to be Nudged.” Behavioral Science & Policy 1 (1), 35–42.
Hagmann, David, and Troy Tassier. 2014. “Endogenous Movement and Equilibrium Selection in Spatial Coordination Games.” Computational Economics 44 (3), 379–395.
(Drafts available upon request)
Hagmann, David and George Loewenstein. “Persuasion With Motivated Beliefs.”
Considerable research finds that people derive utility not only from consumption, but also from their beliefs about themselves and the world. Rather than dispassionately updating their views in response to new information, such belief-based utility leads people to avoid information and use other strategies to protect their existing beliefs. We present a two-stage model of persuasion in the presence of belief-protecting strategies and test it in an incentive compatible persuasion experiment. Persuaders seek to shift receivers’ numeric estimates related to emotionally charged topics, such as abortion and racial discrimination. We manipulate whether the persuader first acknowledges her own lack of certainty and whether she first has an opportunity to build rapport with the receiver, which our theory predicts should enhance persuasiveness, but should be irrelevant or may even go in the opposite direction under the standard account.
Ho, Emily, David Hagmann, and George Loewenstein. “Measuring Information Preferences.”
Advances in medical testing and widespread access to the internet have made it easier than ever to obtain information. Yet, when it comes to some of the most important decisions in life, people often choose to remain ignorant, because they may fear the implications of what they may learn. We design and validate an information preference scale to measure decision makers’ desire to obtain or avoid information that may be unpleasant, but could improve their future decisions. The scale measures information preferences in three domains that are economically, and psychologically consequential: health, consumer finance, and personal characteristics. We present tests of the scale’s reliability and validity and show that the scale predicts a real decision to obtain (or avoid) information in each of the domains. We find that many respondents prefer to remain in a state of active ignorance even when information is freely available. Moreover, we find that information preferences are a stable trait, but that preferences can differ across domains.
Hagmann, David, Emily Ho, and George Loewenstein. “Nudging Out Painful Policies.”
Nudges, like enrolling employees into 401(k) plans by default, have emerged as one of the most promising recent policy developments. They offer policymakers a tool to guide behavior and improve outcomes for many, without requiring heavy-handed interventions that could force some into options that are suboptimal for them. Nudges appear costless, preserving people’s freedom to choose differently than a (potentially misinformed) policymaker. We propose, however, that nudges can have an indirect cost. When heavy-handed and potentially painful policies may be more effective, nudges can provide a convenient excuse to avoid enacting such policies. People may be motivated to exaggerate the effectiveness of a nudge and to see it as an alternative, rather than a complement to standard economic policy. In a series of 5 studies, we show that people perceive nudges as less painful than standard policies, but also believe them to be equally or even more effective. After learning about nudges, respondents in our experiments hold a less favorable view of a corresponding standard policy and were less willing to enact the latter. We replicate our findings with alumni of a policy school, suggesting nudges may crowd out support for standard policies even among experts and those with potential influence over policies.
Hagmann, David, Jason L. Harman, and Cleotilde Gonzalez. “Wait, Wait… Don’t Tell Me: Repeated Choices With Clustered Feedback.”
When individuals make repeated choices between two lotteries without having a description of their payoffs, they have to form beliefs based on the observed outcomes of their choices. Previous research finds that choices differ consistently after learning about outcomes compared to having an objective description, an effect termed the description-experience gap. We introduce a new clustered feedback mechanism in which participants receive feedback consisting of individual outcomes of a number of choices at once, rather than observing the outcome immediately after making a decision. Presenting clustered feedback closes the description-experience gap and leads individuals to act as if they had a description available. We also use lotteries with rare outcomes and find that the description-experience gap is greatest when a high payoff is rare, and is closed by clustered feedback, but does not emerge when a high payoff is common.
Chin, Alycia, David Hagmann, and George Loewenstein. “Fear and Promise of the Unknown: Explore-Exploit Decisions in the Presence of Losses.”
In “explore-exploit” situations, decision makers must choose between exploring unknown options and exploiting known options. We study how explore-exploit decisions vary under the influence of loss aversion, predicting that (1) people will be less likely to explore if doing so can lead to losses and that (2) people will be less likely to exploit when doing so would lead to repeated losses. To examine these predictions, we use a novel computer task in which participants explore a one-dimensional environment that contains only gains or gains and losses. Across multiple studies, we find evidence for both of our predictions. Additionally, we demonstrate that loss aversion can be adaptive, leading participants in low payoff environments to higher total rewards.