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. “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, 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, George Loewenstein, and David Hagmann. “Loss Aversion and Exploration.”
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.