Current Papers
Measuring Information Preferences
(with David Hagmann and George Loewenstein)
Revise and Resubmit at Management Science
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 fear what they may learn. We design and validate an information preference scale to measure an individual's 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 psychologically and materially 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, as well as decisions from unrelated domains. We find that across settings, many respondents prefer to remain in a state of active ignorance even when information is freely available, and that information preferences are a stable trait but that an individual's preference for information can differ across domains. We also find that an individual's preferences for information may affect others: in a medical decision-making context, when caregivers of cancer patients score high on avoidance, the patient they care for are less likely to have an AD.
Look at the scale here.
The Good is the Enemy of the Best: The Hidden Cost of Soft Paternalism
(with David Hagmann and George Loewenstein)
Under Review at Nature Climate Change
‘Nudges,’ like enrolling consumers into renewable energy 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 virtually 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 painful policies may be needed, nudges can provide the promise of a lower cost ‘quick fix,’ undermining support for more effective policies. In a series of five studies, we show that people perceive nudges as less painful (but, mistakenly, as equally effective) alternatives to standard policies. When nudges are introduced as options, they diminish support for more effective standard policies. We replicate our findings with alumni of a policy school, suggesting that this effect generalizes to experts including those who report influencing public policies.
Not all carbon dioxide emissions scenarios are equally likely: A subjective expert assessment
(with David Budescu, Valentina Bosetti, Klaus Keller, and Detlef van Vuuren)
Under Review at Journal of Operations Research
Climate researchers use carbon dioxide emissions scenarios to explore alternative climate futures, potential impacts and implications of mitigation and adaptation policies. Users often seek information about the uncertainty surrounding these emission scenarios (e.g., range or relative probability), but experts typically do not provide formal probabilistic interpretations. Without such specifications, users often pick a small subset of emission scenarios and/or assume that all scenarios are equally likely. We present probabilistic judgments of experts assessing the distribution of 2100 emissions under a business-as-usual and a policy scenario. We obtain the judgments through a method that relies only on relative pairwise comparisons of various ranges of emissions. We contrast these judgments with the emission projections ranges derived from the Shared Socio-economic Pathways (SSPs) and a recent multi-model comparison producing probabilistic emission scenarios. There is wide variability between individual experts, but they do not assign equal probabilities for the emission ranges of the SSPs. Differences on long-term emissions probabilities between expert estimates and model-based calculations may result from various factors including model restrictions, a coverage of a wider set of factors by experts, but also group think and inability to appreciate long-term processes. The results highlight the importance of employing multiple diverse methods.
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