Welcome! I am an Assistant Professor of Economics at the University of Alabama.
I work on behavioral economics, experimental economics, and behavioral finance, with a special focus on the sources and consequences of bounded rationality and belief biases. My CV is here.
Email: qfan5@ua.edu
We study how the construction and transmission of narratives—interpretations that explain observed data—systematically distort belief formation. In a dynamic environment where signals are generated by a potentially evolving state, we show that popular, well-fitting narratives tend to overfit the data and thereby push beliefs toward greater extremeness and volatility. We test this prediction in a controlled experiment that directly compares beliefs formed with and without exposure to a singular, endogenously constructed narrative. Participants exposed to such narratives form substantially more extreme beliefs, overreact to recent data, and exhibit more volatile belief movements over time. These results identify a mechanism through which narrative-based reasoning induces overreaction to news—one that likely matters broadly given the central role of narratives in economic communication.
I design a novel experimental paradigm to document and understand how making choices over a variable distorts agents’ mental models of the data-generating process. Participants learn from observational data and then manipulate a randomly assigned variable—their choice variable—to potentially affect a payoff-relevant outcome. I directly elicit their mental mod- els and find robust evidence of Choice-induced Model Distortion: participants’ models are systematically biased toward including their choice variable relative to other comparable variables, even when the choice variable is entirely irrelevant. Using experimental treatments that isolate different stages of the decision process, I decompose this effect into distinct mechanisms, finding that it arises through both deliberation over choices and the act of choosing itself.
Why is in-kind aid a prominent feature of welfare systems? We present a lab-in-the-field experiment involving members of the general U.S. population and SNAP recipients. After documenting a widespread desire to limit recipients’ choices, we quantify the relative importance of (i) welfarist motives, (ii) utility or disutility derived from curtailing another’s autonomy, and (iii) absolutist attitudes concerning the appropriate form of aid. Choices primarily reflect the two non-welfarist motives. Because people systematically misperceive recipient preferences, their interventions are more restrictive than they intend. Interventionist preferences and non-welfarist motives are more pronounced among the political right, particularly when recipients are black.
Evidence from the laboratory and the field has uncovered both underreaction and overreaction to new information. We provide new experimental evidence on the underlying mechanisms of under- and overreaction by comparing how people make inferences and revise forecasts in the same information environment. Participants underreact to signals when inferring about underlying states, but overreact to the same signals when revising forecasts about future outcomes—a phenomenon we term “the inference-forecast gap.” We show that this gap is largely driven by different simplifying heuristics used in the two tasks. Additional treatments suggest that the choice of heuristics is affected by the similarity between statistics in the information environment and the statistic elicited by the belief-updating problem.
We design an experiment to study the role of motivated reasoning in correlation neglect. Participants receive potentially redundant signals about either an ego-relevant state—their IQ test performance—or an ego-irrelevant state. A simple hypothesis based on motivated reasoning predicts asymmetric updating about signal redundancy and about the focal state only in the treatment with ego-relevance. We find qualified support for our hypothesis: participants generally underappreciate the extent to which identical signals are more likely to come from the same source (and thus contain redundant information), but the bias is significantly stronger for ego-favorable signals than for ego-unfavorable signals. This asymmetric effect disappears in the treatment where the focal state is ego-irrelevant. These results suggest that individuals may neglect the correlation between desirable signals to sustain motivated beliefs. However, the asymmetric updating effect on signal redundancy is not quantitatively large enough to generate significant asymmetric updating about the ego-relevant state (own IQ test performance).