We provide evidence of a powerful barrier to social learning: people are much less sensitive to information others discover compared to equally-relevant information they discover themselves. In a series of incentivized lab experiments, we ask participants to guess the color composition of balls in an urn after drawing balls with replacement. Participants' guesses are substantially less sensitive to draws made by another player compared to draws made themselves. This result holds when others' signals must be learned through discussion, when they are perfectly communicated by the experimenter, and even when participants see their teammate drawing balls from the urn with their own eyes. We find a crucial role for  taking some action to generate one's `own' information, and rule out distrust, confusion, errors in probabilistic thinking, up-front inattention and imperfect recall as channels. 

We develop a model of belief formation where normatively irrelevant cues influence which states come to mind. Beliefs depend on representativeness—the cue’s similarity to a hypotheses relative to its alternative—and resonance—its ability to evoke many states. We experimentally validate the model using subjective similarity judgments, demonstrating that beliefs shift systematically with measured resonance and representativeness. Applying our framework to standard consumption-savings and risky investment problems, we show cue-based beliefs can organize diverse behavioral phenomena, including experience effects, projection bias, present bias, uninformative advertising, and portfolio under-diversification, as well as generate novel predictions about their scope and magnitude.

We rely on memory to form beliefs, but we also frequently revisit memories in conversation and private reflection. I show experimentally that such rehearsal of past experiences generates systematic belief biases. Participants are given a set of experiences and then randomized to have conversations about a subset of them, either ones that reflect well or poorly on them. Such rehearsal has large effects on which of the original experiences participants can recall a week later. Crucially, participants appear naive about rehearsal effects: they take what they remember at face value when later incentivized to form accurate beliefs about the full set of original experiences. Rehearsal therefore distorts not only future recall but also future beliefs. Participants also make rehearsal choices seemingly without regard to their later distortionary effects. Intrinsic preferences for thinking about certain experiences instead drive rehearsal choices and therefore belief biases: in particular, a preference to reflect on positive experiences unintentionally generates a positivity bias in future recall and beliefs. This mechanism provides a new non-strategic channel through which overly optimistic beliefs can arise and generates novel predictions in a range of economic domains.

Economists often estimate preferences by looking how demand for a option changes as its attributes change or as beliefs about them change in response to information. I show in a multi-attribute induced-preference experiment that this method can be substantially biased due to differential inattention. Attention is systematically distorted at baseline, with participants reacting much more to some attributes than others. Further, attention is highly malleable: information telling participants about the value of a desirable attribute—even when the information is already known, transparently redundant, and explicitly randomly assigned—greatly increases attention to the attribute it describes and distracts from other attributes. It also boosts average demand for the good, implying that inattention takes the form of neglect rather than shrinkage toward a prior. These results combine to imply that information experiments with passive control groups can be greatly misleading about preferences and can even have the wrong sign: in my experiment, reducing overoptimism about an attribute nonetheless boosts demand for its associated good. I show, both theoretically and experimentally, that active control-group experiments yield preference estimates with the correct sign but potentially very biased magnitudes. Finally I introduce a novel paradigm—parallel active control-group experiments (PACEs)—that can solve this problem: PACEs yield unbiased estimates of preferences under an equal induced-attention assumption, which is testable (and satisfied) in my experiment.

Note: This replaces a previous draft titled "Information, Attention, and Persuasion."

Do spouses pool useful information and learn from each other when they have incentives to do so? In an experiment with married couples in India, we vary whether individuals discover information themselves or must instead learn via a discussion about what their spouse discovered. Women treat their own and their husband’s information the same. In contrast, men respond half as much to information discovered by their wife, even when it is perfectly communicated. When paired with strangers, both men and women heavily discount their partner’s information relative to their own. We thus provide evidence of a gender difference in social learning (only) in the household.

We investigate the role of information frictions in the US labor market using a new nationally representative panel dataset on individuals' labor market expectations and realizations. We find that expectations about future job offers are, on average, highly predictive of actual outcomes. Despite their predictive power, however, deviations of ex post realizations from ex ante expectations are often sizable. The panel aspect of the data allows us to study how individuals update their labor market expectations in response to such shocks. We find a strong response: an individual who receives a job offer one dollar above her expectation subsequently adjusts her expectations upward by $0.47. The updating patterns we document are, on the whole, inconsistent with Bayesian updating. We embed the empirical evidence on expectations and learning into a model of search on- and off- the job with learning, and show that it is far better able to fit the data on reservation wages relative to a model that assumes complete information. The estimated model indicates that workers would have lower employment transition responses to changes in the value of unemployment through higher unemployment benefits than in a complete information model, suggesting that assuming workers have complete information can bias estimates of the predictions of government interventions. We use the framework to gauge the welfare costs of information frictions which arise because individuals make uninformed job acceptance decisions and find that the costs due to information frictions are sizable, but are largely mitigated by the presence of learning.

We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis by attending “bottom up” to its salient features while neglecting other, potentially more relevant, ones. Only the statistics associated with salient features are used, others are neglected. The model unifies biases in judgments about i.i.d. draws, such as the Gambler’s Fallacy and insensitivity to sample size, with biases in inference such as under- and overreaction and insensitivity to the weight of evidence. The model makes predictions about how changes in the salience of specific features should jointly shape the prevalence of these biases and measured attention to features, but also create entirely new biases. We test and confirm these predictions experimentally. Bottom-up attention to features emerges as a unifying framework for biases conventionally explained using a variety of stable heuristics or distortions of the Bayes rule.

There are teacher shortages in the U.S. and around the world. In a three-year field experiment with a large teacher placement program, Teach For America (TFA), Coffman, Conlon, Featherstone, and Kessler (2019) finds that providing upfront liquidity to prospective teachers in financial need dramatically increases the rate at which they start teaching through TFA. In this paper, we combine TFA administrative data, survey data, and publicly available data (e.g., LinkedIn profiles) to extend those results. We follow individuals for a few years post treatment and find that providing upfront liquidity not only increases the rate that financially constrained individuals join TFA but also increases the rate that they complete the full two years of teaching. Further, providing liquidity to those who need it increases their likelihood of being teachers at all—not just through TFA—through at least two years.

I test, in a field experiment at a flagship state university in the US, whether providing college students salary information can affect their choices of major and classes. I find that undergraduates are substantially misinformed about mean salaries by major. On average, students in my sample underestimate mean salaries, but there is also large heterogeneity in beliefs across individuals. I also find that providing information to correct these errors has a large impact on students' choices; students in the treatment group were nine percentage points (16%) more likely to major in a field about which they received information.

Can access to a few hundred dollars of liquidity affect the career choice of a recent college graduate? In a three-year field experiment with Teach For America (TFA), a prestigious teacher placement program, we randomly increase the financial packages offered to nearly 7,300 potential teachers who requested support for the transition into teaching. The first two years of the experiment reveal that while most applicants do not respond to a marginal $600 of grants or loans, those in the worst financial position respond by joining TFA at higher rates. We continue the experiment into the third year and self-replicate our results. For the highest need applicants, an extra $600 in loans, $600 in grants, and $1,200 in grants increase the likelihood of joining TFA by 12.2, 11.4, and 17.1 percentage points (or 20.0%, 18.7%, and 28.1%), respectively. Additional grant and loan dollars are equally effective, suggesting a liquidity mechanism. A follow-up survey bolsters the liquidity story and also shows that those pulled into teaching would have otherwise worked in private sector firms.

We study behavior in an information cascades setting where previous buyers of the product leave noisy but informative ratings of the product. Although this increases the amount of public information available, Yoon (2015, working paper) shows that ratings can actually increase the frequency of cascades in which buyers do not purchase even though the product is of high quality. This occurs because non-buyers do not leave ratings. Although we find some evidence roughly in line with the theory, those results are swamped by a strong tendency for subjects to purchase even when public information suggests they should not.

I argue that there could be observational evidence for absolute motion. My argument employs a spatial analogue of Shoemaker's classic ‘global freeze’ thought experiment, wherein he imagines a world whose inhabitants would seem to have strong evidence that a period of time without change had occurred. The inhabitants of my own imagined world, I claim, would have strong evidence that everything in the universe had moved the same distance in the same direction and, thus, strong evidence for absolute motion. This conclusion seems to pose a problem for spatial relationists insofar as they cannot account for absolute motion.