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    Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, Frederik Schwerter, and Andrei Shleifer. Working Paper. “Memory and Representativeness”. Abstract
    We explore the idea that judgment by representativeness reflects the workings
    of episodic memory, especially interference. In a new laboratory experiment on cued
    recall, participants are shown two groups of images with different distributions of
    colors. We find that i) decreasing the frequency of a given color in one group significantly
    increases the recalled frequency of that color in the other group, ii) for a
    fixed set of images, different cues for the same objective distribution entail different
    interference patterns and different probabilistic assessments. Selective retrieval
    and interference may offer a foundation for the representativeness heuristic, but
    more generally for understanding the formation of probability judgments from experienced
    statistical associations.
    Bordalo, Pedro, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. Working Paper. “Diagnostic Bubbles”. Abstract
    We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with two well-known mechanisms: learning from prices and speculation (buying for resale). With diagnostic (but not with rational) expectations, these mechanisms lead to price paths exhibiting three phases: initial underreaction, followed by overshooting (the bubble), and finally a crash. With learning from prices, the model generates price extrapolation as a byproduct of fast moving beliefs about fundamentals, which lasts only as the bubble builds up. When investors speculate, even mild diagnostic distortions generate substantial bubbles.
    Bordalo, Pedro, Katie Coffman, Nicola Gennaioli, and Andrei Shleifer. 2019. “Beliefs about Gender.” American Economic Review 109 (3): 739-773. Abstract
    We conduct laboratory experiments that explore how gender stereotypes shape beliefs about ability of oneself and others in different categories of knowledge. The data reveal two patterns. First, men’s and women’s beliefs about both oneself and others exceed observed ability on average, particularly in difficult tasks. Second, overestimation of ability by both men and women varies across categories. To understand these patterns, we develop a model that separates gender stereotypes from mis-estimation of ability related to the difficulty of the task. We find that stereotypes contribute to gender gaps in self-confidence, assessments of others, and behavior in a cooperative game.
    Bordalo, Pedro, Nicola Gennaioli, Yueran Ma, and Andrei Shleifer. Working Paper. “Overreaction in Macroeconomic Expectations”. Abstract
    We examine the rationality of individual and consensus professional forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), which focuses on the predictability of forecast errors from earlier forecast revisions. We document two principal findings: forecasters typically over-react to information individual level, while consensus forecasts exhibit under-reaction. To reconcile these findings, we combine the diagnostic expectations model of belief formation from Bordalo, Gennaioli, and Shleifer (2018) with Woodford’s (2003) noisy information model of belief aggregation. The model accounts for the findings, but also yields a number of new implications related to the forward looking nature of diagnostic expectations, which we also test and confirm. Finally, we compare our model to mechanical extrapolation, rational inattention, and natural expectations.
    Bordalo, Pedro, Nicola Gennaioli, Rafael LaPorta, and Andrei Shleifer. Forthcoming. “Diagnostic Expectations and Stock Returns.” Journal of Finance. Abstract

    We revisit La Porta’s (1996) finding that returns on stocks with the most optimistic analyst long term earnings growth forecasts are substantially lower than those for stocks with the most pessimistic forecasts.  We document that this finding still holds, and present several further facts about the joint dynamics of fundamentals, expectations, and returns for these portfolios.  We explain these facts using a new model of belief formation based on a portable formalization of the representativeness heuristic. In this model, analysts forecast future fundamentals from the history of earnings growth, but they over-react to news by exaggerating the probability of states that have become objectively more likely. Intuitively, fast earnings growth predicts future Googles but not as many as analysts believe. We test predictions that distinguish this mechanism from both Bayesian learning and adaptive expectations, and find supportive evidence. A calibration of the model offers a satisfactory account of the key patterns in fundamentals, expectations, and returns.

    Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer. 2018. “Extrapolation and Bubbles.” Journal of Financial Economics 129 (2): 203-227.
    Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer. Working Paper. “Memory, Attention, and Choice”. Abstract

    Building on the textbook description of associative memory (Kahana 2012), we present a model of choice in which options cue recall of similar past experiences. Recall shapes valuation and choice in two ways. First, recalled experiences form a norm, which serves as an initial anchor for valuation. Second, salient quality and price surprises relative to the norm lead to large adjustments in valuation. The model provides a unified account of many well documented choice puzzles including experience effects, projection and attribution biases, background contrast effects, and context- dependent willingness to pay. The results suggest that well-established psychological processes – memory-based norms and attention to surprising features – are key to understanding decision-making.

    Greenwood, Robin, Andrei Shleifer, and Yang You. 2019. “Bubbles for Fama.” Journal of Financial Economics 131 (1): 20-43. Abstract

    We evaluate Eugene Fama’s claim that stock prices do not exhibit price bubbles. Based on US industry returns 1926-2014 and international sector returns 1985-2014, we present four findings: (1) Fama is correct in that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward; (2) such sharp price increases predict a substantially heightened probability of a crash; (3) attributes of the price run-up, including volatility, turnover, issuance, and the price path of the run-up can all help forecast an eventual crash and future returns; and (4) some of these characteristics can help investors earn superior returns by timing the bubble. Results hold similarly in US and international samples.

    Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, and Andrei Shleifer. 2016. “Stereotypes.” Quarterly Journal of Economics 131 (4): 1753-1794. Publisher's Version Abstract

    We present a model of stereotypes based on Kahneman and Tversky’s representativeness heuristic. A decision maker assesses a target group by overweighting its representative types, defined as the types that occur more frequently in that group than in a baseline reference group. Stereotypes formed this way contain a ‘‘kernel of truth’’: they are rooted in true differences between groups. Because stereotypes focus on differences, they cause belief distortions, particularly when groups are similar. Stereotypes are also context dependent: beliefs about a group depend on the characteristics of the reference group. In line with our predictions, beliefs in the lab about abstract groups and beliefs in the field about political groups are context dependent and distorted in the direction of representative types. JEL Codes: D03, D83, D84, C91.

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