Overreaction in Macroeconomic Expectations

By P. Bordalo, N. Gennaioli, Yueran Ma, A. Shleifer. The American Economic Review, 2018

399 citations recorded by the source corpus.

We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts under-react relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/631b44b58022eb7d08d6a924dfc1661c6a268d9a

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Citations in the corpus

Forecasting: theory and practice (2020, background): “ties, such as mean errors and revisions. Forecaster behaviour can be characterised by the response to new information. Over or under-reaction would constitute ineﬃciency. Broer and Kohlhas (2018) and Bordalo et al. (2018) ﬁnd that agents overreact, generating a negative correlation between their for”
Monetary Policy Communications and Their Effects on Household Inflation Expectations (2018, positive): “and Bordalo et al. 2018 for a recent example). It is most closely related to recent work using randomized information treatments to characterize how agents learn and respond to new information.(4) Randomized information treatments applied to firms in New Zealand, for example, suggest that managers r”
Psychology-based Models of Asset Prices and Trading Volume (2018, methodology): “Bordalo et al. (2017) and Bordalo et al. (2018a) incorporate this belief distortion into a dynamic framework they call “diagnostic expectations.””
Exposure to Daily Price Changes and Inflation Expectations (2019, neutral): “So far, most researchers have focused on the expectations of experts, such as professional forecasters (e.g., see Coibion and Gorodnichenko (2012), Coibion and Gorodnichenko (2015a), Fuhrer (2017), and Bordalo et al. (2018)).”
Five Facts about Beliefs and Portfolios (2019, neutral): “, 2017, 2018; Glaeser and Nathanson, 2017; Adelino, Schoar and Severino, 2018a,b) as well as the role of firm expectations (e.g., Cummins, Hassett and Oliner, 2006; Bacchetta, Mertens and Van Wincoop, 2009; Coibion and Gorodnichenko, 2012; Gennaioli, Ma and Shleifer, 2016; Landier, Ma and Thesmar, 2”
Diagnostic Expectations and Stock Returns (2019, background): “…has been used to shed light on fallacies in probabilistic judgments (Gennaioli and Shleifer (2010), social stereotypes (Bordalo et al. (2016)), beliefs about gender (Bordalo et al. (2019)), credit cycles (Bordalo, Gennaioli, and Shleifer (2018)), and macroeconomic forecasts (Bordalo et al. (2018)).”