Overreaction in Macroeconomic Expectations

2020/09/01 by Pedro Bordalo, Nicola Gennaioli, Yueran Ma +1 · 10 citations
Decision Sciences · Economics, Econometrics and Finance · #Forecasting Techniques and Applications #Market Dynamics and Volatility #Monetary Policy and Economic Impact

paper · doi:10.1257/aer.20181219

openalex publication_date 2020/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

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)

Citations

• Implications of rational inattention
• Subjective probability: A judgment of representativeness
• Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
• Investor Psychology and Security Market Under‐ and Overreactions
• Biases in Dynamic Models with Fixed Effects
• Does the Stock Market Overreact?
• Diagnostic Expectations and Stock Returns
• The trouble with overconfidence.
• Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts

Cited by

• Investor Memory and Biased Beliefs: Evidence from the Field
• Overinference from Weak Signals and Underinference from Strong Signals
• Perceptions About Monetary Policy
• Stories, Statistics, and Memory
• Subjective Models of the Macroeconomy: Evidence From Experts and Representative Samples
• On the Identification of Diagnostic Expectations: Econometric Insights from DSGE Models
• Forward guidance and expectation formation: A narrative approach
• The purpose of an estimator is what it does: Misspecification, estimands, and over-identification
• Dynamic Non-Bayesian Persuasion
• Misspecified Bayesianism

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