Belief Distortions and Macroeconomic Fluctuations

91 Pages Posted: 22 Jun 2020 Last revised: 20 Nov 2021

See all articles by Francesco Bianchi

Francesco Bianchi

Duke University; NBER; CEPR

Sydney C. Ludvigson

New York University - Department of Economics; National Bureau of Economic Research (NBER)

Sai Ma

Board of Governors of the Federal Reserve System

Multiple version iconThere are 2 versions of this paper

Date Written: June 2020

Abstract

This paper combines a data rich environment with a machine learning algorithm to provide new estimates of time-varying systematic expectational errors ("belief distortions") embedded in survey responses. We find that distortions are large even for professional forecasters, with all respondent-types over-weighting their own beliefs relative to publicly available information. Forecasts of inflation and GDP growth oscillate between optimism and pessimism by large margins, with biases in expectations evolving dynamically in response to cyclical shocks. The results suggest that artificial intelligence algorithms can be productively deployed to correct errors in human judgement and improve predictive accuracy.

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Suggested Citation

Bianchi, Francesco and Ludvigson, Sydney C. and Ma, Sai, Belief Distortions and Macroeconomic Fluctuations (June 2020). Available at SSRN: https://ssrn.com/abstract=3632633

Francesco Bianchi (Contact Author)

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Sydney C. Ludvigson

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Sai Ma

Board of Governors of the Federal Reserve System ( email )

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