A Quantitative Analysis of Distortions in Managerial Forecasts

58 Pages Posted: 14 Jun 2018 Last revised: 21 Sep 2020

See all articles by Yueran Ma

Yueran Ma

University of Chicago - Booth School of Business

Tiziano Ropele

Bank of Italy

David Alexandre Sraer

Princeton University; University of California, Berkeley

David Thesmar

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 3 versions of this paper

Date Written: May 29, 2018

Abstract

This paper quantifies the economic costs of distortions in managerial forecasts. We match a unique managerial survey run by the Bank of Italy with administrative data on firm balance sheets and income statements. The resulting dataset allows us to observe a long panel of managerial forecast errors for a sample of firms representative of the Italian economy. We show that managerial forecast errors are positively and significantly autocorrelated. This persistence in forecast error is consistent with managerial underreaction to new information. To quantify the economic significance of this forecasting bias, we estimate a dynamic equilibrium model with heterogeneous firms and distorted expectations. The estimated model matches not only the persistence of forecast errors, but the empirical link between investment and managerial forecasts. Relative to a counterfactual with rational expectations, we find that managers exhibit large forecasting biases, which lead to significant distortions in firm-level investment. These distortions, however, imply limited loss in firm value. In general equilibrium, the estimated model leads to negligible aggregate efficiency losses from distorted forecasts.

Keywords: Expectation Formation; Misallocation; Corporate Investment

JEL Classification: D61; D84

Suggested Citation

Ma, Yueran and Ropele, Tiziano and Sraer, David Alexandre and Sraer, David Alexandre and Thesmar, David, A Quantitative Analysis of Distortions in Managerial Forecasts (May 29, 2018). Available at SSRN: https://ssrn.com/abstract=3187021

Yueran Ma

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Tiziano Ropele

Bank of Italy ( email )

Via Nazionale 91
Rome, 00184
Italy

David Alexandre Sraer (Contact Author)

Princeton University ( email )

22 Chambers Street
Princeton, NJ 08544-0708
United States

University of California, Berkeley ( email )

310 Barrows Hall
Berkeley, CA 94720
United States

David Thesmar

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
Cambridge, MA 02142
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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