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Expectations and Macro-Finance

Paper Session

Saturday, Jan. 8, 2022 10:00 AM - 12:00 PM (EST)

Hosted By: American Economic Association
  • Chair: Emi Nakamura, University of California-Berkeley

Learning about the Long Run

Leland Farmer
,
University of Virginia
Emi Nakamura
,
University of California-Berkeley
Jon Steinsson
,
University of California-Berkeley

Abstract

Forecasts of professional forecasters are anomalous: they are biased, forecast errors are autocorrelated, forecast revisions predict forecast errors, etc. Sticky or noisy information models seem like unlikely explanations for these anomalies: professional forecasters pay attention constantly and have precise knowledge of the data in question. We propose that these anomalies arise because professional forecasters don’t know the model that generates the data. We show that Bayesian agents learning about hard-to-learn features of the data generating process (low frequency behavior) generate all the prominent anomalies emphasized in the literature. We show this for two applications: professional forecasts of nominal interest rates for the sample period 1980-2019 and CBO forecasts of GDP growth for the sample period 1976-2019. Our learning model for interest rates also provides an explanation for deviations from the expectations hypothesis of the term structure that does not rely on time-variation in risk premia.

The Profit-Credit Cycle

Bjorn Richter
,
Pompeu Fabra University
Kaspar Zimmermann
,
Leibniz Institute for Financial Research

Abstract

This paper shows that increasing bank profitability is associated with higher medium-term crisis risk, in particular with banking panics, and declining GDP growth in a long-run panel of advanced economies. To explain these findings, we link bank profitability to the credit cycle. An increase in profitability of the banking sector predicts rising credit-to-GDP ratios and the start of a credit boom. We decompose bank profitability into its sources and uses to study the channels behind this ``profit-credit cycle’’ in more detail. The analysis supports a supply side view of the credit cycle and aligns with recent behavioral credit cycle models.

Expectations and Bank Lending

Yueran Ma
,
University of Chicago
Teodora Paligorova
,
Federal Reserve Board
José-Luis Peydró
,
Imperial College London

Abstract

We study the properties and the impact of lenders' expectations using a new dataset on banks' economic projections about all MSAs in the US, reported annually for normal and downside scenarios. By combining these projections with comprehensive information on bank lending, we document several findings. First, banks' expectations about economic conditions under normal and downside scenarios have different determinants (e.g., opposite loading on MSA outcomes in the Great Recession). Second, expectations at a given point in time display substantial dispersion, across banks for the same MSA and across MSAs for the same bank. Third, firms have lower loan growth when their banks are more pessimistic about the downside scenario. The results hold with firm-year fixed effects: for the same firm in a given year, there is less lending from more pessimistic banks. Lenders' pessimism is also associated with higher interest rates, which further indicate reductions in credit supply. Moreover, there are negative real effects on firm-level total borrowing and capital expenditures, especially among firms with limited sources of financing, and on MSA-level output growth. Finally, banks that were more pessimistic about the downside pre-COVID have fewer past due loans after the pandemic (stronger balance sheets), but continue to lend less due to persistent pessimism.

Robust Inattentive Discrete Choice

Lars Peter Hansen
,
University of Chicago

Abstract

We introduce robustness to the rational inattention model with Shannon mutual information costs in a discrete choice setting when the decision maker is concerned about model misspecification/ambiguity. We provide necessary and sufficient conditions for the robust solution and develop numerical methods to solve it. We show that the decision maker slants their beliefs pessimistically toward worse outcomes. As a result, their choice behavior can be qualitatively different from that in the standard rational inattention model with risk aversion. We apply our model to some alternative consumer or investment problems to show how robustness considerations alter solutions to rational inattention problems.

Discussant(s)
Sydney Ludvigson
,
New York University
Gabriel Chodorow-Reich
,
Harvard University
Stefano Giglio
,
Yale University
Monika Piazzesi
,
Stanford University
JEL Classifications
  • E0 - General
  • C1 - Econometric and Statistical Methods and Methodology: General