University of Notre Dame
Department of Economics
3033 Jenkins Nanovic Hall
Notre Dame, IN 46556
“The Expectations-Driven Financial Accelerator” with Antonio Falato, October 2019.
This paper develops a unified quantitative account of credit cycles and their macroeconomic consequences based on information frictions in debt markets. Using a dynamic model with endogenous default, we highlight a novel “herding” mechanism whereby uninformed debt investors learn about firms’ creditworthiness from publicly-available survey information on quarter-ahead corporate profits. We show that: 1) short-term changes in expectations of corporate profits strongly forecast credit spreads and real economic aggregates over up to two years horizons; 2) credit spreads and defaults are counter-cyclical; 3) the mechanism can account quantitatively for the historically large spike in spreads during the financial crisis.
“Borrowing to Save and Investment Dynamics“, December 2018. (New version soon)
Existing literature on financial frictions argue that firms reduce investment in a crisis due to a lack of credit. However, U.S. public firms, which together accounted for 89 percent of the decline in investment during the Great Recession, experienced no drop in borrowing. Instead of investing, they borrowed to expand their stock of safe assets; that is, they borrowed to save. I model borrowing to save as an optimal portfolio choice when firms face gradually resolving uncertainty. In a quantitative general equilibrium model with heterogeneous firms, I show that this mechanism can simultaneously generate a sharp downturn and a slow recovery.
Work in Progress
“Biased Bank Expectations: Micro Evidence and Macro Consequences” with Antonio Falato. (Working paper soon)
We examine banks’ expectations about the future performance of their loan portfolios, how they are formed and whether they matter for lending decisions. We construct a novel micro dataset on bank expectations using bank-level responses to a set of special questions in the Senior Loan Officer Opinion Survey on Bank Lending Practices for an annual panel of about one hundred U.S. banks between 2006 and 2019. Our first contribution is to document stylized facts on banks’ expectations and behavioral biases, as measured by the systematic forecast errors made by the banks. Our second contribution is to quantify the macroeconomic implications of the forecasting bias, by developing a dynamic equilibrium model with distorted bank expectations.