University of Notre Dame
Department of Economics
3033 Jenkins Nanovic Hall
Notre Dame, IN 46556

Curriculum Vitae

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Working Papers

Borrowing to Save and Investment Dynamics”. Revise & Resubmit, Review of Economic Studies

During the U.S. Great Recession, investment declined more among firms whose indebtedness increased. Instead of investing, they increased their leverage and expanded 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, balancing the desire to invest with the need to prevent default. Embedding this into a quantitative general equilibrium model with heterogeneous firms, I show that this mechanism can simultaneously generate a sharp downturn and a slow recovery in response to a combination of first- and second-moment shocks.

Credit Markets, Learning, and the Business Cycle” with Antonio Falato.

We argue that learning from noisy information is an important propagation mechanism for understanding credit and business cycles. First, we show that revisions of corporate profit expectations in survey data forecast changes in credit spreads and investment up to two years ahead, both in the aggregate and at the firm level. Second, we interpret these findings in a dynamic model with default risk and asymmetric information, whereby lenders are uninformed about firms’ creditworthiness and optimally learn from a noisy public signal. We show that: 1) the model can match the size of the credit risk premium even with risk-neutral lenders whose subjective default risk of the firm is consistently larger than the historically realized default risk; 2) the model generates counter-cyclical spreads and defaults, in sharp contrast to the counterfactual prediction of standard models with full information; 3) the mechanism can account quantitatively for the long-lasting widening in spreads and contraction in aggregate investment during the 2007-09 financial crisis.


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.