Journal of Economic Dynamics and Control. Volume 183, February 2026
Coauthored with Elijah Broadbent, Huberto Ennis, and Horacio Sapriza
Abstract: The provision of bank credit to firms and households affects macroeconomic performance. We use survey measures of changes in bank lending standards, disaggregated by loan category, to quantify the effect of changes in banks’ attitudes toward lending on aggregate output, inflation, and interest rates. Bank lending to businesses is particularly important for macroeconomic outcomes, with peak effects on output growth of around 30 to 40 basis points after four quarters of the initial shock. These effects depend on the stage of the business cycle and the proximity of the short-term interest rate to its effective lower bound. The effects are larger when output is growing below trend, when uncertainty is increasing or high, and when interest rates are away from the lower bound. We also find that the response of the economy to lending-standards shocks is asymmetric, with tightening shocks having larger effects on output.
Coauthored with Francisco Vazquez-Grande
Abstract: This note discusses the out-of-sample (OOS) performance of several probit models used to assess the likelihood that the U.S. economy will be in a recession within the following year.
Coauthored with Francisco Vazquez-Grande
Abstract: Yes. This paper documents the benefits of combining forecasts using weights built with non-linear models. We introduce our tree-based forecast combinations and compare them with benchmark equal weight combination as well as other nonlinear forecast weights. We find that nonlinear models can improve consistently upon the equal weight alternative–breaking the so-called ``forecast combination puzzle’’–and that our proposed methods compete well with other nonlinear methods.
Coauthored with Horacio Sapriza and Tom Zimmermann
Abstract: This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample predicted default probabilities to construct a leading indicator of non-financial corporate health. The index predicts real economic outcomes such as GDP growth and employment up to eight quarters ahead. Impulse responses validate the interpretation of the index as a measure of financial stress.