Presentations: Banco Central de Chile (2023); FINEST (2023); Summer Workshop on Money, Banking, Payments, and Finance - Poster Session (Federal Reserve Board, 2022)*; FMA European Conference (2022); 12th Financial Markets and Corporate Governance Conference (2022)*; 2022 Annual Meeting of the Swiss Society for Financial Market Research (2022)*; Wharton-INSEAD 11th Doctoral Consortium (2022)*, 20th Annual FDIC/JFRS Banking Research Conference Poster Session*, Collegio Carlo Alberto 14th PhD Workshop in Economics*, Federal Reserve Bank of Philadelphia (2019), Wharton (2018)
* presentation by a coauthor
Abstract: We study the role of lenders' ability to collect and process information in financial contracting. Using a large sample of corporate loans, we analyze how banks' industry specialization affects the use of covenants and the outcomes of covenant violations among public U.S. firms. Lenders specialized in the borrower's industry impose less restrictive financial covenants, provide more customized loan terms, and reduce the investment drop following a covenant breach without harming firms' performance. Our results suggest that banks' industry expertise improves contracting efficiency through both the design and enforcement of financial contracts.
Abstract: We propose a new approach for predicting corporate default probabilities and for conducting scenario analyses by combining firm-level and macro time series data. We apply a local projection approach to a simple logit framework and bridge the gap between micro data on firms, for which no scenario is available, and macroeconomic variables, for which the forecaster instead has a scenario. We apply this model to an out-of-sample exercise, estimating it with data through the end of 2017 and forecasting corporate defaults over the following three years. We compute two sets of projections, the first based on the realized values of the macroeconomic time series (baseline), and the second conditional on a scenario that simulates a worsening in the macroeconomic environment comparable to the one observed during the European sovereign debt crisis (adverse). The baseline forecast closely matches the actual corporate debt default rate; under the adverse scenario, the default rate is similar to the one actually recorded in Italy during the sovereign debt crisis. We also run two exercises that make use of the granular forecasts of the corporate default probabilities. First, we assess which sectors are more vulnerable under each of the previous two scenarios (baseline and adverse). Second, we assume that the economy shifts from the baseline to the adverse scenario and construct transition matrices across different risk classes, showing which sectors are more exposed to the shift.
Presentations: EEA (2024)*; IAAE (2024)*; Stockholm School of Economics(2023), Workshop Banca d’Italia EIEF on Financial Intermediation (2023); Universidad Pompeu Fabra (2023)*; University of Colorado, Boulder (2023)
* presentation by a coauthor
Abstract: We present a simple model of a credit market in which firms borrow from multiple banks and credit relationships are simultaneous and interdependent. In this environment, financial and real shocks induce credit reallocation across more and less affected lenders and borrowers, propagating through the network of credit relationships. We show that the interdependence introduces a bias in the standard estimates of the effect of shocks on credit relationships. Moreover, we show that firm fixed effects do not solve the issue, may magnify the problem, and can be biased as well. We propose a novel model that nests commonly used ones, uses the same information set, accounts for and quantifies spillover effects among credit relationships. We document its properties with Monte Carlo simulations and apply it to real credit register data. Evidence from the empirical application suggests that estimates not accounting for spillovers are indeed highly biased.
Presentations: 6th Associazione per la Storia Economica Workshop (2021), Bank of Italy (2021)
Abstract: Due to a dearth of data, nineteenth century lending to sovereign borrowers was a blind date. We argue this is the reason for collateral pledges found in contemporary lending covenants, which enabled not execution, but the production of reliable fiscal data. Lawyers injected collateral clauses in sovereign debt covenants to permit credible disclosure of hard-to-access tax data. The study foregrounds the importance of big law firms as financial intermediaries and information producers. It also contributes a new view on the role played by contracts in sovereign debt.
Presentations: ESCB Third Research Cluster Workshop on Financial Stability, Macroprudential Regulation and Microprudential Supervision (2022), Chicago Financial Institutions Conference (2020 - cancelled due to COVID-19 emergency), Fourth ECB Macroprudential Policy and Research Conference (2019), Wharton (2019), University of Pennsylvania (2017, 2019), Banca d’Italia (2017, 2019)
Abstract: We study the effect on credit relationships of the Small and Medium Enterprises Supporting Factor (SME-SF), a regulatory risk weight reduction on small loans to SMEs. Employing a regression discontinuity design and matched bank-firm data from Italy, we find that a 1 percent drop in capital requirements causes an average 13 basis points reduction in the cost of credit. Moreover, with a novel measure of bank regulatory capital scarcity, we show that the drop is larger for banks facing tighter constraints. Furthermore, the drop is larger for firms with low switching costs, while the sharp assignment rule may have led to the rationing of marginal borrowers. Such findings indicate that the entire distribution of firms and banks' characteristics plays a crucial role in determining the impact of regulatory capital changes.
[Old version] Presentations: IBEFA Young Economist Seminar Series, Ventotene Workshop in Macroeconomics (2022), Ownership, Governance, Management & Firm Performance Conference (2020), University of Pennsylvania (2018, 2019)
Abstract: This study explores the hypothesis that age-dependent credit frictions influence the selection, growth, and productivity of firms in Italy. Motivated by the disproportionate presence of older CEOs and their preferential access to credit, the authors develop a general equilibrium life-cycle model calibrated to rich administrative data. The framework incorporates heterogeneity in managerial age, tenure, and financial constraints to examine how these factors shape firm dynamics and capital allocation. Preliminary results suggest that such frictions may contribute to misallocation and reduced aggregate efficiency.