Welcome! I am a senior economist in the Industrial Output Section at the Federal Reserve Board of Governors in Washington, D.C. My research and policy work leverages cutting-edge AI and natural language processing tools to quantify hard-to-measure economic phenomena—from firm-level uncertainty and AI adoption to supply chain bottlenecks and bank lending risks—delivering precise, real-time economic indicators and policy-relevant insights critical for economists, policymakers, and market participants. My research has appeared in leading academic journals including Management Science, the Journal of International Economics, and the Journal of Financial Services Research.
Management Science, 2025
We use the ECB's Asset Quality Review as a natural experiment, showing that banks temporarily reduce risk by shifting portfolios toward safer assets for supervisory compliance, but revert afterward, causing persistent negative real effects, particularly harming high-risk firms.
View PaperJournal of International Economics, 2022
We examine how the simultaneous implementation of capital controls and domestic reserve requirements in Colombia during a credit boom effectively curtailed banks' risky lending practices, and show that these policies complementarily strengthened the transmission of monetary policy to credit supply by limiting foreign currency arbitrage and domestic funding, ultimately reducing financial vulnerability.
View PaperR&R at the Review of Financial Studies
We examine Colombia's foreign-debt capital controls using firm-level data, finding that these controls limit risky foreign borrowing during booms, thus safeguarding exports and employment during crises, especially benefiting financially constrained firms.
View PaperFinance and Economics Discussion Series, 2024
We study how trademark similarity among banks significantly increases deposit withdrawals following bank failures, particularly when media coverage is extensive, highlighting the underestimated role of trademarks in financial contagion and banking stability.
View PaperJournal of Financial Services Research, 2021
I use NLP methods on bank earnings calls to measure idiosyncratic uncertainty to show that higher uncertainty significantly reduces lending and increases liquidity, particularly during volatile economic conditions, directly impacting broader credit availability.
View PaperR&R at Journal of Applied Econometrics
We show that NLP techniques, including transformer-based deep learning models, applied to purchasing managers' textual survey responses significantly enhance forecasting accuracy of U.S. industrial production.
View PaperFinance and Economics Discussion Series, 2025
I develop the AIR Index—a novel NLP-based measure from earnings calls—to quantify AI R&D at the firm level, and show that AI R&D leads to immediate market valuation gains and accelerated capital expenditures without immediate productivity increases.
View PaperFinance and Economics Discussion Series, 2024
We analyze unique board-meeting records from community banks, showing that during financial distress boards shift discussions from routine activities toward capital management and regulatory oversight, and experience increased turnover and sharply negative sentiment.
View PaperFinance and Economics Discussion Series, 2024
We develop a real-time indicator of layoffs using SEC 8-K filings analyzed through NLP and LLMs, providing timely signals that correlate strongly with labor market conditions.
View PaperFEDS Notes, 2024
We review multiple firm and employee surveys, revealing that AI adoption varies widely but consistently falls within a 20-40% range.
Featured in speech by Vice Chair for Supervision Michael S. Barr, Feb 18, 2025
Featured in Speech by Governor Adriana D. Kugler, Feb 7, 2025
View PaperFEDS Notes, 2023
I develop the Supply Chain Bottleneck Sentiment (SCB Sentiment) index, a novel NLP-based measure derived from Federal Reserve Beige Books, capturing both frequency and sentiment of supply chain disruptions.
Featured in Financial Times, March 11, 2025
Featured in Remarks from Vice Chair Philip N. Jefferson, Feb 21, 2025
View PaperI am a senior economist at the Federal Reserve Board, having joined in 2022. As part of the Industrial Output section, I work on the Federal Reserve Board's Expanded Measurement Agenda (EMA) where I leverage ML/AI techniques alongside novel data sources to develop measures of economic activity. I am also a Research Fellow at the Federal Deposit Insurance Corporation. Previously, from 2018-2022, I was a financial economist at the Federal Deposit Insurance Corporation (FDIC), where I conducted banking research and developed quantitative models to support FDIC operations.
I completed my PhD in Economics in July 2018 at Universitat Pompeu Fabra and the Barcelona School of Economics. My academic background includes a Bachelor's degree in Applied Mathematics from the University of California, Berkeley. During my doctoral studies, I collaborated with central banks, including an eight-month research visit at the Deutsche Bundesbank and research projects with the Banco de la República of Colombia. I also held internships in the credit analytics department at Moody's Analytics and various investment funds. Additionally, I taught courses in Text Mining and Financial Analytics as an adjunct professor at the University of Maryland from 2019 to 2023.
Outside of economics and finance, my interests include artificial intelligence, Brazilian Jiu Jitsu, and improv comedy.