Paul Goldsmith-Pinkham's research spans consumer finance, housing markets, and applied econometrics, with a focus on uncovering and explaining disparities across demographic groups. His work examines how financial decisions and market outcomes vary by race, ethnicity, and gender—from housing returns and real estate agent effectiveness to consumer debt and health insurance transitions. As an applied econometrician, he develops and critiques empirical methods, including recent work on contamination bias in linear regressions, Bartik and shift-share instruments, and the application of machine learning to credit markets. His research on financial crises includes analysis of bank runs and contagion effects. Paul's work frequently appears in top journals and has been covered by major media outlets including The Economist, NPR, and CNBC. Before joining Yale, he was a Research Economist at the Federal Reserve Bank of New York. He earned a bachelor’s degree in economics from Swarthmore College, and a PhD in economics from Harvard University.
Brattle Group Prize in Corporate Finance, First Place, Journal of Finance 2022 for Predictably Unequal? The Effects of Machine Learning on Credit Markets Outstanding Paper award for “Sea Level Rise Exposure and Municipal Bond Yields”, Jacobs Levy Center Research Paper Prizes, 2021 Best Empirical Finance Paper for “The Gender Gap in Housing Returns”, WRDS (Wharton Research Data Services), 2020 Best Empirical Finance Paper for “Predictably Unequal? The Effects of Machine Learning on Credit Markets”, WRDS (Wharton Research Data Services), 2019
