'Highly Disaggregated Land Unavailability', a seminar by Dr Chandler Lutz (North Carolina-Charlotte)

Highly Disaggregated Land Unavailability

by Dr Chandler Lutz

Abstract

We combine high-resolution satellite imagery with modern machine-learning methods to construct novel datasets that capture the geographic determinants of U.S. housing supply. This Land Unavailability (LU) measure is a markedly more accurate house price predictor than the popular proxy of Saiz (2010). We apply LU to fundamental housing finance problems to provide substantially more precise housing wealth elasticity estimates, new evidence on the relationship between house prices and entrepreneurship during COVID-19, and novel empirical tests of the supply-side speculation theory. Finally, our LU instrument is broadly uncorrelated with housing demand proxies, supporting its use as an instrument for house prices.

About the speaker

Chandler Lutz is an Associate Professor of Finance and the Steven Ott Distinguished Scholar in Real Estate in the Belk College of Business at UNC Charlotte. He also is a research fellow at the UCLA Ziman Center for Real Estate. His research employs econometric, statistical, and machine learning methods in the study of housing markets, labor economics, and monetary policy.

Chandler’s research has been published in the Review of Financial Studies, the Journal of Labor Economics, and the Journal of Urban Economics, among other outlets. In recent work, he has developed new datasets that measure the amount of land unavailable for housing construction across the United States and causally assessed the impact of interest rate declines on distressed borrowers. While at the SEC, Chandler’s policy work spanned housing markets, financial risk, and macroeconomic analysis.