Doubly Robust Identification of Causal Effects of a Continuous Treatment using Discrete Instruments
Prof. Yingying DONG
Professor, University of California Irvine
Date: 09 May 2024 (Thursday)
Time: 03:00 pm – 04:30 pm
Venue: E22-G015
Host: Prof. Zhuo QIAO, Associate Professor in Business Economics
Abstract
Many empirical applications estimate causal effects of a continuous endogenous variable (treatment) using a binary instrument. Estimation is typically done through linear 2SLS. This approach requires a mean treatment change and causal interpretation requires the LATE-type monotonicity in the first stage. An alternative approach is to explore distributional changes in the treatment, where the first-stage restriction is treatment rank similarity. We propose causal estimands that are doubly robust in that they are valid under either of these two restrictions. We apply the doubly robust estimation to estimate the impacts of sleep on well-being. Our new estimates corroborate the usual 2SLS estimates.
Speaker
Prof. DONG received her Ph.D. in 2009 from Boston College. She is currently a professor of Economics at University of California Irvine. She is also a research fellow at Institute for the Study of Labor. She works on both theoretical and empirical econometrics. Her research focuses on causal inference, treatment effects models and policy evaluation as well as applied topics in labor, education and health. She has published in the Review of Economics and Statistics, Journal of Econometrics, Journal of the American Statistical Association, Journal of Business and Economic Statistics, European Economic Review, and Journal of Applied Econometrics among others.
All are welcome!
