Andres Santos studies nonparametric and semiparametric estimation and inference, as well as large deviations optimality.
Among his recent working papers are “Interval Estimation of Potentially Misspecified Quantile Models in the Presence of Missing Data” (with Patrick Kline); “On the Asymptotic Optimality of Empirical Likelihood for Testing Moment Restrictions” (with Yuichi Kitamura and Azeem Shaikh); and “Semiparametric Estimation of Nonseparable Models: A Minimum Distance from Independence Approach” (with Ivana Komunjer).
Santos joined the University of California, San Diego economics faculty in 2007, and won the Department of Economics Graduate Teaching Award for the next two years.
He earned his PhD in economics from Stanford University, where he won the Stanford Institute for Economic Policy Research Dissertation Fellowship in 2006 and the Sean Buckley Prize for Best PhD Candidacy Paper in 2004.
- 2011: March 7–11