Econometrics, Applied Microeconomics
Xiaodong Liu and Lung-fei Lee (2010) "GMM Estimation of Social Interaction Models with Centrality", Journal of Econometrics 159, 99-115. (working paper version)
Xiaodong Liu, Lung-fei Lee and Christopher R. Bollinger (2010) "An Efficient GMM Estimator of Spatial Autoregressive Models", Journal of Econometrics 159, 303-319. (working paper version)
Lung-fei Lee and Xiaodong Liu (2010) "Efficient GMM Estimation of High Order Spatial Autoregressive Models with Autoregressive Disturbances", Econometric Theory 26, 187-230. (working paper version)
Lung-fei Lee, Xiaodong Liu and Xu Lin (2010) "Specification and Estimation of Social Interaction Models with Network Structures", The Econometrics Journal 13, 145-176. (working paper version)
Xiaodong Liu (2012) "On the Consistency of the LIML Estimator of a Spatial Autoregressive Model with Many Instruments", Economics Letters 116, 472-475. (working paper version)
Xiaodong Liu and Lung-fei Lee (2013) "Two Stage Least Squares Estimation of Spatial Autoregressive Models with Endogenous Regressors and Many Instruments", Econometric Reviews 32, 734-753. (paper and appendix)
Xiaodong Liu (2013) "Estimation of a Local-Aggregate Network Model with Sampled Networks", Economics Letters 118, 243-246. (working paper version)
Xiaodong Liu, Eleonora Patacchini and Yves Zenou (2014) "Endogenous Peer Effects: Local Aggregate or Local Average?", Journal of Economic Behavior & Organization 103, 39-59. (working paper version)
Xiaodong Liu (2014) "Identification and Efficient Estimation of Simultaneous Equations Network Models", Journal of Business & Economic Statistics 32, 516-536. (working paper version)
Xiaodong Liu and Paulo Saraiva (2015) "GMM Estimation of SAR Models with Endogenous Regressors", Regional Science and Urban Economics 55, 68-79. (working paper version)
William Horrace, Xiaodong Liu and Eleonora Patacchini (2016) "Endogenous Network Production Functions with Selectivity", Journal of Econometrics 190, 222-232. (working paper version)
Xiaodong Liu, Eleonora Patacchini and Edoardo Rainone (2016) "Peer Effects in Bed Time Decisions among Adolescents: a Social Network Model with Sampled Data", forthcoming at The Econometrics Journal.
Xiaodong Liu and Ingmar R. Prucha (2016) "A Robust Test for Network Generated Dependence".
Xiaodong Liu, Eleonora Patacchini, Yves Zenou and Lung-fei Lee (2014) "Criminal Networks: Who is the Key Player?".
Ethan Cohen-Cole, Xiaodong Liu, and Yves Zenou (2014) "Multivariate Choice and Identification of Social Interactions".
Michael Kӧnig, Xiaodong Liu and Yves Zenou (2014) "R&D networks: theory, emprics and policy implications".
Econ 8838 - Econometrics Seminar II (Graduate)
Description: This is a second-year graduate econometrics course that focuses on the analysis of individual-level data. It covers econometric methods based on the general linear and nonlinear models for cross-section data and panel data. Numerical and simulation-based computational techniques in estimation will be explored. If time permits, spatial and social interaction models will be introduced. (course website)
Econ 8828 - Econometrics Seminar I (Graduate)
Description: Econ 8828 is an advanced level graduate econometrics course that focuses on asymptotic theory for cross-sectional data. This course begins by reviewing the LS and IV estimators for linear models. Following this, the course provides large sample theory to study consistency, asymptotical normality, and asymptotical efficiency of the LS and IV estimators. If time permits, nonlinear estimators like quasi-ML and GMM estimators will be introduced. (course website)
Econ 4818 - Introduction to Econometrics (Undergraduate)
Description: This course provides an introduction to the theory and applications of modern econometrics. In this course, students are guided through the principals of simple and multiple regression analysis. Issues related to estimation, inference and specification will be explored. (course website)
Econ 3818 - Introduction to Statistics with Computer Applications (Undergraduate)
Description: This course gives an introduction to statistics with emphasis on both theory and applications. It covers basic statistical concepts and techniques, and introduces their applications to a variety of practical problems. (course website)