Christian B. Hansen, University of Chicago
Professor
Chicago, Illinois
chansen1@chicagobooth.edu
Office:
(773) 834-1702
Expert In
Bio/Research
Christian B. Hansen studies applied and theoretical econometrics, the uses of high-dimensional statistical methods in economic applications, estimation of panel data models, quantile regression, and weak instruments. In 2008, Hansen was named a Neubauer Family Faculty Fellow, and he was named the...
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Bio/Research
Christian B. Hansen studies applied and theoretical econometrics, the uses of high-dimensional statistical methods in economic applications, estimation of panel data models, quantile regression, and weak instruments. In 2008, Hansen was named a Neubauer Family Faculty Fellow, and he was named the Wallace W. Booth professorship in 2014.
Hansen's recent research has focused on the uses of high-dimensional data and methods in economics applications. The papers “Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain” with A. Belloni, D. Chen, and V. Chernzhukov (Econometrica, 2012) and “Inference on Treatment Effects after Selection amongst High-Dimensional Controls” with A. Belloni and V. Chernozhukov (Review of Economic Studies, 2014) present approaches to estimating structural or treatment effects from economic data in canonical instrumental variables and treatment effects models. These papers are extended in “Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach” with V. Chernozhukov and M. Spindler (Annual Review of Economics, 2015) and the forthcoming papers “Inference in High Dimensional Panel Models with an Application to Gun Control” with A. Belloni, V. Chernozhukov, and D. Kozbur (Journal of Business and Economic Statistics) and “Program Evaluation with High-Dimensional Data” with A. Belloni, V. Chernozhukov, and I. Fernández-Val (Econometrica).
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Hansen's recent research has focused on the uses of high-dimensional data and methods in economics applications. The papers “Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain” with A. Belloni, D. Chen, and V. Chernzhukov (Econometrica, 2012) and “Inference on Treatment Effects after Selection amongst High-Dimensional Controls” with A. Belloni and V. Chernozhukov (Review of Economic Studies, 2014) present approaches to estimating structural or treatment effects from economic data in canonical instrumental variables and treatment effects models. These papers are extended in “Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach” with V. Chernozhukov and M. Spindler (Annual Review of Economics, 2015) and the forthcoming papers “Inference in High Dimensional Panel Models with an Application to Gun Control” with A. Belloni, V. Chernozhukov, and D. Kozbur (Journal of Business and Economic Statistics) and “Program Evaluation with High-Dimensional Data” with A. Belloni, V. Chernozhukov, and I. Fernández-Val (Econometrica).
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