陈晓红 (1965年)

关于名为陈晓红的其他人物，請見「陈晓红」。

陈晓红（1965年—）^[1]，出生于湖北武汉，美籍华裔经济学家，目前担任耶鲁大学Malcolm K. Brachman经济学教授。她是和2017年中国经济学奖获得者，也是第一位来自中国大陆的经济计量学会会士。^[2]她的研究领域为计量经济学理论，提出了一套对于具有内生性的半非参数条件矩模型的估计和推断方法。^[3]

陈晓红 Xiaohong Chen
出生	中国湖北省武汉市
母校	武汉大学 (B.A.) 中国人民大学 (中美经济学培训班) 西安大略大学 (M.A.) 聖地牙哥加利福尼亞大學 (Ph.D.)
雇主	耶鲁大学
荣誉	2007 经济计量学会会士 2012 Fellow of Journal of Econometrics 2017 中国经济学奖 2018 Sargan Lecturer, Econometric Society 2019 美国人文与科学院院士

部分研究论文

• Carroll, R. J., Chen, X., & Hu, Y. (2010). Identification and estimation of nonlinear models using two samples with nonclassical measurement errors. Journal of Nonparametric Statistics, 22(4), 419-423.
• Chen, X., & Christensen, T. M. (2015). Optimal Sup-norm Rates and Uniform Inference on Nonlinear Functionals of Nonparametric IV Regression. Quantitative Economics, 9, 39-84.
• Chen, X., & Fan, Y. (2006). Estimation of copula-based semiparametric time series models. Journal of Econometrics, 130(2), 307-335.
• Chen, X., & Gao, F. (2017). A Reverse Gaussian Correlation Inequality by Adding Cones. Statistics & Probability Letters, 123, 84-87.
• Chen, X., Jacho-Chávez, D. T., & Linton, O. (2016). Averaging of an Increasing Number of Moment Condition Estimators. Econometric Theory, 32, 30-70.
• Chen, X., Linton, O., & Yi, Y. (2017). Semiparametric Identification of the Bid-Ask Spread in Extended Roll Models. Journal of Econometrics, 200, 312-325.
• Chen, X., Linton, O., Schneeberger, S., & Yi, Y. (2019). Semiparametric estimation of the bid–ask spread in extended roll models. Journal of Econometrics, 208(1), 160-178.
• Chen, X., & Ludvigson, S. (2009). Land of Addicts? An Empirical Investigation of Habit-Based Asset Pricing Behavior. Journal of Applied Econometrics, 24, 1057-1093.
• Chen, X., & Qiu, Y. J. (2016). Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide. SSRN Electronic Journal, 2016(8), 259-290.
• Chen, X., & Santos, A. (2018). Overidentification in Regular Models. Econometrica, 86(5), 1771-1817.
• Chen, X., Shao, Q., Wu, W. B., & Xu, L. (2016). Self-normalized Cramér-type moderate deviations under dependence. The Annals of Statistics, 44, 1593-1617.
• Tamer, E., Christensen, T. M., & Chen, X. (2018). Monte Carlo confidence sets for identified sets. Econometrica, 86(6), 1965-2018.^[4]