Tetsuya Kaji
I am Associate Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. I work at the intersections of economics, statistics, and machine learning.
Working Papers
The Hellinger Bounds on the Kullback-Leibler Divergence and the Bernstein Norm
Why Do the Elderly Save? Using Health Shocks to Uncover Bequests Motives (with Elena Manresa)
A Necessary and Sufficient Condition for Convergence in Distribution of P-P Process in L1(0,1) (with Brendan Beare)
A Necessary and Sufficient Condition for Convergence in Distribution of Quantile Process in L1(0,1) (with Brendan Beare)
Assessing Heterogeneity of Treatment Effects (with Jianfei Cao)
Controlling Tail Risk Measures with Estimation Error (with Hyungjune Kang)
Publications
An Adversarial Approach to Structural Estimation
Econometrica, 91(6), 2041−2063, November 2023 (with Elena Manresa and Guillaume Pouliot). [Preprint] [Online Appendix] [Code] [Chicago Booth Review]
Metropolis-Hastings via Classification
Journal of the American Statistical Association, 118(544), 2533−2547, 2023 (with Veronika Ročková). [Preprint] [Online Appendix]
Approximate Bayesian Computation via Classification
Journal of Machine Learning Research, 23(350), 1−49, 2022 (with Yuexi Wang and Veronika Ročková). [Preprint]
Adversarial Inference Is Efficient
AEA Papers and Proceedings, 111, 621−625, May 2021 (with Elena Manresa and Guillaume Pouliot). [Online Appendix]
Theory of Weak Identification in Semiparametric Models
Econometrica, 89(2), 733−763, March 2021. [Preprint] [Code]
Extremal Quantile Regression
Handbook of Quantile Regression, ed. by R. Koenker, V. Chernozhukov, X. He, and L. Peng, Chapman & Hall/CRC, 2017, ch. 18, 333−362 (with Victor Chernozhukov and Iván Fernández-Val). [Preprint] [Code]