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STICERD Associate and Professor of Econometrics
Expertise: nonparametric and semiparametric methods, microeconometrics
25 January 2022
Hao Dong, Taisuke Otsu and Luke Taylor
We propose two novel bandwidth selection procedures for the nonparametric regression model with classical measurement error in the regressors. Each method is based on evaluating the prediction errors of the regression us... Read more...
07 January 2022
Yukitoshi Matsushita, Taisuke Otsu and Keisuke Takahata
In various fields of data science, researchers often face problems of estimating the ratios of two probability densities. Particularly in the context of causal inference, the product of marginals for a treatment variable... Read more...
26 October 2021
Taisuke Otsu and Martin Pesendorfer
This paper surveys the recent literature on dynamic games estimation when there is a concern of equilibrium multiplicity. We focus on the questions of testing for equilibrium multiplicity and estimation in the presence o... Read more...
19 October 2021
Harold D Chiang, Yukitoshi Matsushita and Taisuke Otsu
his paper develops a general methodology to conduct statistical inference for observations indexed by multiple sets of entities. We propose a novel multiway empirical likeli- hood statistic that converges to a chi-square... Read more...
14 September 2021
Daisuke Kurisu and Taisuke Otsu
This paper studies asymptotic properties of the local linear quantile estimator under the extremal order quantile asymptotics, and develops a practical inference method for conditional quantiles in extreme tail areas. By... Read more...
19 July 2021
By utilizing intermediate Gaussian approximations, this paper establishes asymptotic linear representations of nonparametric deconvolution estimators for the classical measurement error model with repeated measurements. ... Read more...
01 December 2020
Karun Adusumilli, Taisuke Otsu and Chen Qiu
This paper is concerned with inference on finite dimensional parameters in semiparametric moment condition models, where the moment functionals are linear with respect to unknown nuisance functions. By exploiting this li... Read more...
05 August 2020
Yukitoshi Matsushita and Taisuke Otsu
This paper proposes a jackknife Lagrange multiplier (JLM) test for instrumental variable regression models, which is robust to (i) many instruments, where the number of instruments may increase proportionally with the sa... Read more...
12 May 2020
This paper studies second-order properties of the many instruments robust t-ratios based on the limited information maximum likelihood and Fuller estimators for instrumental variable regression models under the many inst... Read more...
20 January 2020
Taisuke Otsu, Martin Pesendorfer, Yuya Sasaki and Yuya Takahashi
We propose a multiplicity-robust estimation method for (static or dynamic) games. The method allows for distinct behaviors and strategies across markets by treating market specific behaviors as correlated latent variable... Read more...
04 December 2008
Taisuke Otsu (Yale)
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