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I am interested in statistical methods to analyze high-dimensional data. High-dimensional datasets typically contain a lot of useless information, which has to be removed for adequate statistical analysis. I am working on dimension reduction methods that do not lose important information.
Lectures and Seminars
Econometrics B (Graduate/Postgraduate )
This course is designed for first year Ph.D. students. Basic econometric methods that are necessary to conduct empirical research are covered.
You can find detailed course descriptions here
Third year students will study basic methods of macine learning by reading textbooks in turns and using computers. Students are expected to analyze data using R or Python.
Fourth year students will prepare for writing their graduation thesis. All students are required to write a thesis on either theoretical or applied econometrics.
Subjects of the seminar depend on the interest of participants.
- "Regularization Parameter Selection for Penalized Empirical Likelihood Estimator," with Tomohiro Ando, Economics Letters, 2019, 178, 1-4.
- "A Note on Generalized Empirical Likelihood Estimation of Semiparametric Conditional Moment Restriction Models," Econometric Theory, 2017, 33, 1242-1258.