Yuya Sasaki

Yuya Sasaki
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Yuya Sasaki

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Statistics - Methodology (3)
Statistics - Theory (2)
Mathematics - Statistics (2)

Publications Authored By Yuya Sasaki

This paper studies identification, estimation, and inference of quantile treatment effects in the fuzzy regression kink design with a binary treatment variable. We first show the identification of conditional quantile treatment effects given the event of local compliance. We then propose a bootstrap method of uniform inference for the local quantile process. Read More

Computation of asymptotic distributions is known to be a nontrivial and delicate task for the regression discontinuity designs (RDD) and the regression kink designs (RKD). It is even more complicated when a researcher is interested in joint or uniform inference across heterogeneous subpopulations indexed by covariates or quantiles. Hence, bootstrap procedures are often preferred in practice. Read More

This paper develops a method to construct uniform confidence bands for a nonparametric regression function where a predictor variable is subject to a measurement error. We allow for the distribution of the measurement error to be unknown, but assume that there is an independent sample from the measurement error distribution. The sample from the measurement error distribution need not be independent from the sample on response and predictor variables. Read More

This paper develops a method to construct uniform confidence bands in deconvolution when the error distribution is unknown. We work with the setting where an auxiliary sample from the error distribution is available and the error density is ordinary smooth. The construction is based upon the "intermediate" Gaussian approximation and the Gaussian multiplier bootstrap, but not on explicit limit distributions such as Gumbel distributions, which enables us to prove validity of the multiplier bootstrap confidence band under weak regularity conditions. Read More

The quantile regression kink design (QRKD) is proposed by empirical researchers as a potential method to assess heterogeneous treatment effects under suitable research designs, but its causal interpretation remains unknown. We propose causal interpretations of the QRKD estimand. Under flexible heterogeneity and endogeneity, the sharp and fuzzy QRKD estimands measure weighted averages of heterogeneous marginal effects at respective conditional quantiles of outcome given a designed kink point. Read More