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Yuya Sasaki

41 papers hereh-index 16715 citations105 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author12
  • middle author9
  • last author19

Across the 40 of 41 papers where every author was matched, so the position is known.

fields
  • econ.EM30
  • math.ST4
  • stat.ME4
  • econ.GN2
  • stat.ML1
same name
  • Yuya Sasaki — 23 papers, h 13
  • Yuya Sasaki — 8 papers, h 2
  • Yuya Sasaki — 8 papers, h 5
  • Yuya Sasaki — 3 papers, h 2
  • Yuya Sasaki — 2 papers, h 2
  • Yuya Sasaki — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162026
most citedNonparametric Difference-in-Differences in Repeated Cross-Sections with Continuous Treatments

33 citations · 124 across the 37 of their papers we have counts for

collaborators
Showing math.STShow all

4 papers · 1 filter

math.ST2024

Extremal Quantiles under Two-Way Clustering

Harold D. Chiang, Ryutah Kato, Yuya Sasaki

This paper studies extremal quantiles under two-way clustered dependence. We show that the limiting distribution of unconditional intermediate-order tail quantiles is Gaussian. Thi…

math.ST2022

On Uniform Confidence Intervals for the Tail Index and the Extreme Quantile

Yuya Sasaki, Yulong Wang

This paper presents two results concerning uniform confidence intervals for the tail index and the extreme quantile. First, we show that it is impossible to construct a length-opti…

math.ST2017★ 4 cited

Uniform confidence bands for nonparametric errors-in-variables regression

Kengo Kato, Yuya Sasaki

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 fo…

math.ST2016★ 4 cited

Uniform confidence bands in deconvolution with unknown error distribution

Kengo Kato, Yuya Sasaki

This paper develops a method to construct uniform confidence bands in deconvolution when the error distribution is unknown. We mainly focus on the baseline setting where an auxilia…

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