activity
20172022
most citedConstructive Identification of Heterogeneous Elasticities in the Cobb-Douglas Production Function

3 citations · 6 across the 6 of their papers we have counts for

collaborators

12 papers

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…

econ.EM2022

Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving

Hao Dong, Yuya Sasaki

This paper proposes a density-weighted average derivative estimator based on two noisy measures of a latent regressor. Both measures have classical errors with possibly asymmetric…

econ.EM20212 cited

Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs

Harold D. Chiang, Kengo Kato, Yuya Sasaki +1

We develop a novel method of constructing confidence bands for nonparametric regression functions under shape constraints. This method can be implemented via a linear programming,…

econ.EM20201 cited

Welfare Analysis via Marginal Treatment Effects

Yuya Sasaki, Takuya Ura

Consider a causal structure with endogeneity (i.e., unobserved confoundedness) in empirical data, where an instrumental variable is available. In this setting, we show that the mea…

econ.EM2020

Testing Finite Moment Conditions for the Consistency and the Root-N Asymptotic Normality of the GMM and M Estimators

Yuya Sasaki, Yulong Wang

Common approaches to inference for structural and reduced-form parameters in empirical economic analysis are based on the consistency and the root-n asymptotic normality of the GMM…

econ.EM2019

Multiway Cluster Robust Double/Debiased Machine Learning

Harold D. Chiang, Kengo Kato, Yukun Ma +1

This paper investigates double/debiased machine learning (DML) under multiway clustered sampling environments. We propose a novel multiway cross fitting algorithm and a multiway DM…