9 citations · 29 across the 17 of their papers we have counts for
12 papers · 1 filter
Robust Econometrics for Growth-at-Risk
Tobias Adrian, Yuya Sasaki, Yulong Wang
The Growth-at-Risk (GaR) framework has garnered attention in recent econometric literature, yet current approaches implicitly assume a constant Pareto exponent. We introduce novel…
Extreme Quantile Treatment Effects under Endogeneity: Evaluating Policy Effects for the Most Vulnerable Individuals
Yuya Sasaki, Yulong Wang
We introduce a novel method for estimating and conducting inference about extreme quantile treatment effects (QTEs) in the presence of endogeneity. Our approach is applicable to a…
Genuinely Robust Inference for Clustered Data
Harold D. Chiang, Yuya Sasaki, Yulong Wang
Conventional cluster-robust inference can be invalid when data contain clusters of unignorably large size. We formalize this issue by deriving a necessary and sufficient condition…
Extreme Changes in Changes
Yuya Sasaki, Yulong Wang
Policy analysts are often interested in treating the units with extreme outcomes, such as infants with extremely low birth weights. Existing changes-in-changes (CIC) estimators are…
Non-Robustness of the Cluster-Robust Inference: with a Proposal of a New Robust Method
Yuya Sasaki, Yulong Wang
The conventional cluster-robust (CR) standard errors may not be robust. They are vulnerable to data that contain a small number of large clusters. When a researcher uses the 51 sta…
Tuning Parameter-Free Nonparametric Density Estimation from Tabulated Summary Data
Ji Hyung Lee, Yuya Sasaki, Alexis Akira Toda +1
Administrative data are often easier to access as tabulated summaries than in the original format due to confidentiality concerns. Motivated by this practical feature, we propose a…
Non-Existent Moments of Earnings Growth
Silvia Sarpietro, Yuya Sasaki, Yulong Wang
The literature often employs moment-based earnings risk measures like variance, skewness, and kurtosis. However, under heavy-tailed distributions, these moments may not exist in th…
Nonparametric Tests of Tail Behavior in Stochastic Frontier Models
William, C. Horrace, Yulong Wang
This article studies tail behavior for the error components in the stochastic frontier model, where one component has bounded support on one side, and the other has unbounded suppo…
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…
Estimation and Inference about Tail Features with Tail Censored Data
Yulong Wang, Zhijie Xiao
This paper considers estimation and inference about tail features when the observations beyond some threshold are censored. We first show that ignoring such tail censoring could le…
Fixed-k Inference for Conditional Extremal Quantiles
Yuya Sasaki, Yulong Wang
We develop a new extreme value theory for repeated cross-sectional and panel data to construct asymptotically valid confidence intervals (CIs) for conditional extremal quantiles fr…
Threshold Regression with Nonparametric Sample Splitting
Yoonseok Lee, Yulong Wang
This paper develops a threshold regression model where an unknown relationship between two variables nonparametrically determines the threshold. We allow the observations to be cro…