11 citations · 28 across the 5 of their papers we have counts for
6 papers
Capital and Labor Income Pareto Exponents in the United States, 1916-2019
Ji Hyung Lee, Yuya Sasaki, Alexis Akira Toda +1
Accurately estimating income Pareto exponents is challenging due to limitations in data availability and the applicability of statistical methods. Using tabulated summaries of inco…
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…
Fixed-k Tail Regression: New Evidence on Tax and Wealth Inequality from Forbes 400
Ji Hyung Lee, Yuya Sasaki, Alexis Akira Toda +1
We develop a novel fixed-k tail regression method that accommodates the unique feature in the Forbes 400 data that observations are truncated from below at the 400th largest order…
Predictive Quantile Regression with Mixed Roots and Increasing Dimensions: The ALQR Approach
Rui Fan, Ji Hyung Lee, Youngki Shin
In this paper we propose the adaptive lasso for predictive quantile regression (ALQR). Reflecting empirical findings, we allow predictors to have various degrees of persistence and…
Complete Subset Averaging for Quantile Regressions
Ji Hyung Lee, Youngki Shin
We propose a novel conditional quantile prediction method based on complete subset averaging (CSA) for quantile regressions. All models under consideration are potentially misspeci…
On LASSO for Predictive Regression
Ji Hyung Lee, Zhentao Shi, Zhan Gao
Explanatory variables in a predictive regression typically exhibit low signal strength and various degrees of persistence. Variable selection in such a context is of great importan…