依赖数据未知阈值下的阈值期望分位数回归

Threshold Expectile Regressions With an Unknown Threshold for Dependent Data

Oxford Bulletin of Economics and Statistics · 2025
被引 5 · 同刊同年前 1%
人大 AABS 3

中文导读

针对依赖数据提出了一个阈值期望分位数回归模型,用于刻画经济和金融中的非线性和异方差性,并开发了检验阈值效应和共同阈值的推断方法,模拟和实证表明模型有效。

Abstract

ABSTRACT This article introduces a threshold expectile regression model with an unknown threshold for dependent data, which enables simple characterization of nonlinearity and heteroscedasticity in economic and financial applications. Profile estimation is proposed for the unknown parameters, and a sup‐Wald test is developed to test the existence of the threshold effect at a fixed expectile level. Inference issues across multiple expectile levels are further considered, with a likelihood‐ratio‐type test designed to check for the presence of a common threshold value. Monte Carlo simulations demonstrate the nice finite sample performance of the proposed inference procedures. Finally, an empirical application demonstrates that the debt‐to‐GDP ratio has a heterogeneous threshold effect on the U.S. growth rate across the growth distribution.

阈值期望回归相依数据非线性检验异质性阈值效应