Factor-augmented forecasting regressions with threshold effects

IF 2.9 4区 经济学 Q1 ECONOMICS
Yayi Yan, Tingting Cheng
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引用次数: 2

Abstract

This paper introduces a factor-augmented forecasting regression model in the presence of threshold effects. We consider least squares estimation of the regression parameters and establish asymptotic theories for estimators of both slope coefficients and the threshold parameter. Prediction intervals are also constructed for factor-augmented forecasts. Moreover, we develop a likelihood ratio statistic for tests on the threshold parameter and a sup-Wald test statistic for tests on the presence of threshold effects, respectively. Simulation results show that the proposed estimation method and testing procedures work very well in finite samples. Finally, we demonstrate the usefulness of the proposed model through an application to forecasting stock market returns.
具有阈值效应的因子增强预测回归
本文介绍了一种存在阈值效应的因子增广预测回归模型。我们考虑回归参数的最小二乘估计,并建立了斜率系数和阈值参数估计的渐近理论。还为因子增广预测构建了预测区间。此外,我们分别为阈值参数测试开发了似然比统计量,为阈值效应存在测试开发了sup-Wald统计量。仿真结果表明,所提出的估计方法和测试程序在有限样本中运行良好。最后,我们通过预测股票市场收益的应用证明了所提出的模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Econometrics Journal
Econometrics Journal 管理科学-数学跨学科应用
CiteScore
4.20
自引率
5.30%
发文量
25
审稿时长
>12 weeks
期刊介绍: The Econometrics Journal was established in 1998 by the Royal Economic Society with the aim of creating a top international field journal for the publication of econometric research with a standard of intellectual rigour and academic standing similar to those of the pre-existing top field journals in econometrics. The Econometrics Journal is committed to publishing first-class papers in macro-, micro- and financial econometrics. It is a general journal for econometric research open to all areas of econometrics, whether applied, computational, methodological or theoretical contributions.
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