阈值预测回归模型中局部爆炸回归量的估计与推断
Estimation and Inference in Threshold Predictive Regression Models with Locally Explosive Regressors
AI总结：
本文研究含局部爆炸回归量的阈值预测回归模型，提出估计方法并推导渐近分布，通过模拟和实证揭示经济政策不确定性对可预测性的影响。
摘要：
本文研究具有混合随机局部单位根预测变量的阈值预测回归模型的估计问题。我们展示了估计过程，并在阈值效应递减的原假设下，推导了最小二乘估计量及Magdalinos和Phillips（2009）提出的基于IV的估计量的渐近分布。仿真实验关注在存在随机局部单位根阈值效应的情况下，我们提出的估计量及Gonzalo和Pitarakis（2012）中相应可预测性检验的有限样本表现。对股票回报权益指数的实证应用，说明了我们的框架在揭示特定时期可预测性机制方面的有用性。特别是，我们关注了可预测性文献中先前未考察的一个方面，即经济政策不确定性的影响。
英文摘要：
In this paper, we study the estimation of the threshold predictive regression model with hybrid stochastic local unit root predictors. We demonstrate the estimation procedure and derive the asymptotic distribution of the least square estimator and the IV based estimator proposed by Magdalinos and Phillips (2009), under the null hypothesis of a diminishing threshold effect. Simulation experiments focus on the finite sample performance of our proposed estimators and the corresponding predictability tests as in Gonzalo and Pitarakis (2012), under the presence of threshold effects with stochastic local unit roots. An empirical application to stock return equity indices, illustrate the usefulness of our framework in uncovering regimes of predictability during certain periods. In particular, we focus on an aspect not previously examined in the predictability literature, that is, the effect of economic policy uncertainty.
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