Inference regarding multiple structural changes in linear models estimated via two stage least squares
Inference regarding multiple structural changes in linear models estimated via two stage least squares
复制标题
关于通过两阶段最小二乘估计的线性模型中的多个结构变化的推断
DOI：
--
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
O. Boldea
中科院分区：
文献类型：
--
作者：
A. Hall;S. Han;O. Boldea
本文将Bai和Perron（1998，Econometrica，p.47-78）的多重断点检验框架扩展到线性模型，并通过两阶段最小二乘法（2SLS）进行估计。在我们的框架内，通过最小化2SLS估计的第二步上的残差平方和，与回归参数同时估计断点。我们建立的一致性，由此产生的估计断点分数。我们证明了基于2SLS估计的结构失稳的各种F-统计量与Bai和Perron（1998）考虑的OLS的类似统计量具有相同的极限分布。这使我们能够将Bai和Perron（1998）的选择断点数量的顺序过程扩展到2SLS设置。我们的方法还允许结构的不稳定性，在减少的形式，已确定了先验使用基于数据的方法。作为实证说明，我们的方法被用来评估新凯恩斯主义菲利普斯曲线的稳定性。
In this paper, we extend Bai and Perron’s (1998, Econometrica, p.47-78) framework for multiple break testing to linear models estimated via Two Stage Least Squares (2SLS). Within our framework, the break points are estimated simultaneously with the regression parameters via minimization of the residual sum of squares on the second step of the 2SLS estimation. We establish the consistency of the resulting estimated break point fractions. We show that various F-statistics for structural instability based on the 2SLS estimator have the same limiting distribution as the analogous statistics for OLS considered by Bai and Perron (1998). This allows us to extend Bai and Perron’s (1998) sequential procedure for selecting the number of break points to the 2SLS setting. Our methods also allow for structural instability in the reduced form that has been identified a priori using data-based methods. As an empirical illustration, our methods are used to assess the stability of the New Keynesian Phillips curve.