标题： 一种加权回归方法用于面板数据中的断点检测 显示英文标题

标题： A Weighted Regression Approach to Break-Point Detection in Panel Data

摘要： 针对检测面板数据横截面均值变化的新程序被提出。 这些程序依赖于使用跨面板的某些横截面均值通过加权最小二乘回归来估计干扰参数。 在面板之间存在弱横截面相关性的情况下，我们展示了如何构造检验统计量，使其极限零分布不依赖于通常用于估计面板误差长期方差的带宽选择。 理论断言适用于回归权重的一般选择，并表明可以从所提出的过程中获得一致的检验过程。 理论结果扩展到面板之间存在强横截面相关性的案例。 本文最后通过数值研究说明了检验过程的几个特殊案例在有限样本中的行为。 显示英文摘要

摘要： New procedures for detecting a change in the cross-sectional mean of panel data are proposed. The procedures rely on estimating nuisance parameters using certain cross-sectional means across panels using a weighted least squares regression. In the case of weak cross-sectional dependence between panels, we show how test statistics can be constructed to have a limit null distribution not depending on any choice of bandwidths typically needed to estimate the long-run variances of the panel errors. The theoretical assertions are derived for general choices of the regression weights, and it is shown that consistent test procedures can be obtained from the proposed process. The theoretical results are extended to the case where strong cross-sectional dependence exist between panels. The paper concludes with a numerical study illustrating the behavior of several special cases of the test procedure in finite samples.