【摘要】 面板数据中的变点问题是金融和计量经济学中的一类重要课题。现将局部形态识别的二元分割算法推广到面板数据上，研究了面板数据中均值多变点和方差多变点的估计问题，同时得到了变点个数及变点位置的估计，证明了估计量的相合性。Monte Carlo模拟表明基于局部形态识别的二元分割算法对这两类变点的估计效果均优于二元分割算法。最后将提出的算法分别应用于不同的股市周指数数据，说明了算法的有效性。更多还原

【Abstract】 Change-point problem in panel data is an important topic in finance and econometric. A multiple change-point estimation procedure based on the shape-based BS algorithm is extended to panel data, multiple change-point estimation in the mean and variance of panel data model is studied. The number and location of the change-points are also obtained, and the consistency of the change point estimators is proved. Monte Carlo simulation shows that the shape-based BS algorithm outperforms the BS algorithm in estimating both types of change points. Finally, this method is applied to different weekly index data of the stock market, which shows the effectiveness of the algorithm.更多还原