非等间隔动态面板数据模型：估计方法与应用实例

非等间隔动态面板数据模型由于相邻两期观测之间的时间长度不尽相同使得传统动态面板数据模型的估计方法失效，本文提出使用非线性最小二乘、最短距离以及它们的一步估计量对该模型进行估计，证明了这四个估计量的一致性和渐进正态性，同时借助蒙特卡洛模拟的方法验证了它们在有限样本中的估计精度，并且进一步使用所提出的估计量讨论了以往文献由于缺乏相应的估计方法而没有被研究或者充分讨论的问题，得到了一些新的结论。

The Unequally Spaced Dynamic Panel Data Model: Estimation and Applications

The nature of varying time interval lengths of two contiguous periods in unequally spaced dynamic panel data nullify the traditional estimation methods for dynamic panel data, and the current paper provides nonlinear least squares, minimum distance and their one-step estimators for the model with establishing their consistency as well as asymptotic normality. The simulation study corroborates the results in the case of finite sample. The paper also applies these estimators to discuss some uncovered or understudied topics in the existing literature due to the lack of econometric techniques, and draws some new conclusions.