Identification and Estimation of Continuous Time Dynamic Systems With Exogenous Variables Using Panel Data
研究了从离散时间样本中识别和最大似然估计随机微分方程参数的方法，推导了得分函数和似然方程，并扩展到含随机效应的面板数据分析，探讨了外生变量对参数可识别性的影响。
This paper deals with the identification and maximum likelihood estimation of the parameters of a stochastic differential equation from discrete time sampling. Score function and maximum likelihood equations are derived explicitly. The stochastic differential equation system is extended to allow for random effects and the analysis of panel data. In addition, we investigate the identifiability of the continuous time parameters, in particular the impact of the inclusion of exogenous variables.