Consistency, distributional convergence, and optimality of time-varying parameters in score-driven models
得分驱动模型时变参数的一致性、分布收敛与最优性
Observation-driven models for time series have a long history in statistics and econometrics, but are typically studied under the assumption of correct dynamic specification. We develop an in-fill asymptotic framework to study the limiting behavior of the estimated (i.e., filtered) time-varying parameter paths obtained with such models in (severely) mis-specified settings. We show that despite such mis-specification, the filtered paths, particularly those from the class of…