We introduce a class of semiparametric time series models by assuming quasi-likelihood approach driven latent factor process. More specifically, given the process, we only specify conditional mean and variance enjoy function for estimating parameters related to mean. This proposed methodology has three remarkable features: (i) no parametric form is assumed distribution process; (ii) able modell...

Abstract We argue that existing methods for the treatment of missing observations in time-varying parameter observation-driven models lead to inconsistent inference. provide a formal proof this inconsistency Gaussian model with mean. A Monte Carlo simulation study supports theoretical result and illustrates how problem extends score-driven and, more generally, models, which include well-known c...