  This paper deals with a general class of observation-driven time series
models with a special focus on time series of counts. We provide conditions
under which there exist strict-sense stationary and ergodic versions of such
processes. The consistency of the maximum likelihood estimators is then derived
for well- specified and misspecified models.
