Semiparametric Efficient Estimation in Time Series.

We obtain semiparametric efficiency bounds for estimation of a location parameter in a time series model where the innovations are stationary and ergodic conditionally symmetric marginale differences but otherwise prossess general depence and distributions of unknown from. We then describe an iterative estimator that achieves this bound when the conditional density functions of the sample are known. Finally , we develop a "semi-adaptive" estimator that achieves this bound when these densities are unknown by the investigator.