Semiparametric Efficient Estimation in Time Series

RCER Working Papers from University of Rochester - Center for Economic Research (RCER)

Abstract: 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.

Keywords: TIME SERIES; EVALUATION; ECONOMIC MODELS (search for similar items in EconPapers)
JEL-codes: C20 C22 (search for similar items in EconPapers)
Pages: 40 pages
Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:roc:rocher:442

Access Statistics for this paper

More papers in RCER Working Papers from University of Rochester - Center for Economic Research (RCER) University of Rochester, Center for Economic Research, Department of Economics, Harkness 231 Rochester, New York 14627 U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by Richard DiSalvo ( this e-mail address is bad, please contact ).