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.
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Paper provided by University of Rochester - Center for Economic Research (RCER) in its series RCER Working Papers with number
442.
Length: 40 pages Date of creation: 1997 Date of revision: Handle: RePEc:roc:rocher:442
Contact details of provider: Postal: UNIVERSITY OF ROCHESTER, CENTER FOR ECONOMIC RESEARCH, DEPARTMENT OF ECONOMICS, HARKNESS 231 ROCHESTER NEW YORK 14627 U.S.A.
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Find related papers by JEL classification: C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions