It is well known that GM estimators for linear models are consistent and lead to a small loss of efficiency with respect to LS estimator. When they are extended to threshold models, which are piecewise linear models, the consistency of GM estimators is guaranteed only under certain choices of the objective function.In this paper we explore, in a simulation experiment, the loss of consistency of GMSETAR estimator under different objective functions, time series length, parameters combinations and type of contaminations. Finally the best robust estimator is appliedto study the dynamic of electricity prices where regime switching and high spikes are widely observed features.

Robust estimation of regime switching models

GROSSI, Luigi;Nan, Fany
2013-01-01

Abstract

It is well known that GM estimators for linear models are consistent and lead to a small loss of efficiency with respect to LS estimator. When they are extended to threshold models, which are piecewise linear models, the consistency of GM estimators is guaranteed only under certain choices of the objective function.In this paper we explore, in a simulation experiment, the loss of consistency of GMSETAR estimator under different objective functions, time series length, parameters combinations and type of contaminations. Finally the best robust estimator is appliedto study the dynamic of electricity prices where regime switching and high spikes are widely observed features.
9788867871179
Switching models; Robust statistics; Extreme observations
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/627786
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