Abstract
It is well known that generalized-M (GM) estimators for linear models are consistent and lead to a small loss of efficiency with respect to least squares (LS) estimator. When they are extended to threshold models the consistency of GM estimators is guaranteed only under certain objective functions. In this paper we explore, in a simulation experiment, the loss of consistency of GM-SETAR estimator under different objective functions, time-series length, parameter combinations and type of contaminations. Finally the best robust estimator is applied to study the dynamic of electricity prices where regime switching and high spikes are widely observed features.
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References
Andersen, R.: Modern Methods for Robust Regression. SAGE Publications, Chicago (2008)
Battaglia, F., Orfei, L.: Outlier detection and estimation in nonlinear time series. J. Time Ser. Anal. 26(1), 107–121 (2005)
Chan, W.S., Cheung, S.H.: On robust estimation of threshold autoregressions. J. Forecast. 13, 37–49 (1994)
Franses, P.H., van Dijk, D.: Non-linear Time Series Models in Empirical Finance. Cambridge University Press, Cambridge (2000)
Giordani, P.: A cautionary note on outlier robust estimation of threshold models. J. Forecast. 25(1), 37–47 (2006)
Giordani, P., Kohn, R., van Dijk, D.: A unified approach to nonlinearity, structural change, and outliers. J. Econ. 137(1), 112–133 (2007)
Hansen, B.E.: Inference in TAR models. Stud. Nonlinear Dyn. Econ. 2(1), 1–14 (1997)
Huisman, R., Mahieu, R.: Regime jumps in electricity prices. Energy Econ. 25(5), 425–434 (2003)
Janczura, J., Weron, R.: An empirical comparison of alternate regime-switching models for electricity spot prices. Energy Econ. 32, 1059–1073 (2010)
Janczura, J., Trueck, S., Weron, R., Wolff, R.C.: Identifying spikes and seasonal components in electricity spot price data: a guide to robust modeling. Energy Econ. 38, 96–110 (2013)
Lucas, A., van Dijk, R., Kloek, T.: Outlier robust GMM estimation of leverage determinants in linear dynamic panel data models. Discussion Paper 94–132, Tinbergen Institute (1996)
Maronna, R.A., Martin, R.D., Yohai, V.J.: Robust Statistics: Theory and Methods. Wiley, London (2006)
Nowotarski, J., Tomczyk, J., Weron, R.: Robust estimation and forecasting of the long-term seasonal component of electricity spot prices. Energy Econ. 39, 13–27 (2013)
Percival, D., Walden, A.: Wavelet Methods for Time Series Analysis. Cambridge University Press, Cambridge (2000)
van Dijk, D.: Smooth transition models: extensions and outlier robust inference. Ph.D. thesis, Erasmus University Rotterdam, Rotterdam (1999)
Zhang, L.X., Chan, W.S., Cheung, S.H., Hung, K.C.: A note on the consistency of a robust estimator for threshold autoregressive processes. Stat. Probab. Lett. 79, 807–813 (2009)
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Grossi, L., Nan, F. (2015). Robust Estimation of Regime Switching Models. In: Morlini, I., Minerva, T., Vichi, M. (eds) Advances in Statistical Models for Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-17377-1_14
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DOI: https://doi.org/10.1007/978-3-319-17377-1_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-17376-4
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