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Strong consistency of conditional least squares estimators in multiple regime threshold autoregressive models

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Summary

In this paper we analyse the conditional least squares estimators of the parameters of a multiple regime threshold AR(1) model and prove that under certain conditions these are strongly consistent. We assume that the error process in each regime is amartingale difference sequence. Then we deal with strong consistency of the natural estimator of the error variance in each regime.

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Authors and Affiliations

  1. Dipartimento di Scienze Economiche e Statistiche, Università di Trieste, Piazzale Europa 1, I-34127, Trieste, Italy

    Gabriella Schoier

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  1. Gabriella Schoier
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Correspondence to Gabriella Schoier.

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Schoier, G. Strong consistency of conditional least squares estimators in multiple regime threshold autoregressive models. J. Ital. Statist. Soc. 8, 75 (1999). https://doi.org/10.1007/BF03178942

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  • DOI: https://doi.org/10.1007/BF03178942

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