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Empirical Likelihood-based Inference for Stationary-ergodicity of the Generalized Random Coefficient Autoregressive Model

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  • Zhi-Wen Zhao
  • De-Hui Wang
  • Cui-Xin Peng
  • Mei-Li Zhang

Abstract

In this article, we consider the application of the empirical likelihood method to the generalized random coefficient autoregressive (GRCA) model. When the order of the model is 1, we derive an empirical likelihood ratio test statistic to test the stationary-ergodicity. Some simulation studies are also conducted to investigate the finite sample performances of the proposed test.

Suggested Citation

  • Zhi-Wen Zhao & De-Hui Wang & Cui-Xin Peng & Mei-Li Zhang, 2015. "Empirical Likelihood-based Inference for Stationary-ergodicity of the Generalized Random Coefficient Autoregressive Model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(12), pages 2586-2599, June.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:12:p:2586-2599
    DOI: 10.1080/03610926.2013.786786
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    Cited by:

    1. Chi Yao & Wei Yu & Xuejun Wang, 2023. "Strong Consistency for the Conditional Self-weighted M Estimator of GRCA(p) Models," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-21, March.
    2. Yuxin Pang & Dehui Wang, 2024. "A New Random Coefficient Autoregressive Model Driven by an Unobservable State Variable," Mathematics, MDPI, vol. 12(24), pages 1-16, December.

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