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Minimum distance estimation for random coefficient autoregressive models

Author

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  • Swaminathan, V.
  • Naik-Nimbalkar, U. V.

Abstract

In this paper, we extend the minimum distance method of Beran (1993) to random coefficient autoregressive (RCA) models. After stating the necessary assumptions the asymptotic properties of the minimum distance estimator are derived.

Suggested Citation

  • Swaminathan, V. & Naik-Nimbalkar, U. V., 1997. "Minimum distance estimation for random coefficient autoregressive models," Statistics & Probability Letters, Elsevier, vol. 34(4), pages 313-322, June.
    • Handle: RePEc:eee:stapro:v:34:y:1997:i:4:p:313-322
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    References listed on IDEAS

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    1. Rudolf Beran, 1993. "Semiparametric random coefficient regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(4), pages 639-654, December.
    2. Pham, Tuan D. & Tran, Lanh T., 1985. "Some mixing properties of time series models," Stochastic Processes and their Applications, Elsevier, vol. 19(2), pages 297-303, April.
    3. Mohsen Pourahmadi, 1988. "STATIONARITY OF THE SOLUTION OF Xt= AtXt‐1+εt AND ANALYSIS OF NON‐GAUSSIAN DEPENDENT RANDOM VARIABLES," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(3), pages 225-239, May.
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    Cited by:

    1. Yoon, Gawon, 2016. "Stochastic unit root processes: Maximum likelihood estimation, and new Lagrange multiplier and likelihood ratio tests," Economic Modelling, Elsevier, vol. 52(PB), pages 725-732.

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