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Rank tests for testing the randomness of autoregressive coefficients

Author

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  • Ramanathan, R. V.
  • Rajarshi, M. B.

Abstract

We propose a class of rank tests for testing the randomness of the regression coefficients in a random coefficient autoregressive model. Asymptotic distributions of these tests are obtained via weak convergence results of a randomly weighted residual empirical process proved by Koul and Ossiander (1993). The proposed rank tests are found to be asymptotically distribution free under H0. The asymptotic relative efficiency (ARE) (in the Pitman sense) of a rank test with respect to the score test for a Gaussian model is obtained.

Suggested Citation

  • Ramanathan, R. V. & Rajarshi, M. B., 1994. "Rank tests for testing the randomness of autoregressive coefficients," Statistics & Probability Letters, Elsevier, vol. 21(2), pages 115-120, September.
    • Handle: RePEc:eee:stapro:v:21:y:1994:i:2:p:115-120
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    Cited by:

    1. Hwang, Sun Y. & Basawa, I. V., 2001. "Nonlinear time series contiguous to AR(1) processes and a related efficient test for linearity," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 381-390, May.
    2. Ha, Jeongcheol & Lee, Sangyeol, 2002. "Coefficient constancy test in AR-ARCH models," Statistics & Probability Letters, Elsevier, vol. 57(1), pages 65-77, March.
    3. Horváth, Lajos & Trapani, Lorenzo, 2019. "Testing for randomness in a random coefficient autoregression model," Journal of Econometrics, Elsevier, vol. 209(2), pages 338-352.

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