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Testing for Coefficient Stability of AR(1) Model When the Null is an Integrated or a Stationary Process

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  • Daisuke Nagakura

    (Institute for Monetary and Economic Studies, Bank of Japan (E-mail: daisuke.nagakura@boj.or.jp))

Abstract

In this paper, we propose a test for coefficient stability of an AR(1) model against the random coefficient autoregressive model of order 1 or RCA(1) model without assuming a stationary nor a non- stationary process under the null hypothesis of constant coefficient. The proposed test is obtained as a modification of the locally best invariant (LBI) test by Lee (1998). We examine finite sample properties of the proposed test by Monte Carlo experiments comparing with other existing tests including the LBI test by McCabe and Tremayne (1995), which is for the null of unit root against the alternative of stochastic unit root.

Suggested Citation

  • Daisuke Nagakura, 2007. "Testing for Coefficient Stability of AR(1) Model When the Null is an Integrated or a Stationary Process," IMES Discussion Paper Series 07-E-20, Institute for Monetary and Economic Studies, Bank of Japan.
    • Handle: RePEc:ime:imedps:07-e-20
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    References listed on IDEAS

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    Cited by:

    1. Daisuke Nagakura, 2009. "Inconsistency of a Unit Root Test against Stochastic Unit Root Processes," IMES Discussion Paper Series 09-E-23, Institute for Monetary and Economic Studies, Bank of Japan.
    2. Nagakura, Daisuke, 2009. "Asymptotic theory for explosive random coefficient autoregressive models and inconsistency of a unit root test against a stochastic unit root process," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2476-2483, December.

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    More about this item

    Keywords

    Random Coefficient Autoregressive Model; Stability; Constancy;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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