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Linearity tests and stochastic trend under the STAR framework

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  • Lingxiang Zhang

    (Beijing Institute of Technology)

Abstract

This study investigates the linearity test of smooth transition autoregressive models when the true data generating process is a stochastic trend process. Results show that, under the null hypothesis of linearity, the asymptotic distribution of the W statistic proposed by Teräsvirta (J Am Stat Assoc 89:208–218, 1994) follows the χ2 distribution, whereas the finite sample distribution does not. A maximized Monte Carlo simulation-based test is used to perform the linearity test, and the results show good performance.

Suggested Citation

  • Lingxiang Zhang, 2020. "Linearity tests and stochastic trend under the STAR framework," Statistical Papers, Springer, vol. 61(6), pages 2271-2282, December.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:6:d:10.1007_s00362-018-1047-4
    DOI: 10.1007/s00362-018-1047-4
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    References listed on IDEAS

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    More about this item

    Keywords

    Linearity; STAR; Stochastic trend; Maximized Monte Carlo simulation-based test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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