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New Unit Root Tests in the Nonlinear ESTAR Framework: The Movement and Volatility Characteristics of Crude oil and Copper Prices

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  • Yanglin Li

    (Huazhong University of Science and Technology)

Abstract

This paper proposes new wild bootstrap GLS-detrended unit root tests in the exponential smooth transition autoregressive framework, which could handle both nonlinear movement and time-varying volatility for financial time series. We derive the asymptotic distributions of the proposed tests and explore the finite sample properties. Simulation results show that the size and power performance of the proposed tests are better than the conventional tests. An application on crude oil and copper prices further underlines our test’s priority, and our proposed tests do not reject the unit root null of crude oil and copper prices.

Suggested Citation

  • Yanglin Li, 2024. "New Unit Root Tests in the Nonlinear ESTAR Framework: The Movement and Volatility Characteristics of Crude oil and Copper Prices," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1757-1776, May.
  • Handle: RePEc:kap:compec:v:63:y:2024:i:5:d:10.1007_s10614-023-10381-8
    DOI: 10.1007/s10614-023-10381-8
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    References listed on IDEAS

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    1. Kapetanios, George & Shin, Yongcheol, 2008. "GLS detrending-based unit root tests in nonlinear STAR and SETAR models," Economics Letters, Elsevier, vol. 100(3), pages 377-380, September.
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    More about this item

    Keywords

    Unit root tests; ESTAR; Time-varying volatility; Wild bootstrap;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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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