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Adjusted-range-based self-normalized autocorrelation tests

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  • Sun, Jiajing
  • Zhu, Meiting
  • Linton, Oliver

Abstract

This paper presents adjusted range-based self-normalized tests for the autocorrelation function (ACF) in time series, which is crucial for understanding the dependence structure and making reliable statistical inferences. Our approach offers improved performance, especially when testing for the presence of first-order ACF. We demonstrate the efficacy of these tests through simulations and apply them to analyze COVID-19 case counts in Beijing. The results confirm the robustness of our methods, promising significant advancements in the detection of temporal dependence in complex data settings.

Suggested Citation

  • Sun, Jiajing & Zhu, Meiting & Linton, Oliver, 2025. "Adjusted-range-based self-normalized autocorrelation tests," Economics Letters, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:ecolet:v:251:y:2025:i:c:s0165176525001521
    DOI: 10.1016/j.econlet.2025.112315
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    References listed on IDEAS

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