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The balance between size and power in testing for linear association for two stationary AR(1) processes

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  • Christos Agiakloglou
  • Charalampos Agiropoulos

Abstract

The classical statistical procedure in testing the null hypothesis of zero correlation for two independent stationary AR(1) processes produces spurious correlations, contrast to the alternative testing approach that has been proposed by Agiakloglou and Tsimpanos (2012). This study examines the trade-offs between size distortions and power using both testing techniques, including the case where the true values of the autoregressive parameters are replaced by their estimates.

Suggested Citation

  • Christos Agiakloglou & Charalampos Agiropoulos, 2016. "The balance between size and power in testing for linear association for two stationary AR(1) processes," Applied Economics Letters, Taylor & Francis Journals, vol. 23(4), pages 230-234, March.
    • Handle: RePEc:taf:apeclt:v:23:y:2016:i:4:p:230-234
    DOI: 10.1080/13504851.2015.1066486
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    Cited by:

    1. Christos Agiakloglou & Anil Bera & Emmanouil Deligiannakis, 2022. "Evaluating measures of dependence for linearly generated nonlinear time series along with spurious correlation," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 535-552, July.

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