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Modeling bivariate long‐range dependence with general phase

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  • Stefanos Kechagias
  • Vladas Pipiras

Abstract

Bivariate time series models are considered that are suitable for estimation, that have interpretable parameters and that can capture the general semi‐parametric formulation of bivariate long‐range dependence, including a general phase. The models also allow for short‐range dependence and fractional cointegration. A simulation study to test the performance of a conditional maximum likelihood estimation method is carried out, under the proposed models. Finally, an application is presented to the U.S. inflation rates in goods and services where models not allowing for general phase suffer from misspecification.

Suggested Citation

  • Stefanos Kechagias & Vladas Pipiras, 2020. "Modeling bivariate long‐range dependence with general phase," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 268-292, March.
    • Handle: RePEc:bla:jtsera:v:41:y:2020:i:2:p:268-292
    DOI: 10.1111/jtsa.12504
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    References listed on IDEAS

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