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The Chang-Kim-Park Model of Cointegrated Density-Valued Time Series Cannot Accommodate a Stochastic Trend

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  • Brendan K. Beare

Abstract

In this comment on a 2016 article in the Journal of Econometrics by Yoosoon Chang, Chang Sik Kim, and Joon Y. Park I point out that the time series of densities which the authors purport to model as a nonstationary cointegrated process is in fact stationary under their assumptions, aside from a deterministic component.

Suggested Citation

  • Brendan K. Beare, 2017. "The Chang-Kim-Park Model of Cointegrated Density-Valued Time Series Cannot Accommodate a Stochastic Trend," Econ Journal Watch, Econ Journal Watch, vol. 14(2), pages 133–137-1, May.
  • Handle: RePEc:ejw:journl:v:14:y:2017:i:2:p:133-137
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    References listed on IDEAS

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    1. Chang, Yoosoon & Kim, Chang Sik & Park, Joon Y., 2016. "Nonstationarity in time series of state densities," Journal of Econometrics, Elsevier, vol. 192(1), pages 152-167.
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    Cited by:

    1. Beare, Brendan K. & Seo, Won-Ki, 2020. "Representation Of I(1) And I(2) Autoregressive Hilbertian Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 773-802, October.
    2. Won-Ki Seo, 2020. "Functional Principal Component Analysis for Cointegrated Functional Time Series," Papers 2011.12781, arXiv.org, revised Apr 2023.
    3. Brendan K. Beare & Juwon Seo & Won-Ki Seo, 2017. "Cointegrated Linear Processes in Hilbert Space," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1010-1027, November.
    4. Franchi, Massimo & Paruolo, Paolo, 2020. "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 803-839, October.
    5. Seo, Won-Ki & Beare, Brendan K., 2019. "Cointegrated linear processes in Bayes Hilbert space," Statistics & Probability Letters, Elsevier, vol. 147(C), pages 90-95.

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    More about this item

    Keywords

    Nonstationarity; cointegration; functional time series.;
    All these keywords.

    JEL classification:

    • 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

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