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On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests

In: Essays in Honor of Peter C. B. Phillips

Author

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  • Eric Ghysels
  • J. Isaac Miller

Abstract

We analyze the sizes of standard cointegration tests applied to data subject to linear interpolation, discovering evidence of substantial size distortions induced by the interpolation. We propose modifications to these tests to effectively eliminate size distortions from such tests conducted on data interpolated from end-of-period sampled low-frequency series. Our results generally do not support linear interpolation when alternatives such as aggregation or mixed-frequency-modified tests are possible.

Suggested Citation

  • Eric Ghysels & J. Isaac Miller, 2014. "On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 14, pages 93-122, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320140000033004
    DOI: 10.1108/S0731-905320140000033004
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    Cited by:

    1. Doré, Natalia I. & Araújo, Eliane, 2025. "Long-term analysis of Kaldor's law applied to Brazil (1909-2020)," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 147-157.
    2. Doré, Natalia I. & Teixeira, Aurora A.C., 2023. "The role of human capital, structural change, and institutional quality on Brazil's economic growth over the last two hundred years (1822–2019)," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 1-12.
    3. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    4. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    5. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    6. J. Isaac Miller, 2019. "Testing Cointegrating Relationships Using Irregular and Non‐Contemporaneous Series with an Application to Paleoclimate Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 936-950, November.
    7. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.
    8. Aurora A. C. Teixeira & Ana Sofia Loureiro, 2019. "FDI, income inequality and poverty: a time series analysis of Portugal, 1973–2016," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 18(3), pages 203-249, October.

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    JEL classification:

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