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Cointegration and sampling frequency

Author

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  • Marcus J. Chambers

Abstract

This paper analyses the effects of sampling frequency on the properties of spectral regression estimators of cointegrating parameters. Large sample asymptotic properties are derived under three scenarios concerning the span of data and sampling frequency, each scenario depending on whether span or frequency (or both) tends to infinity. The limiting distributions are shown to be different in each case. Furthermore, the asymptotic efficiency of the estimators obtained with a fixed sampling frequency is compared with that obtained with a continuous record of data, and it is shown that the only inefficiencies arise with respect to stock variables. Some simulation results and an empirical illustration are also provided.
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Suggested Citation

  • Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    • Handle: RePEc:ect:emjrnl:v:14:y:2011:i:2:p:156-185
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    Cited by:

    1. J. Isaac Miller & Xi Wang, 2016. "Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 810-824, November.
    2. Hoffmann, Clemens & von Cramon-Taubadel, Stephan, 2023. "The Effects of Temporal Data Aggregation on Price Transmission Analysis," 2023 Conference, April 24-25, 2023, St. Louis, Missouri 379022, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    3. Gustavo Fruet Dias & Karsten Schweiker, 2024. "Integrated Variance Estimation for Assets Traded in Multiple Venues," University of East Anglia School of Economics Working Paper Series 2024-04, School of Economics, University of East Anglia, Norwich, UK..
    4. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    5. Dierk Herzer & Holger Strulik, 2017. "Religiosity and income: a panel cointegration and causality analysis," Applied Economics, Taylor & Francis Journals, vol. 49(30), pages 2922-2938, June.
    6. Nicole Grunewald & Inmaculada Martínez-Zarzoso, 2014. "Green Growth in Mexico, Brazil and Chile: Policy strategies and future prospects," Ibero America Institute for Econ. Research (IAI) Discussion Papers 229, Ibero-America Institute for Economic Research.
    7. Herzer, Dierk & Nunnenkamp, Peter, 2015. "Income inequality and health: Evidence from developed and developing countries," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, vol. 9, pages 1-56.
    8. Eric Ghysels & J. Isaac Miller, 2015. "Testing for Cointegration with Temporally Aggregated and Mixed-Frequency Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 797-816, November.
    9. Ewald, Christian & Hadina, Jelena & Haugom, Erik & Lien, Gudbrand & Størdal, Ståle & Yahya, Muhammad, 2023. "Sample frequency robustness and accuracy in forecasting Value-at-Risk for Brent Crude Oil futures," Finance Research Letters, Elsevier, vol. 58(PA).
    10. Partha Ray & Vinodh Madhavan, 2014. "Price and Volatility Linkages between Indian Stocks and their European GDRs," Proceedings of International Academic Conferences 0300812, International Institute of Social and Economic Sciences.
    11. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    12. Marcus J. Chambers & J. Roderick McCrorie & Michael A. Thornton, 2018. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Springer Books, in: Kees van Montfort & Johan H. L. Oud & Manuel C. Voelkle (ed.), Continuous Time Modeling in the Behavioral and Related Sciences, chapter 0, pages 317-357, Springer.
    13. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    14. 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.
    15. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.
    16. Dierk Herzer & Holger Strulik & Sebastian Vollmer, 2012. "The long-run determinants of fertility: one century of demographic change 1900–1999," Journal of Economic Growth, Springer, vol. 17(4), pages 357-385, December.
    17. Herzer, Dierk, 2013. "Cross-Country Heterogeneity and the Trade-Income Relationship," World Development, Elsevier, vol. 44(C), pages 194-211.
    18. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    19. Cui, Xiaomeng & Gafarov, Bulat & Ghanem, Dalia & Kuffner, Todd, 2024. "On model selection criteria for climate change impact studies," Journal of Econometrics, Elsevier, vol. 239(1).

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