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Cointegration and sampling frequency

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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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    1. Hooker, Mark A., 1993. "Testing for cointegration : Power versus frequency of observation," Economics Letters, Elsevier, vol. 41(4), pages 359-362.
    2. Shiller, Robert J. & Perron, Pierre, 1985. "Testing the random walk hypothesis : Power versus frequency of observation," Economics Letters, Elsevier, vol. 18(4), pages 381-386.
    3. Phillips, P.C.B., 1989. "Partially Identified Econometric Models," Econometric Theory, Cambridge University Press, vol. 5(2), pages 181-240, August.
    4. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 99-125.
    5. Bergstrom, A.R., 1984. "Continuous time stochastic models and issues of aggregation over time," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 20, pages 1145-1212, Elsevier.
    6. Perron, Pierre, 1991. "Test Consistency with Varying Sampling Frequency," Econometric Theory, Cambridge University Press, vol. 7(3), pages 341-368, September.
    7. Otero, Jesus & Smith, Jeremy, 2000. "Testing for cointegration: power versus frequency of observation -- further Monte Carlo results," Economics Letters, Elsevier, vol. 67(1), pages 5-9, April.
    8. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    9. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.
    10. Lahiri, Kajal & Mamingi, Nlandu, 1995. "Testing for cointegration: Power versus frequency of observation -- another view," Economics Letters, Elsevier, vol. 49(2), pages 121-124, August.
    11. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    12. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 8(4), pages 489-500, December.
    13. Chambers, Marcus J., 2001. "Temporal Aggregation And The Finite Sample Performance Of Spectral Regression Estimators In Cointegrated Systems," Econometric Theory, Cambridge University Press, vol. 17(3), pages 591-607, June.
    14. McCrorie, J. Roderick, 2000. "Deriving The Exact Discrete Analog Of A Continuous Time System," Econometric Theory, Cambridge University Press, vol. 16(6), pages 998-1015, December.
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    Cited by:

    1. 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..
    2. 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.
    3. Herzer, Dierk, 2013. "Cross-Country Heterogeneity and the Trade-Income Relationship," World Development, Elsevier, vol. 44(C), pages 194-211.
    4. 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.
    5. 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.
    6. 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 (IfW Kiel), vol. 9, pages 1-56.
    7. 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.
    8. 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).
    9. 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.
    10. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    18. 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.

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