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Comovements in Large Systems

Author

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  • GONZALO, Jesus

    (Department of Economics, Boston University)

  • PITARAKIS, Jean-Yves

    (CORE, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium)

Abstract

In this paper we study various methods for detecting the co integrating rank as the number of variables gets large. We show that the use of standard tools will always lead to misleading inferences in such settings due to excessive size distortions. Particularly the LR test tends to produce too much cointegration. We introduce a new test statistic that displays excellent size properties in both small and large systems. In addition we propose a model selection procedure for selecting the cointegrating rank. A new criterion outperforms the standard information-theoretic criteria (AIC, BIC).

Suggested Citation

  • GONZALO, Jesus & PITARAKIS, Jean-Yves, 1994. "Comovements in Large Systems," LIDAM Discussion Papers CORE 1994065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:1994065
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    References listed on IDEAS

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    Cited by:

    1. Onatski, Alexei & Wang, Chen, 2019. "Extreme canonical correlations and high-dimensional cointegration analysis," Journal of Econometrics, Elsevier, vol. 212(1), pages 307-322.
    2. Alexei Onatski & Chen Wang, 2018. "Alternative Asymptotics for Cointegration Tests in Large VARs," Econometrica, Econometric Society, vol. 86(4), pages 1465-1478, July.
    3. Marie-Josée Godbout & Simon van Norden, 1997. "Reconsidering Cointegration in International Finance: Three Case Studies of Size Distortion in Finite Samples," Staff Working Papers 97-1, Bank of Canada.
    4. Jesús Gonzalo & Jean‐Yves Pitarakis, 2002. "Lag length estimation in large dimensional systems," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 401-423, July.
    5. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2021. "Spurious relationships in high-dimensional systems with strong or mild persistence," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1480-1497.
    6. Alfredo Marvão Pereira and Rui Manuel Pereira, 2020. "Infrastructure Investment, Labor Productivity, and International Competitiveness: The Case of Portugal," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 45(2), pages 1-29, June.
    7. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    8. Rabindra Nepal and John Foster, 2016. "Testing for Market Integration in the Australian National Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    9. Tu, Yundong & Yao, Qiwei & Zhang, Rongmao, 2020. "Error-correction factor models for high-dimensional cointegrated time series," LSE Research Online Documents on Economics 106994, London School of Economics and Political Science, LSE Library.
    10. Gonzalo, Jesus & Pitarakis, Jean-Yves, 1998. "Specification via model selection in vector error correction models," Economics Letters, Elsevier, vol. 60(3), pages 321-328, September.
    11. Marie-Josée Godbout & Simon van Norden, 1996. "Unit-Root Test and Excess Returns," Staff Working Papers 96-10, Bank of Canada.
    12. Anna Bykhovskaya & Vadim Gorin, 2022. "Asymptotics of Cointegration Tests for High-Dimensional VAR($k$)," Papers 2202.07150, arXiv.org, revised Nov 2023.
    13. Lee, Tae-Hwy & Tse, Yiuman, 1996. "Cointegration tests with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 73(2), pages 401-410, August.
    14. Ho, Mun S & Sorensen, Bent E, 1996. "Finding Cointegration Rank in High Dimensional Systems Using the Johansen Test: An Illustration Using Data Based Monte Carlo Simulations," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 726-732, November.

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    More about this item

    Keywords

    cointegration; information criteria; large systems; likelihood ratio tests;
    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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