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The modified R a robust measure of association for time series

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  • Rehman, Atiq-ur-
  • Malik, Muhammad Irfan

Abstract

Since times of Yule (1926), it is known that correlation between two time series can produce spurious results. Granger and Newbold (1974) see the roots of spurious correlation in non-stationarity of the time series. However the study of Granger, Hyung and Jeon (2001) prove that spurious correlation also exists in stationary time series. These facts make the correlation coefficient an unreliable measure of association. This paper proposes ‘Modified R’ as an alternate measure of association for the time series. The Modified R is robust to the type of stationarity and type of deterministic part in the time series. The performance Modified R is illustrated via extensive Monte Carlo Experiments.

Suggested Citation

  • Rehman, Atiq-ur- & Malik, Muhammad Irfan, 2014. "The modified R a robust measure of association for time series," MPRA Paper 60025, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:60025
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    File URL: https://mpra.ub.uni-muenchen.de/60025/1/MPRA_paper_60025.pdf
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    References listed on IDEAS

    as
    1. Clive Granger & Namwon Hyung & Yongil Jeon, 2001. "Spurious regressions with stationary series," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 899-904.
    2. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    3. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    4. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    5. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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    Cited by:

    1. Fazal, Rizwan & Rehman, Syed Aziz Ur & Rehman, Atiq Ur & Bhatti, Muhammad Ishaq & Hussain, Anwar, 2021. "Energy-environment-economy causal nexus in Pakistan: A graph theoretic approach," Energy, Elsevier, vol. 214(C).
    2. Ghouse, Ghulam & Khan, Saud Ahmed & Rehman, Atiq Ur, 2018. "ARDL model as a remedy for spurious regression: problems, performance and prospectus," MPRA Paper 83973, University Library of Munich, Germany.
    3. Rizwan Fazal & Syed Aziz Ur Rehman & Muhammad Ishaq Bhatti & Atiq Ur Rehman & Fariha Arooj & Umar Hayat, 2021. "A Cross-Sectoral Investigation of the Energy–Environment–Economy Causal Nexus in Pakistan: Policy Suggestions for Improved Energy Management," Energies, MDPI, vol. 14(17), pages 1-22, September.
    4. Fazal, Rizwan & Bhatti, M. Ishaq & Rehman, Atiq Ur, 2022. "Causality Analysis: The study of Size and Power based on riz-PC Algorithm of Graph Theoretic Approach," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    5. Fazal, Rizwan & Rehman, Syed Aziz Ur & Bhatti, M. Ishaq, 2022. "Graph theoretic approach to expose the energy-induced crisis in Pakistan," Energy Policy, Elsevier, vol. 169(C).

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    More about this item

    Keywords

    Correlation Coefficient; Spurious Regression; Stationary Series;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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