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ARDL model as a remedy for spurious regression: problems, performance and prospectus

Author

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  • Ghouse, Ghulam
  • Khan, Saud Ahmed
  • Rehman, Atiq Ur

Abstract

Spurious regression have performed a vital role in the construction of contemporary time series econometrics and have developed many tools employed in applied macroeconomics. The conventional Econometrics has limitations in the treatment of spurious regression in non-stationary time series. While reviewing a well-established study of Granger and Newbold (1974) we realized that the experiments constituted in this paper lacked Lag Dynamics thus leading to spurious regression. As a result of this paper, in conventional Econometrics, the Unit root and Cointegration analysis have become the only ways to circumvent the spurious regression. These procedures are also equally capricious because of some specification decisions like, choice of the deterministic part, structural breaks, autoregressive lag length choice and innovation process distribution. This study explores an alternative treatment for spurious regression. We concluded that it is the missing variable (lag values) that are the major cause of spurious regression therefore an alternative way to look at the problem of spurious regression takes us back to the missing variable which further leads to ARDL Model. The study mainly focus on Monte Carlo simulations. The results are providing justification, that ARDL model can be used as an alternative tool to avoid the spurious regression problem.

Suggested Citation

  • 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.
  • Handle: RePEc:pra:mprapa:83973
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    References listed on IDEAS

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    1. Pesaran, M. H. & Shin, Y. & Smith, R. J., 1996. "Testing for the 'Existence of a Long-run Relationship'," Cambridge Working Papers in Economics 9622, Faculty of Economics, University of Cambridge.
    2. Atiq-ur-Rehman, Atiq-ur-Rehman & Zaman, Asad, 2008. "Model specification, observational equivalence and performance of unit root tests," MPRA Paper 13489, University Library of Munich, Germany.
    3. Plosser, Charles I. & Schwert*, G. William, 1978. "Money, income, and sunspots: Measuring economic relationships and the effects of differencing," Journal of Monetary Economics, Elsevier, vol. 4(4), pages 637-660, November.
    4. Rehman, Atiq-ur- & Malik, Muhammad Irfan, 2014. "The Modi ed R a Robust Measure of Association for Time Series," MPRA Paper 60025, University Library of Munich, Germany.
    5. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    6. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    7. Nigar Hashimzade & Michael A. Thornton (ed.), 2013. "Handbook of Research Methods and Applications in Empirical Macroeconomics," Books, Edward Elgar Publishing, number 14327, April.
    8. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    9. Sun, Yixiao, 2004. "A CONVERGENT t-STATISTIC IN SPURIOUS REGRESSIONS," Econometric Theory, Cambridge University Press, vol. 20(5), pages 943-962, October.
    10. HENDRY, David F. & RICHARD, Jean-François, 1983. "The econometric analysis of economic time series," CORE Discussion Papers RP 531, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Ahking, Francis W., 2002. "Model mis-specification and Johansen's co-integration analysis: an application to the US money demand," Journal of Macroeconomics, Elsevier, vol. 24(1), pages 51-66, March.
    12. Carlos Enrique Carrasco Gutiérrez & Reinaldo Castro Souza & Osmani Teixeira de Carvalho Guillén, 2007. "Selection of Optimal Lag Length in Cointegrated VAR Models with Weak Form of Common Cyclical Features," Working Papers Series 139, Central Bank of Brazil, Research Department.
    13. DeJong, David N. & Nankervis, John C. & Savin, N. E. & Whiteman, Charles H., 1992. "The power problems of unit root test in time series with autoregressive errors," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 323-343.
    14. Jen-Je Su, 2008. "A note on spurious regressions between stationary series," Applied Economics Letters, Taylor & Francis Journals, vol. 15(15), pages 1225-1230.
    15. Ventosa-Santaulària, Daniel, 2008. "Spurious Regression," MPRA Paper 59008, University Library of Munich, Germany.
    16. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    17. Pesaran, M Hashem, 1997. "The Role of Economic Theory in Modelling the Long Run," Economic Journal, Royal Economic Society, vol. 107(440), pages 178-191, January.
    18. Chi-Young Choi; Ling Hu; Masao Ogaki, 2004. "A Spurious Regression Approach to Estimating Structural Parameters," Econometric Society 2004 Far Eastern Meetings 555, Econometric Society.
    19. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    20. Uwe Hassler, 2003. "Nonsense regressions due to neglected time-varying means," Statistical Papers, Springer, vol. 44(2), pages 169-182, April.
    21. Hendry, David F. & Pagan, Adrian R. & Sargan, J.Denis, 1984. "Dynamic specification," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 18, pages 1023-1100, Elsevier.
    22. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    23. Gutierrez, Carlos Enrique Carrasco & Souza, Reinaldo Castro & Guillén, Osmani Teixeira de Carvalho, 2009. "Selection of Optimal Lag Length in Cointegrated VAR Models with Weak Form of Common Cyclical Features," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 29(1), May.
    24. Hendry, David F, 1980. "Econometrics-Alchemy or Science?," Economica, London School of Economics and Political Science, vol. 47(188), pages 387-406, November.
    25. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-162, April.
    26. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-692, December.
    27. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    28. Stephen Leybourne & Paul Newbold, 2003. "Spurious rejections by cointegration tests induced by structural breaks," Applied Economics, Taylor & Francis Journals, vol. 35(9), pages 1117-1121.
    29. Dahud Kehinde Shangodoyin & Raghunath Arnab & Oluokun Kasali Agunloye, 2014. "Lag Length Specification in Engle-Granger Cointegration Test: A Modified Koyck Mean Lag Approach Based on Partial Correlation," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(4), pages 559-572, September.
    30. 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.
    31. Wojciech W. Charemza & Derek F. Deadman, 1997. "New Directions In Econometric Practice, Second Edition," Books, Edward Elgar Publishing, number 1139, April.
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    Cited by:

    1. Stephen T. Onifade & Ahmet Ay & Simplice A. Asongu & Festus V. Bekun, 2019. "Revisiting the Trade and Unemployment Nexus: Empirical Evidence from the Nigerian Economy," Working Papers of the African Governance and Development Institute. 19/079, African Governance and Development Institute..
    2. Ghouse, Ghulam & Khan, Saud Ahmed & Habeeb, Kashif, 2019. "Information Transmission Among Equity Markets: A Comparison Between ARDL and GARCH Model," MPRA Paper 97925, University Library of Munich, Germany.

    More about this item

    Keywords

    Spurious regression; misspecification; Stationarity; unit root; cointegration and ARDL;

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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