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Demand for Money: A Study in Testing Time Series for Long Memory and Nonlinearity

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Author Info

  • Derek Bond

    (University of Ulster)

  • Michael J. Harrison

    (Trinity College Dublin)

  • Edward J. O'Brien

    (European Central Bank)

Abstract

This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applying them, selected techniques are applied to a demand for money dataset. Comparisons of the results from this illustrative case study are presented, and conclusions are drawn that should aid practitioners in applied time-series econometrics.

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File URL: http://www.esr.ie/Vol38_1/bond.pdf
File Function: First version, 2007
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Bibliographic Info

Article provided by Economic and Social Studies in its journal Economic and Social Review.

Volume (Year): 38 (2007)
Issue (Month): 1 ()
Pages: 1-24

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Handle: RePEc:eso:journl:v:38:y:2007:i:1:p:1-24

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References

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  1. Peter C.B. Phillips, 2003. "Laws and Limits of Econometrics," Cowles Foundation Discussion Papers 1397, Cowles Foundation for Research in Economics, Yale University.
  2. Laura Mayoral, 2005. "Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks," Economics Working Papers 956, Department of Economics and Business, Universitat Pompeu Fabra.
  3. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is what?: A simple time-domain test of long-memory vs. structural breaks," Economics Working Papers 954, Department of Economics and Business, Universitat Pompeu Fabra.
  4. Shi-Miin Liu & Chih-Hsien Chou, 2003. "Parities and Spread Trading in Gold and Silver Markets: A Fractional Cointegration Analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 899-911.
  5. Walter Kramer & Philipp Sibbertsen, 2002. "Testing for Structural Changes in the Presence of Long Memory," International Journal of Business and Economics, College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 1(3), pages 235-242, December.
  6. In Choi & Pentti Saikkonen, 2004. "Testing linearity in cointegrating smooth transition regressions," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 341-365, December.
  7. Dahl, Christian M. & Hylleberg, Svend, 2004. "Flexible regression models and relative forecast performance," International Journal of Forecasting, Elsevier, vol. 20(2), pages 201-217.
  8. Dittmann, Ingolf, 2000. "Error correction models for fractionally cointegrated time series," Technical Reports 2000,02, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  9. Nelson C. Mark & Donggyu Sul, 2003. "Cointegration Vector Estimation by Panel DOLS and Long-run Money Demand," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 655-680, December.
  10. Serena Ng & Pierre Perron, 1997. "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Boston College Working Papers in Economics 369, Boston College Department of Economics, revised 01 Sep 2000.
  11. Neil R. Ericsson & James G. MacKinnon, 1999. "Distributions of error correction tests for cointegration," International Finance Discussion Papers 655, Board of Governors of the Federal Reserve System (U.S.).
  12. A. Mansur & M. Masih & Rumi Masih, 2004. "Fractional cointegration, low frequency dynamics and long-run purchasing power parity: an analysis of the Australian dollar over its recent float," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 593-605.
  13. Francis X. Diebold & Atsushi Inoue, 2000. "Long Memory and Regime Switching," NBER Technical Working Papers 0264, National Bureau of Economic Research, Inc.
  14. Luis A. Gil-Alana, 2003. "Testing of Fractional Cointegration in Macroeconomic Time Series," Faculty Working Papers 09/03, School of Economics and Business Administration, University of Navarra.
  15. Alex Maynard & Peter C. B. Phillips, 2001. "Rethinking an old empirical puzzle: econometric evidence on the forward discount anomaly," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 671-708.
  16. Baillie, Richard T. & Bollerslev, Tim, 2000. "The forward premium anomaly is not as bad as you think," Journal of International Money and Finance, Elsevier, vol. 19(4), pages 471-488, August.
  17. Dahl, Christian M. & Gonzalez-Rivera, Gloria, 2003. "Testing for neglected nonlinearity in regression models based on the theory of random fields," Journal of Econometrics, Elsevier, vol. 114(1), pages 141-164, May.
  18. Hamilton, James D, 2001. "A Parametric Approach to Flexible Nonlinear Inference," Econometrica, Econometric Society, vol. 69(3), pages 537-73, May.
  19. Fiess, Norbert & MacDonald, Ronald, 2001. " The Instability of the Money Demand Function: An I(2) Interpretation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(4), pages 475-95, September.
  20. Bond Derek & Harrison Michael J. & O'Brien Edward J., 2005. "Investigating Nonlinearity: A Note on the Estimation of Hamilton's Random Field Regression Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(3), pages 1-43, September.
  21. Christian M. Dahl, 2002. "An investigation of tests for linearity and the accuracy of likelihood based inference using random fields," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 263-284, 06.
  22. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "Testing I(1) against I(d) alternatives in the presence of deteministic components," Economics Working Papers 957, Department of Economics and Business, Universitat Pompeu Fabra.
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Cited by:
  1. Gerlach-Kristen, Petra & O'Connell, Brian & O'Toole, Conor, 2013. "How do banking crises affect aggregate consumption? Evidence from international crisis episodes," Papers WP464, Economic and Social Research Institute (ESRI).

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