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Using HP Filtered Data for Econometric Analysis: Some Evidence from Monte Carlo Simulations

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  • Mark Meyer

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  • Peter Winker*

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Abstract

The Hodrick-Prescott (HP) filter has become a widely used tool for detrending integrated time series in applied econometric analysis. Even though the theoretical time series literature sums up an extensive catalogue of severe criticism against an econometric analysis of HP filtered data, the original Hodrick and Prescott (1980, 1997) suggestion to measure the strength of association between (macro-)economic variables by a regression analysis of corresponding HP filtered time series still appears to be popular. A contradictory situation which might be justified only if HP induced distortions were quantitatively negligible in empirical applications. However, this hypothesis can hardly be maintained as the simulation results presented within this paper indicate that HP filtered series give seriously rise to spurious regression results.
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Suggested Citation

  • Mark Meyer & Peter Winker*, 2005. "Using HP Filtered Data for Econometric Analysis: Some Evidence from Monte Carlo Simulations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 89(3), pages 303-320, August.
  • Handle: RePEc:spr:alstar:v:89:y:2005:i:3:p:303-320
    DOI: 10.1007/s10182-005-0206-9
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    1. 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.
    2. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    3. Nelson, Charles R & Kang, Heejoon, 1981. "Spurious Periodicity in Inappropriately Detrended Time Series," Econometrica, Econometric Society, vol. 49(3), pages 741-751, May.
    4. Hilde Christiane BjÛrnland, 2000. "Detrending methods and stylized facts of business cycles in Norway - an international comparison," Empirical Economics, Springer, vol. 25(3), pages 369-392.
    5. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco J., 2005. "Habit formation and the persistence of monetary shocks," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1073-1088, September.
    6. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    7. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    8. Razzak, W., 1997. "The Hodrick-Prescott technique: A smoother versus a filter: An application to New Zealand GDP," Economics Letters, Elsevier, vol. 57(2), pages 163-168, December.
    9. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    10. Alain Guay & Pierre Saint-Amant, 2005. "Do the Hodrick-Prescott and Baxter-King Filters Provide a Good Approximation of Business Cycles?," Annals of Economics and Statistics, GENES, issue 77, pages 133-155.
    11. Smant, David J. C., 1998. "Modelling trends, expectations and the cyclical behaviour of prices," Economic Modelling, Elsevier, vol. 15(1), pages 151-161, January.
    12. Beck, Martin & Winker, Peter, 2004. "Modeling spillovers and feedback of international trade in a disequilibrium framework," Economic Modelling, Elsevier, vol. 21(3), pages 445-470, May.
    13. Singleton, Kenneth J., 1988. "Econometric issues in the analysis of equilibrium business cycle models," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 361-386.
    14. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    15. Christodoulakis, Nicos & Dimelis, Sophia P & Kollintzas, Tryphon, 1995. "Comparisons of Business Cycles in the EC: Idiosyncracies and Regularities," Economica, London School of Economics and Political Science, vol. 62(245), pages 1-27, February.
    16. Fiorito, Riccardo & Kollintzas, Tryphon, 1994. "Stylized facts of business cycles in the G7 from a real business cycles perspective," European Economic Review, Elsevier, vol. 38(2), pages 235-269, February.
    17. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    18. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    19. 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.
    20. Morten O. Ravn & Harald Uhlig, 2002. "On adjusting the Hodrick-Prescott filter for the frequency of observations," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 371-375.
    21. Pedersen, Torben Mark, 2001. "The Hodrick-Prescott filter, the Slutzky effect, and the distortionary effect of filters," Journal of Economic Dynamics and Control, Elsevier, vol. 25(8), pages 1081-1101, August.
    22. Canova, Fabio & Marrinan, Jane, 1998. "Sources and propagation of international output cycles: Common shocks or transmission?," Journal of International Economics, Elsevier, vol. 46(1), pages 133-166, October.
    23. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    24. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.
    25. Weyerstraß, Klaus, 2002. "Der Einfluss der US-amerikanischen Konjunktur auf Deutschland und die Europäische Union - eine Untersuchung mit VAR-Modellen," IWH Discussion Papers 158, Halle Institute for Economic Research (IWH).
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    Cited by:

    1. Brück, Tilman & Xu, Guo, 2012. "Who gives aid to whom and when? Aid accelerations, shocks and policies," European Journal of Political Economy, Elsevier, vol. 28(4), pages 593-606.
    2. Michael Artis & Toshihiro Okubo, 2008. "The Intranational Business Cycle: Evidence from Japan," Centre for Growth and Business Cycle Research Discussion Paper Series 101, Economics, The Univeristy of Manchester.
    3. Löschel Andreas & Oberndorfer Ulrich, 2009. "Oil and Unemployment in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 229(2-3), pages 146-162, April.
    4. Auer Benjamin R., 2012. "Lassen sich CAPM, HCAPM und CCAPM durch konsumbasierte zeitvariable Parameterspezifikation rehabilitieren? / Can Time-varying Parameter Specification Based on Consumption Variables Rehabilitate CAPM, ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(5), pages 518-544, October.
    5. Michael Artis & Toshihiro Okubo, 2011. "The intranational business cycle in Japan," Oxford Economic Papers, Oxford University Press, vol. 63(1), pages 111-133, January.
    6. Michele Piffer & Maximilian Podstawski, 2016. "Identifying Uncertainty Shocks Using the Price of Gold," Discussion Papers of DIW Berlin 1549, DIW Berlin, German Institute for Economic Research.
    7. Flaig Gebhard, 2015. "Why We Should Use High Values for the Smoothing Parameter of the Hodrick-Prescott Filter," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(6), pages 518-538, December.
    8. Staszewska-Bystrova Anna, 2013. "Modified Scheffé’s Prediction Bands," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(5-6), pages 680-690, October.
    9. Gunter Löffler, 2013. "Can rating agencies look through the cycle?," Review of Quantitative Finance and Accounting, Springer, vol. 40(4), pages 623-646, May.
    10. João Sousa Andrade & António Portugal Duarte, 2012. "The Importance of a Good Indicator for Global Exciess Demand," Book Chapters, Institute of Economic Sciences.
    11. Artis, Michael & Okubo, Toshihiro, 2009. "Globalization and business cycle transmission," The North American Journal of Economics and Finance, Elsevier, vol. 20(2), pages 91-99, August.
    12. Kappler Marcus, 2011. "Business Cycle Co-movement and Trade Intensity in the Euro Area: is there a Dynamic Link?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(2), pages 247-265, April.
    13. João Sousa Andrade & António Portugal Duarte, 2014. "Output-gaps in the PIIGS Economies: An Ingredient of a Greek Tragedy," GEMF Working Papers 2014-06, GEMF, Faculty of Economics, University of Coimbra.

    More about this item

    Keywords

    HP filter; spurious regression; detrending; JEL C15; C22;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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