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Three new empirical perspectives on the Hodrick–Prescott parameter

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  • Kosei Fukuda

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  • Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    • Handle: RePEc:spr:empeco:v:39:y:2010:i:3:p:713-731
    DOI: 10.1007/s00181-009-0332-4
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    References listed on IDEAS

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    1. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    2. Assenmacher-Wesche, Katrin & Gerlach, Stefan, 2008. "Money growth, output gaps and inflation at low and high frequency: Spectral estimates for Switzerland," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 411-435, February.
    3. Albert Marcet & Morte O. Ravn, "undated". "The HP-Filter in Cross-Country Comparisons," Studies on the Spanish Economy 100, FEDEA.
    4. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    5. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    6. Fuhrer, Jeff & Tootell, Geoff, 2008. "Eyes on the prize: How did the fed respond to the stock market?," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 796-805, May.
    7. Camba-Mendez, Gonzalo & Rodriguez-Palenzuela, Diego, 2003. "Assessment criteria for output gap estimates," Economic Modelling, Elsevier, vol. 20(3), pages 529-562, May.
    8. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    9. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 299-307, October.
    10. Kosei Fukuda, 2006. "Age-period-cohort decomposition of aggregate data: an application to US and Japanese household saving rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 981-998.
    11. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study: Response," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 313-315, October.
    12. Afonso, António & Furceri, Davide, 2008. "EMU enlargement, stabilization costs and insurance mechanisms," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 169-187, March.
    13. 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.
    14. Canova, Fabio, 1994. "Detrending and turning points," European Economic Review, Elsevier, vol. 38(3-4), pages 614-623, April.
    15. 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.
    16. J. Z. Easaw & S. M. Heravi & J. C. K. Ash & D. J. Smyth, 2002. "Are Hodrick-Prescott `forecasts' rational?," Empirical Economics, Springer, vol. 27(4), pages 631-643.
    17. 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.
    18. 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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    Citations

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    Cited by:

    1. Kristian Jönsson, 2017. "Restricted Hodrick–Prescott filtering in a state-space framework," Empirical Economics, Springer, vol. 53(3), pages 1243-1251, November.
    2. Fukuda, Kosei, 2012. "Illustrating extraordinary shocks causing trend breaks," Economic Modelling, Elsevier, vol. 29(4), pages 1045-1052.

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    More about this item

    Keywords

    Bayesian smoothness solution; Empirical perspective: Hodrick–Prescott filter; Multistep ahead forecasting; Output gap; C22; E32;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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