IDEAS home Printed from https://ideas.repec.org/p/ucm/doicae/9312.html
   My bibliography  Save this paper

Further evidence on forecasting international GNP growth rates using unobserved components transfer function models

Author

Listed:
  • Antonio García Ferrer

    (Dpto. de Análisis Económico, Universidad Autónoma de Madrid.)

  • Juan del Hoyo Bernat

    (Dpto. de Análisis Económico, Universidad Autónoma de Madrid.)

  • Peter C. Young

    (Environmental Science Division, Lancaster University, U.K.)

  • Alfonso Novales Cinca

    (Instituto Complutense de Análisis Económico, Universidad Complutense, Madrid.)

Abstract

Forecast of international GNP growth rates are computed using a novel, onobserved components model that allows for estimating the trend and the perturbational components in GNPdata. The model is formulated in state space terms, and estimating using recursive methods of filtering and fixed interval smoothing, The decomposition crucially hinges on the choice of the Noise-Variance Ratio parameter. As any other signal extraction method, the choice of the relevants parameters affects the statistical characteristics of the estimated components. Here, we incororate a priori beliefs on the values of the NVR parameter leading to a decomposition with reasonable business cycle properties. Throughout the paper, forecast comparisons are made with other Bayesian and non-Bayesian alternatives.

Suggested Citation

  • Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Further evidence on forecasting international GNP growth rates using unobserved components transfer function models," Documentos de Trabajo del ICAE 9312, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    • Handle: RePEc:ucm:doicae:9312
    as

    Download full text from publisher

    File URL: https://eprints.ucm.es/id/eprint/28457/1/9312.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    2. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-174, Summer.
    3. Zellner, Arnold & Hong, Chansik, 1989. "Forecasting international growth rates using Bayesian shrinkage and other procedures," Journal of Econometrics, Elsevier, vol. 40(1), pages 183-202, January.
    4. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    5. 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.
    6. 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.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nelson, Charles R., 1988. "Spurious trend and cycle in the state space decomposition of a time series with a unit root," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 475-488.
    2. Michael A. Kouparitsas, 1999. "Is there evidence of the new economy in the data?," Working Paper Series WP-99-22, Federal Reserve Bank of Chicago.
    3. Frédéric Dufourt, 2005. "Demand and Productivity Components of Business Cycles : Estimates and Implications," Working Papers halshs-00789009, HAL.
    4. Dufourt, Frederic, 2005. "Demand and productivity components of business cycles: Estimates and implications," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1089-1105, September.
    5. 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.
    6. Schlitzer, Giuseppe, 1995. "Testing the stationarity of economic time series: further Monte Carlo evidence," Ricerche Economiche, Elsevier, vol. 49(2), pages 125-144, June.
    7. Emara, Noha & Ma, Jinpeng, 2019. "An Analysis of the Seasonal Cycle and the Business Cycle," MPRA Paper 99310, University Library of Munich, Germany.
    8. Ángel Guillén & Gabriel Rodríguez, 2014. "Trend-cycle decomposition for Peruvian GDP: application of an alternative method," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-44, December.
    9. Willie Lahari, 2011. "Assessing Business Cycle Synchronisation - Prospects for a Pacific Islands Currency Union," Working Papers 1110, University of Otago, Department of Economics, revised Oct 2011.
    10. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    11. Leo Butler, 1996. "The Bank of Canada's New Quarterly Porjection Model Part 4 : A Semi- Structural Method to Estimate Potential Output : Combining Economic Theory with a Time-Series Filter," Technical Reports 77, Bank of Canada.
    12. Arkadiusz Kijek, 2017. "Spectral analysis of business cycles in Poland and its major trading partners," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 57-75.
    13. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    14. Robert Dixon & G.C. Lim, 2004. "Underlying Inflation in Australia: Are the Existing Measures Satisfactory?," The Economic Record, The Economic Society of Australia, vol. 80(251), pages 373-386, December.
    15. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
    16. Myroslav Pidkuyko, 2014. "Dynamics of Consumption and Dividends over the Business Cycle," CERGE-EI Working Papers wp522, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    17. Quah, Danny, 1992. "The Relative Importance of Permanent and Transitory Components: Identification and Some Theoretical Bounds," Econometrica, Econometric Society, vol. 60(1), pages 107-118, January.
    18. Morana, Claudio, 2024. "A new macro-financial condition index for the euro area," Econometrics and Statistics, Elsevier, vol. 29(C), pages 64-87.
    19. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    20. Hilde Christiane Bjørnland, 1999. "Structural breaks and stochastic trends in macroeconomic variables in Norway," Applied Economics Letters, Taylor & Francis Journals, vol. 6(3), pages 133-138.

    More about this item

    Keywords

    GNP; PIB/PNB.;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ucm:doicae:9312. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Águeda González Abad (email available below). General contact details of provider: https://edirc.repec.org/data/feucmes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.