IDEAS home Printed from https://ideas.repec.org/p/ucm/doicae/9310.html
   My bibliography  Save this paper

Recursive identification, estimation and forecasting of nonstationary economic time series with applications to GNP international data

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

En este trabajo proponemos un modelo novedoso de componentes no observables para las variaciones en el PNB anual en varios países. El modelo se formula en espacio de los estados y se estima mediante procedimientos recursivos de filtrado y de suavizado con la muestra completa. Se analiza el producto real anual de nueve países a partir del modelo de componentes no observables en sus versiones univariante y de función de transferencia, utilizando en esta última versión la oferta monetaria como indicador adelantado. Se compara el comportamiento de las predicciones de estos modelos con las obtenidas en trabajos anteriores utilizando el mismo conjunto de datos.

Suggested Citation

  • Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Recursive identification, estimation and forecasting of nonstationary economic time series with applications to GNP international data," Documentos de Trabajo del ICAE 9310, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    • Handle: RePEc:ucm:doicae:9310
    as

    Download full text from publisher

    File URL: https://eprints.ucm.es/id/eprint/28298/1/9310.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Litterman, Robert B, 1986. "A Statistical Approach to Economic Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 1-4, January.
    2. 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.
    3. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
    4. ZELLNER, Arnold & PALM, Franz, 1975. "Time series and structural analysis of monetary models of the U.S. economy," LIDAM Reprints CORE 247, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Mittnik, Stefan, 1990. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 205-208, April.
    6. Genshiro Kitagawa, 1981. "A Nonstationary Time Series Model And Its Fitting By A Recursive Filter," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(2), pages 103-116, March.
    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. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
    2. Cubadda, G. & Hecq, A.W. & Palm, F.C., 2007. "Studying co-movements in large multivariate models without multivariate modelling," Research Memorandum 032, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    3. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
    4. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
    5. Pena, Daniel & Poncela, Pilar, 2004. "Forecasting with nonstationary dynamic factor models," Journal of Econometrics, Elsevier, vol. 119(2), pages 291-321, April.
    6. Ribeiro Ramos, Francisco Fernando, 2003. "Forecasts of market shares from VAR and BVAR models: a comparison of their accuracy," International Journal of Forecasting, Elsevier, vol. 19(1), pages 95-110.
    7. Hecq, A.W. & Laurent, S.F.J.A. & Palm, F.C., 2011. "On the univariate representation of multivariate volatility models with common factors," Research Memorandum 011, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    8. Hecq Alain & Palm Franz C. & Laurent Sébastien, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 91-113, July.
    9. Justin L. Tobias & Mingliang Li, 2003. "A finite-sample hierarchical analysis of wage variation across public high schools: evidence from the NLSY and high school and beyond," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 315-336.
    10. Guangling 'Dave' Liu & Rangan Gupta & Eric Schaling, 2009. "A New-Keynesian DSGE model for forecasting the South African economy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 387-404.
    11. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    12. Umberto Triacca, 2016. "Measuring the Distance between Sets of ARMA Models," Econometrics, MDPI, vol. 4(3), pages 1-11, July.
    13. Fushing Hsieh & Emilio Ferrer & Shu-Chun Chen & Sy-Miin Chow, 2010. "Exploring the Dynamics of Dyadic Interactions via Hierarchical Segmentation," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 351-372, June.
    14. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    15. Kazimi, Camilla & Brownstone, David, 1999. "Bootstrap confidence bands for shrinkage estimators," Journal of Econometrics, Elsevier, vol. 90(1), pages 99-127, May.
    16. Rangan Gupta & Stephen Miller, 2012. "“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(3), pages 763-782, June.
    17. Víctor Gómez & Félix Aparicio‐Pérez, 2009. "A new state–space methodology to disaggregate multivariate time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 97-124, January.
    18. Pami Dua & Nishita Raje & Satyananda Sahoo, 2004. "Interest Rate Modeling and Forecasting in India," Occasional papers 3, Centre for Development Economics, Delhi School of Economics.
    19. Emmanuel Apergis & Nicholas Apergis, 2021. "The impact of COVID-19 on economic growth: evidence from a Bayesian Panel Vector Autoregressive (BPVAR) model," Applied Economics, Taylor & Francis Journals, vol. 53(58), pages 6739-6751, December.

    More about this item

    Keywords

    Annual real output.;

    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:9310. 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.