IDEAS home Printed from https://ideas.repec.org/a/jof/jforec/v22y2003i5p411-426.html
   My bibliography  Save this article

BBVA-ARIES: a forecasting and simulation model for EMU

Author

Listed:
  • Sonsoles Castillo

    (Research Department, BBVA)

  • Fernando C. Ballabriga

    (ESADE, Barcelona, Spain)

Abstract

This paper describes the BBVA-ARIES, a Bayesian vector autoregression (BVAR) for the European Economic and Monetary Union (EMU). In addition to providing EMU-wide growth and inflation forecasts, the model provides an assessment of the interactions between key EMU macroeconomic variables and external ones, such as world GDP or commodity prices. A comparison of the forecasts generated by the model and those of private analysts and public institutions reveals a very positive balance in favour of the model. For their part, the simulations allow us to assess the potential macroeconomic effects of macroeconomic developments in the EMU. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • Sonsoles Castillo & Fernando C. Ballabriga, 2003. "BBVA-ARIES: a forecasting and simulation model for EMU," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 411-426.
    • Handle: RePEc:jof:jforec:v:22:y:2003:i:5:p:411-426
    DOI: 10.1002/for.861
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/for.861
    File Function: Link to full text; subscription required
    Download Restriction: no
    File URL: https://libkey.io/10.1002/for.861?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Luis J. Álvarez & Fernando C. Ballabriga, 1994. "BVAR models in the context of cointegration: A Monte Carlo experiment," Working Papers 9405, Banco de España.
    2. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    3. Fernando C. Ballabriga & Luis Julián Álvarez González & Javier Jareño Morago, 1998. "Un modelo macroeconómico BVAR para la economía española: metodología y resultados," Estudios Económicos, Banco de España, number 64.
    4. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    5. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    6. Artis, Michael J & Zhang, Wenda, 1990. "BVAR Forecasts of the World Economy," CEPR Discussion Papers 380, C.E.P.R. Discussion Papers.
    7. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    8. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Duarte, Agustin & Venetis, Ioannis A. & Paya, Ivan, 2005. "Predicting real growth and the probability of recession in the Euro area using the yield spread," International Journal of Forecasting, Elsevier, vol. 21(2), pages 261-277.

    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. Mr. Matteo Ciccarelli & Mr. Alessandro Rebucci, 2003. "Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System," IMF Working Papers 2003/102, International Monetary Fund.
    2. Andrea Nobili, 2005. "Forecasting Output Growth And Inflation In The Euro Area: Are Financial Spreads Useful?," Temi di discussione (Economic working papers) 544, Bank of Italy, Economic Research and International Relations Area.
    3. Committee, Nobel Prize, 2011. "Thomas J. Sargent and Christopher A. Sims: Empirical Macroeconomics," Nobel Prize in Economics documents 2011-2, Nobel Prize Committee.
    4. Francisco F. R. Ramos, 1996. "VAR Priors: Success or lack of a decent macroeconomic theory?," Econometrics 9601002, University Library of Munich, Germany.
    5. Duo Qin, 2006. "VAR Modelling Approach and Cowles Commission Heritage," Working Papers 557, Queen Mary University of London, School of Economics and Finance.
    6. Peter C.B. Phillips, 1992. "Bayes Methods for Trending Multiple Time Series with an Empirical Application to the US Economy," Cowles Foundation Discussion Papers 1025, Cowles Foundation for Research in Economics, Yale University.
    7. 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.
    8. Carlo A. Favero, 2007. "Model Evaluation in Macroeconometrics: from early empirical macroeconomic models to DSGE models," Working Papers 327, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Research Discussion Papers 4/1991, Bank of Finland.
    10. Jarociński, Marek & Marcet, Albert, 2019. "Priors about observables in vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(2), pages 238-255.
    11. Espinosa Acuña, Óscar A. & Vaca González, Paola A. & Avila Forero, Raúl A., 2013. "Elasticidades de demanda por electricidad e impactos macroecon_omicos del precio de la energía eléctrica en Colombia || Elasticity of Electricity Demand and Macroeconomics Impacts of Electricity Price," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 16(1), pages 216-249, December.
    12. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2014. "Signals from the Government: Policy Uncertainty and the Transmission of Fiscal Shocks," MPRA Paper 56136, University Library of Munich, Germany.
    13. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    14. Jonathan B. Hill, 2007. "Efficient tests of long-run causation in trivariate VAR processes with a rolling window study of the money-income relationship," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 747-765.
    15. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    16. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    17. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2016. "Signals from the government: Policy disagreement and the transmission of fiscal shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 107-118.
    18. Maged Shawky Sourial, 2002. "The Future of the Stock Market Channel In Egypt," Finance 0204002, University Library of Munich, Germany.
    19. 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.
    20. Susi Gorbey & Doug James & Jacques Poot, 1999. "Population Forecasting with Endogenous Migration: An Application to Trans-Tasman Migration," International Regional Science Review, , vol. 22(1), pages 69-101, April.

    More about this item

    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:jof:jforec:v:22:y:2003:i:5:p:411-426. 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: Wiley-Blackwell Digital Licensing or Christopher F. Baum (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    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.