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Un modelo de proyección BVAR para la inflación peruana

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  • Llosa, Gonzalo
  • Tuesta, Vicente
  • Vega, Marco

Abstract

Se construye un marco simple de proyección no estructural BVAR para proyectar datos macroeconómicos claves de la economía peruana, en particular la inflación y el producto. A manera de contribución, con relación a aplicaciones estándar, se propone una especificación de priors a la Litterman, en la cual se considera que la estructura que conduce la dinámica de la economía se ha desplazado hacia un régimen de metas de inflación. Se comparan varias especificaciones BVAR contra un modelo de proyección de paseo aleatorio y se encuentra que las primeras tienen una buena performance relativa en términos de proyecciones de inflación para todos los horizontes. Sin embargo, las proyecciones de crecimiento del PBI no llegan a superar claramente al modelo de paseo aleatorio.

Suggested Citation

  • Llosa, Gonzalo & Tuesta, Vicente & Vega, Marco, 2006. "Un modelo de proyección BVAR para la inflación peruana," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 13.
  • Handle: RePEc:rbp:esteco:ree-13-02
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    File URL: http://www.bcrp.gob.pe/docs/Publicaciones/Revista-Estudios-Economicos/13/Estudios-Economicos-13-2.pdf
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    References listed on IDEAS

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    1. Lars E O Svensson, 2005. "Monetary Policy with Judgment: Forecast Targeting," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    2. Armas, Adrián & Grippa, Francisco & Quispe, Zenón & Valdivia, Luis, 2001. "De metas monetarias a metas de inflación en una economía con dolarización parcial: El caso peruano," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 7.
    3. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    4. Winkelried, Diego, 2003. "Hacia una meta explícita de inflación: Anticipando la inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 9, pages 11-40.
    5. Eric M. Leeper & Jennifer E. Roush, 2003. "Putting "M" back in monetary policy," Proceedings, Federal Reserve Bank of Cleveland, pages 1217-1264.
    6. 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.
    7. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18.
    8. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    9. Luque, Javier & Vega, Marco, 2003. "Usando un modelo semi-estructural de pequeña escala para hacer proyecciones: Algunas consideraciones," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 10.
    10. Zenón Quispe, 2000. "Monetary Policy in a Dollarized Economy: the Case of Peru," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, vol. 0(2), pages 167-206, July-Dece.
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    Cited by:

    1. Carlos Garcia & Pablo Gonzalez & Antonio Moncado, 2010. "Proyecciones Macroeconómicas en Chile: Una Aproximación Bayesiana," ILADES-Georgetown University Working Papers inv262, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines.

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