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Inflación e incertidumbre inflacionaria: la postura del Banco de México, 1969-2017

Author

Listed:
  • Eduardo Rosas Rojas
  • Teresa López González

Abstract

Este artículo examina la relación entre inflación e incertidumbre inflacionaria para la economía de México durante el periodo que comprende enero de 1969 a febrero de 2017, utilizando modelos SARMA-GARCH y sus extensiones GJR-GARCH-M y E-GARCH-M. Entre los hallazgos es posible evidenciar un efecto causal negativo de la incertidumbre inflacionaria sobre la inflación (cumplimiento de la hipótesis de Holland), lo cual indica que el Banco de México exhibe un comportamiento estabilizador ante la inflación. También se corrobora el cumplimiento de la hipótesis de Friedman-Ball, que establece que altos niveles de inflación incrementan la incertidumbre inflacionaria.

Suggested Citation

  • Eduardo Rosas Rojas & Teresa López González, 2018. "Inflación e incertidumbre inflacionaria: la postura del Banco de México, 1969-2017," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 10(2), pages 349-372, November.
    • Handle: RePEc:col:000443:016929
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    References listed on IDEAS

    as
    1. Luca Benati & Paolo Surico, 2008. "Evolving U.S. Monetary Policy and The Decline of Inflation Predictability," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 634-646, 04-05.
    2. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521721684.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Baillie, Richard T & Chung, Ching-Fan & Tieslau, Margie A, 1996. "Analysing Inflation by the Fractionally Integrated ARFIMA-GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 23-40, Jan.-Feb..
    5. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955.
    6. Ana María Aguilar Argaez & Gabriel Cuadra & Claudia Ramírez Bulos & Daniel Sámano Peñaloza, 2014. "Anclaje de las expectativas de inflación ante choques de oferta adversos," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(1), pages 55-89, enero-jun.
    7. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    8. Bojanic, Antonio N., 2013. "Inflación e incertidumbre inflacionaria en Bolivia," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(318), pages 401-426, abril-jun.
    9. Alesina, Alberto & Summers, Lawrence H, 1993. "Central Bank Independence and Macroeconomic Performance: Some Comparative Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(2), pages 151-162, May.
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    More about this item

    Keywords

    Banco Central; efectos asimétricos; incertidumbre inflacionaria; inflación.;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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