IDEAS home Printed from https://ideas.repec.org/p/bdr/borrec/705.html
   My bibliography  Save this paper

Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case

Author

Listed:
  • Luis Fernando Melo
  • Rubén Albeiro Loaiza Maya

Abstract

Typically, when forecasting inflation rates, there are a variety of individual models and a combination of several of these models. We implement a Bayesian shrinkage combination methodology to include information that is not captured by the individual models using expert forecasts as prior information. To take into account two common characteristics in emerging countries’ economies, possible parameter instabilities and non-stationary dynamics, we use a rolling estimation windows technique for series integrated of order one. The empirical results of Colombian inflation show that the Bayesian forecast combination model outperforms the individual models and the random walk predictions for every evaluated forecast horizon. Moreover, these results outperform shrinkage forecasts that consider other priors as equal or zero weights.

Suggested Citation

  • Luis Fernando Melo & Rubén Albeiro Loaiza Maya, 2012. "Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case," Borradores de Economia 705, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:705
    DOI: 10.32468/be.705
    as

    Download full text from publisher

    File URL: https://doi.org/10.32468/be.705
    Download Restriction: no

    File URL: https://libkey.io/10.32468/be.705?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Gary Koop & Simon M. Potter, 2003. "Forecasting in large macroeconomic panels using Bayesian Model Averaging," Staff Reports 163, Federal Reserve Bank of New York.
    2. Mario Nigrinis Ospina, 2004. "Es lineal la Curva de Phillips en Colombia?," Borradores de Economia 282, Banco de la Republica de Colombia.
    3. Martha Misas Arango & Enrique López Enciso & Pablo Querubín Borrero, 2002. "La inflación en Colombia: una aproximación desde las redes neuronales," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 20(41-42), pages 143-214, June.
    4. Luis Fernando Melo Velandia & Héctor M. Núñez Amortegui, 2004. "Combinación de pronósticos de la inflación en presencia de cambios estructurales," Borradores de Economia 2153, Banco de la Republica.
    5. Diebold, Francis X. & Pauly, Peter, 1990. "The use of prior information in forecast combination," International Journal of Forecasting, Elsevier, vol. 6(4), pages 503-508, December.
    6. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    7. 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.
    8. Munir A. Jalil B. & Luis Fernando Melo Velandia, 2000. "Una Relación No Lineal Entre Inflación Y Medios De Pago," Borradores de Economia 3725, Banco de la Republica.
    9. Wright, Jonathan H., 2008. "Bayesian Model Averaging and exchange rate forecasts," Journal of Econometrics, Elsevier, vol. 146(2), pages 329-341, October.
    10. Munir A. Jalil & Luis Fernando Melo, 2000. "Una Relación no Líneal entre Inflación y los Medios de Pago," Borradores de Economia 145, Banco de la Republica de Colombia.
    11. Miguel I. Gómez & Eliana R. González & Luis F. Melo, 2012. "Forecasting Food Inflation in Developing Countries with Inflation Targeting Regimes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 153-173.
    12. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    13. Elkin Castaño Vélez & Luis Fernando Melo Velandia, 2000. "Metodos de combinacion de pronosticos: una aplicacion a la inflacion," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 52, pages 113-165, Enero Jun.
    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. Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.
    2. Jing Zeng, 2015. "Combining Country-Specific Forecasts when Forecasting Euro Area Macroeconomic Aggregates," Working Paper Series of the Department of Economics, University of Konstanz 2015-11, Department of Economics, University of Konstanz.
    3. Héctor Mauricio Nunez Amortegui, 2005. "Una evaluación de los pronósticos de inflación en Colombia bajo el esquema de inflación objetivo," Revista de Economía del Rosario, Universidad del Rosario, December.
    4. Simionescu, Mihaela, 2014. "Bayesian Forecasts Combination To Improve The Romanian Inflation Predictions Based On Econometric Models," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 5(2), pages 131-140.
    5. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    6. Andrés M. Alonso & Guadalupe Bastos & Carolina García-Martos, 2016. "Electricity Price Forecasting by Averaging Dynamic Factor Models," Energies, MDPI, vol. 9(8), pages 1-21, July.
    7. Jing Zeng, 2016. "Combining country-specific forecasts when forecasting Euro area macroeconomic aggregates," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 43(2), pages 415-444, May.
    8. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317974, HAL.
    9. Drechsel, Katja & Scheufele, Rolf, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10/2010, Halle Institute for Economic Research (IWH).
    10. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
    11. Samuels, Jon D. & Sekkel, Rodrigo M., 2017. "Model Confidence Sets and forecast combination," International Journal of Forecasting, Elsevier, vol. 33(1), pages 48-60.
    12. Yoonseok Lee & Donggyu Sul, 2023. "Depth-weighted Forecast Combination: Application to COVID-19 Cases," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 235-260, Emerald Group Publishing Limited.
    13. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
    14. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
    15. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    16. Eliana González, 2010. "Bayesian Model Averaging. An Application to Forecast Inflation in Colombia," Borradores de Economia 7013, Banco de la Republica.
    17. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    18. Chen Yu-Chin & Rogoff Kenneth, 2012. "Are The Commodity Currencies An Exception To The Rule?," Global Journal of Economics (GJE), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 1-28.
    19. Katja Drechsel & Laurent Maurin, 2011. "Flow of conjunctural information and forecast of euro area economic activity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 336-354, April.
    20. Joshua Gallin & Randal Verbrugge, 2007. "Improving the CPI’s Age-Bias Adjustment: Leverage, Disaggregation and Model Averaging," Working Papers 411, U.S. Bureau of Labor Statistics.

    More about this item

    Keywords

    Forecast combination; Shrinkage; Expert forecasts; Rolling window estimation; Inflation forecasts.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bdr:borrec:705. 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: Clorith Angélica Bahos Olivera (email available below). General contact details of provider: https://edirc.repec.org/data/brcgvco.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.