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Forecasting Food Inflation in Developing Countries with Inflation Targeting Regimes


  • Miguel I. Gómez
  • Eliana R. González
  • Luis F. Melo


Developing countries that employ inflation-targeting monetary policy regimes require accurate short-run food inflation forecasts. We develop a systematic approach to improve food inflation forecasts, apply it to Colombian monthly data from December 1989 to April 2006, and show its relevance for inflation targeting regimes. Forecast accuracy can be improved by: disaggregating food products into away-from-home, processed and fresh foods; employing econometric methods to combine forecasts from individual models; and using flexible least squares methods in the presence of structural changes. We also show the importance of accurate food inflation forecasts in models simulating monetary policy transmission.AMS Subject Classification ,, Copyright 2012, Oxford University Press.

Suggested Citation

  • 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.
  • Handle: RePEc:oup:ajagec:v:94:y:2012:i:1:p:153-173

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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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