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Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon

  • Carlos, Thiago C.
  • Marçal, Emerson Fernandes

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian Consumer inflation (IPCA). We will compare forecasting models using disaggregated and aggregated data over twelve months ahead. The disaggregated models were estimated by SARIMA and will have different levels of disaggregation. Aggregated models will be estimated by time series techniques such as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy comparison will be made by the selection model procedure known as Model Confidence Set and by Diebold-Mariano procedure. We were able to find evidence of forecast accuracy gains in models using more disaggregated data

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Paper provided by Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil) in its series Textos para discussão with number 346.

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Date of creation: 09 Dec 2013
Date of revision:
Handle: RePEc:fgv:eesptd:346
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  1. Elano Ferreira Arruda & Roberto Tatiwa Ferreira & Ivan Castelar, 2008. "Modelos lineares e não lineares da curva de Phillips para previsão da taxa de Inflação no Brasil," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211607140, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
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  6. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
  7. Martin Evans & Paul Wachtel, 1993. "Inflation regimes and the sources of inflation uncertainty," Proceedings, Federal Reserve Bank of Cleveland, pages 475-520.
  8. David F. Hendry & Kirstin Hubrich, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 216-227, April.
  9. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
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  19. repec:fip:fedgsq:y:2007:i:jul10 is not listed on IDEAS
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