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

  • Carlos, Thiago Carlomagno
  • 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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