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

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  • Carlos, Thiago Carlomagno
  • Marçal, Emerson Fernandes

Abstract

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

Suggested Citation

  • Carlos, Thiago Carlomagno & Marçal, Emerson Fernandes, 2013. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Textos para discussão 346, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    • Handle: RePEc:fgv:eesptd:346
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    Cited by:

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    3. Carlos Medel, 2021. "Forecasting Brazilian Inflation with the Hybrid New Keynesian Phillips Curve: Assessing the Predictive Role of Trading Partners," Working Papers Central Bank of Chile 900, Central Bank of Chile.
    4. Olofin, S.O. & Salisu, A.A & Tule, M.K, 2020. "Revised Small Macro-Econometric Model Of The Nigerian Economy," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 20(1), pages 97-116.

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