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

Thiago Carlomagno Carlos and Emerson Marçal

No 346, Textos para discussão from FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil)

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

Date: 2013-12-09
New Economics Papers: this item is included in nep-for
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Journal Article: Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:fgv:eesptd:346

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