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

dc.contributor.authorCarlos, Thiago Carlomagno
dc.contributor.authorMarçal, Emerson Fernandes
dc.contributor.unidadefgvEscolas::EESPpor
dc.date.accessioned2013-12-09T15:35:15Z
dc.date.available2013-12-09T15:35:15Z
dc.date.issued2013-12-09
dc.description.abstractThis 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 dataeng
dc.identifier.siciTD 346
dc.identifier.urihttps://hdl.handle.net/10438/11338
dc.language.isopor
dc.relation.ispartofseriesEESP - Textos para Discussão;TD 346por
dc.subjectInflationpor
dc.subjectForecastingpor
dc.subjectARIMApor
dc.subjectSpace-state modeleng
dc.subjectMarkov switchingeng
dc.subjectModel confidence seteng
dc.subject.areaEconomiapor
dc.subject.bibliodataEconomiapor
dc.titleForecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizonpor
dc.typeWorking Papereng
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