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Forecasting Inflation Through a Bottom-Up Approach: The Portuguese Case

Publication Year 
JEL Code 
C22 - Time-Series Models
C32 - Time-Series Models
C43 - Index Numbers and Aggregation
C53 - Forecasting and Other Model Applications
E31 - Price Level; Inflation; Deflation
E37 - Forecasting and Simulation
The aim of this paper is to assess inflation forecasting acurracy over the short-term horizon using Consumer Price Index (CPI) disaggregated data. That is, aggregating forecasts is compared with aggregate forecasting. In particular, three questions are addressed: i) one should bottom-up or not, ii) how bottom one should go and iii) how one should model at the bottom. In contrast with the literature, di erent levels of data dis-aggregation are allowed, namely a higher disaggregation level than the one considered up to now. Moreover, both univariate and multivariate models are considered, such as SARIMA and SARIMAX models with dynamic common factors. An out-of-sample forecast comparison (up to twelve months ahead) is done using Portuguese CPI dataset. Aggregating the forecasts seems to be better than aggregate forecasting up to a five-months ahead horizon. Moreover, this improvement increases with the disaggregation level and the multivariate modelling outperforms the univariate one in the very short-run.
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Forecasting inflation through a bottom-up approach: How bottom is bottom?