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Evaluation of inflation forecasting methods
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| 3.46 MB | Adobe PDF |
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Resumo(s)
This paper evaluates inflation forecast accuracy for Germany using disaggregated
Harmonized Index of Consumer Prices (HICP) data, comparing a bottom-up approach
to direct aggregate forecasting. By examining more granular data disaggregation,
Autoregressive, Vector Autoregressive, and factor-augmented models are used to forecast
HICP. The findings show that direct aggregate forecasting consistently outperforms the
bottom-up approach. Additionally, we enhance aggregate forecast accuracy through
forecast combination techniques, which deliver better results than individual models.
Descrição
Palavras-chave
Aggregate forecasts Disaggregate information Forecast combination Inflation Linear time series models