Arbeitspapier
Forecasting Austrian Inflation
In this paper we apply factor models proposed by Stock and Watson [18] and VAR and ARIMA models to generate 12-month out of sample forecasts of Austrian HICP inflation and its subindices processed food, unprocessed food, energy, industrial goods and services price inflation. A sequential forecast model selection procedure tailored to this specific task is applied. It turns out that factor models possess the highest predictive accuracy for several subindices and that predictive accuracy can be further improved by combining the information contained in factor and VAR models for some indices. With respect to forecasting HICP inflation, our analysis suggests to favor the aggregation of subindices forecasts. Furthermore, the subindices forecasts are used as a tool to give a more detailed picture of the determinants of HICP inflation from both an ex-ante and ex-post perspective.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 91
- Klassifikation
-
Wirtschaft
Model Evaluation, Validation, and Selection
Forecasting Models; Simulation Methods
Price Level; Inflation; Deflation
- Thema
-
Inflation Forecasting
Forecast Model selection
Aggregation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Moser, Gabriel
Rumler, Fabio
Scharler, Johann
- Ereignis
-
Veröffentlichung
- (wer)
-
Oesterreichische Nationalbank (OeNB)
- (wo)
-
Vienna
- (wann)
-
2004
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:24 MESZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Moser, Gabriel
- Rumler, Fabio
- Scharler, Johann
- Oesterreichische Nationalbank (OeNB)
Entstanden
- 2004
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