Forecasting Austrian Inflation

Gabriel Moser (), Fabio Rumler and Johann Scharler
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Gabriel Moser: Oesterreichische Nationalbank, http://www.oenb.at

Working Papers from Oesterreichische Nationalbank (Austrian Central Bank)

Abstract: 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.

Keywords: Inflation Forecasting; Forecast Model selection; Aggregation (search for similar items in EconPapers)
JEL-codes: C52 C53 E31 (search for similar items in EconPapers)
Pages: 56
Date: 2004-10-04
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-mac and nep-mon
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Citations: View citations in EconPapers (31)

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Journal Article: Forecasting Austrian inflation (2007)
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