Analysing and forecasting price dynamics across euro area countries and sectors: A panel VAR approach
Stephane Dees and
Jochen Güntner
No 2014-10, Economics working papers from Department of Economics, Johannes Kepler University Linz, Austria
Abstract:
This paper uses a panel VAR (PVAR) approach to estimating, analysing and forecasting price dynamics in four different sectors - industry, services, construction, and agriculture - across the four largest euro area economies - Germany, France, Italy and Spain - and the euro area as a whole. By modelling prices together with real activity, employment and wages, we can disentangle the role of unit labour costs and profit margins as the factors affecting price pressures on the supply side. In out-of-sample forecast exercises, the PVAR model fares comparatively well against common alternatives, although short-horizon forecast errors tend to be large when we consider only the period of the recent financial crisis. The second part of the paper focuses on Spain, for which prediction errors during the crisis are particularly large. Given that its economy faced dramatic sectoral changes due to the burst of a housing bubble, we use the PVAR model for studying the transmission of shocks originating from the Spanish construction sector to other sectors. In a multi-country extension of the model, we also allow for spillovers to the other euro area countries in our sample.
Keywords: Cost pressures; forecasting; impulse response analysis; panel VAR models (search for similar items in EconPapers)
JEL-codes: C33 C53 E31 E37 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2014-09
New Economics Papers: this item is included in nep-eec, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
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Working Paper: Analysing and forecasting price dynamics across euro area countries and sectors: a panel VAR approach (2014) 
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Persistent link: https://EconPapers.repec.org/RePEc:jku:econwp:2014_10
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