Forecasting Spanish inflation using information from different sectors and geographical areas

Juan de Dios Tena (), Antoni Espasa () and Gabriel Pino ()

Statistics and Econometrics Working Papers from Universidad Carlos III, Departamento de Estadística y Econometría

Abstract: This paper evaluates different strategies to forecast Spanish inflation using information of price series for 57 products and 18 regions in Spain. We consider vector equilibrium correction (VeqC) models that include cointegration relationships between Spanish prices and prices in the regions of Valencia, Andalusia, Madrid, Catalonia and the Basque Country. This approach is consistent with economic intuition and is shown to be of tangible importance after suitable econometric evaluation. It is found that inflation forecasts can always be improved by aggregating projections from differente sectors and geographical areas. Moreover, cointegration relationships between regional and national prices must be considered in order to obtain a significantly better inflation forecast.

Keywords: Vector equilibrium correction models; Relative prices; Cointegration; Disaggregation (search for similar items in EconPapers)
JEL-codes: C2 C5 (search for similar items in EconPapers)
Date: 2008-01
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://e-archivo.uc3m.es/bitstream/10016/1150/1/ws080101.pdf (application/pdf)

Related works:
Working Paper: Forecasting Spanish inflation using information from different sectors and geographical areas
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cte:wsrepe:ws080101

Access Statistics for this paper

More papers in Statistics and Econometrics Working Papers from Universidad Carlos III, Departamento de Estadística y Econometría
Contact information at EDIRC.
Series data maintained by ().