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Forecasting inflation using economic indicators: the case of France Author info | Abstract | Publisher info | Download info | Related research | Statistics O. De Bandt (Banque de France, Paris, France)
E. Michaux (HSBC Halbis Partners, Paris, France, and Banque de France, Paris, France)
C. Bruneau (Banque de France and University of Paris X, Paris, France)
A. Flageollet (Banque de France and University of Paris X, Paris, France)
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In order to provide short-run forecasts of headline and core HICP inflation for France, we assess the forecasting performance of a large set of economic indicators, individually and jointly, as well as using dynamic factor models. We run out-of-sample forecasts implementing the Stock and Watson (1999) methodology. We find that, according to usual statistical criteria, the combination of several indicators-in particular those derived from surveys-provides better results than factor models, even after pre-selection of the variables included in the panel. However, factors included in VAR models exhibit more stable forecasting performance over time. Results for the HICP excluding unprocessed food and energy are very encouraging. Moreover, we show that the aggregation of forecasts on subcomponents exhibits the best performance for projecting total inflation and that it is robust to data snooping. Copyright © 2007 John Wiley & Sons, Ltd.
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting .
Volume (Year): 26 (2007)
Issue (Month): 1 ()
Pages: 1-22
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Handle: RePEc:jof:jforec:v:26:y:2007:i:1:p:1-22Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
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Ard Reijer & Peter Vlaar, 2006.
"Forecasting Inflation: An Art as Well as a Science! ,"
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"Dynamic Factors in the Presence of Block Structure ,"
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