Abstract
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. It turns out that, according to usual statistical criteria, the combination of several indicators - in particular those derived from surveys- provides better results than dynamic 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 HICP excluding unprocessed food and energy are very encouraging. Moreover, we show that it is possible to use forecasts on this indicator to project overall inflation.
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