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Leading Indicators for Euro-area Inflation and GDP Growth

  • Anindya Banerjee
  • Massimiliano Marcellino
  • Igor Masten

In this paper we evaluate the role of a set of variables as leading indicators for Euro-area inflation and GDP growth. Our evaluation is based on using the variables in the ECB Euroarea model database, plus a set of similar variables for the U.S. We compare the forecasting performance of each indicator with that of purely autoregressive models, using an evaluation procedure that is particularly relevant for policy making. The evaluation is conducted both expost and in a pseudo real time context, for several forecast horizons, and using both recursive and rolling estimation. We also analyze three different approaches to combining the information from several indicators. First, we discuss the use as indicators of the estimated factors from a dynamic factor model for all the indicators. Second, an automated model selection procedure is applied to models with a large set of indicators. Third, we consider pooling the single indicator forecasts. The results indicate that single indicator forecasts are on average better than those derived from more complicated methods, but for them to beat the autoregression a different indicator has to be used in each period. A simple real-time procedure for indicator-selection produces good results.

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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number 235.

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Date of creation: 2003
Date of revision:
Handle: RePEc:igi:igierp:235
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  1. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
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  17. Massimiliano Marcellino, . "Forecast pooling for short time series of macroeconomic variables," Working Papers 212, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
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