Leading Indicators for Euro-area Inflation and GDP Growth
Number: 235
Year: 2003
Author(s): Anindya Banerjee (European University Institute), Massiliano Marcellino (IEP, IGIER, Bocconi University) and Igor Masten (European University Institute)
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 US. 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.
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 US. 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.
Keywords: leading indicator, factor model, model selection, GDP growth, inflation
JEL codes: C53, E37, C50