In this paper, we evaluate the role of a set of variables as leading indicators for Euro-area inflation and GDP growth. Our leading indicators are taken from the variables in the European Central Bank's (ECB) Euro-area-wide model database, plus a set of similar variables for the US. We compare...

The accession of ten countries into the European Union makes the forecasting of their key macroeconomic indicators an exercise of some importance. Because of the transition period, only short spans of reliable time series are available, suggesting the adoption of simple time series models as...

The accession of ten countries into the European Union makes the forecasting of their key macroeconomic indicators such as GDP growth, inflation and interest rates an exercise of some importance. Because of the transition period, only short spans of reliable time series are available which...

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...

We conduct a detailed simulation study of the forecasting performance of diffusion index-based methods in short samples with structural change. We consider several data generation processes, to mimic different types of structural change, and compare the relative forecasting performance of factor...

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor-augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual...

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 euro area model database, plus a set of similar variables for the US. We compare the forecasting performance of each...

We conduct a detailed simulation study of the forecasting performance of diffusion index-based methods in short samples with structural change. We consider several data generation processes, to mimic different types of structural change, and compare the relative forecasting performance of factor...

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor-augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual...

The Factor-augmented Error Correction Model (FECM) generalizes the factor-augmented VAR (FAVAR) and the Error Correction Model (ECM), combining error-correction, cointegration and dynamic factor models. It uses a larger set of variables compared to the ECM and incorporates the long-run...