the General-To-Specific approach. In an empirical application, we show that the two competing models produce accurate …

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due …

The estimation of structural dynamic factor models (DFMs) for large sets of variables is attracting considerable … two alternative estimation methods for the DFM. Finally, as an example, we reconsider the issue of the identification of …

This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments …-GMM estimation, which is also easily implemented. …

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due … alternative estimation approaches based, respectively, on static and dynamic principal components. The new method appears to … idiosyncratic components of the series. A similar pattern emerges in an empirical application with a large dataset of US …

This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments … experiments and empirical applications highlight the relevance and simplicity of Factor-GMM estimation. …

scale of a DSGE model and that of the time series data used for its estimation generally creates identfication problems …, introduces estimation bias and distorts the results of policy analysis. On the constructive side, we prove that the use of mixed … frequency data, combined with a proper estimation approach, can alleviate the temporal aggregation bias, mitigate the …

estimation can have serious consequences for identification, estimation and interpretation of the impulse response functions …. However, the use of mixed frequency data, combined with a proper estimation approach, can alleviate the temporal aggregation …