estimation of static factor models and factor augmented autoregressions using a set of 190 quarterly observations of 144 US …

version of the D6 Factor that improves upon the original model in several ways. While the original D6 based its estimation on … estimation period by a decade. These changes provide the updated model with substantially more information while reducing the … noise in the estimation. -- coincident index ; dynamic factor model …

the observed time series. We develop a simulated maximum likelihood estimation method based on importance sampling and …

This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly … estimation with sparse priors on the loadings matrix. The choice of a sparse prior is an extension to the existing macroeconomic … majority of the variables in both datasets are irrelevant for factor estimation. -- Factor models ; variable selection ; sparse …

Germany. We apply two methods for the estimation of the cyclical components from the data: the approach based on the …

the observed time series. We develop a simulated maximum likelihood estimation method based on importance sampling and …