This paper shows consistency of a two step estimator of the parameters of a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters are first estimated from an OLS on principal components. In the second step, the factors are estimated...

This paper shows consistency of a two step estimation of the factors in a dynamic approximate factor model when the panel of time series is large ( large). In the first step, the parameters of the model are estimated from an OLS on principal components. In the second step, the factors are...

This paper shows consistency of a two step estimation of the factors in a dynamic approximate factor model when the panel of time series is large ( large). In the first step, the parameters of the model are estimated from an OLS on principal components. In the second step, the factors are...

This paper shows consistency of a two step estimator of the parameters of a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters are first estimated from an OLS on principal components. In the second step, the factors are estimated...

The authors replicate and extend the Monte Carlo experiment presented in Doz et al. (2012) on alternative (time-domain based) methods for extracting dynamic factors from large datasets; they employ open source software and consider a larger number of replications and a wider set of scenarios....

The authors replicate and extend the Monte Carlo experiment presented in Doz, Giannone and Reichlin (A Quasi-Maximum Likelihood Approach For Large, Approximate Dynamic Factor Models, Review of Economics and Statistics, 2012) on alternative (time-domain based) methods for extracting dynamic...