We derive computationally simple and intuitive score tests of neglected serial correlation in unobserved component univariate models using frequency domain techniques. In some common situations in which the alternative model information matrix is singular under the null, we derive one-sided...

Generalizamos el algoritmo EM espectral para modelos factoriales dinámicos de Fiorentini, Galesi y Sentana (2014) a modelos bifactoriales con factores tanto globales como regionales. Aprovechamos la raleza de las matrices de coefi cientes de manera que se puedan estimar dichos modelos por...

Realizamos dos contribuciones complementarias para estimar eficientemente modelos factoriales dinámicos: un algoritmo EM espectral y un procedimiento de inferencia indirecta iterada rapidísimo para modelos ARMA sin pérdida de eficiencia asintótica para cualquier número finito de...

We introduce a frequency domain version of the EM algorithm for general dynamic factor models. We consider both AR and ARMA processes, for which we develop iterative indirect inference procedures analogous to the algorithms in Hannan (1969). Although our proposed procedure allows researchers to...

We derive computationally simple and intuitive score tests of neglected serial correlation in unobserved component univariate models using frequency domain techniques. In some common situations in which the alternative model information matrix is singular under the null, we derive one-sided...

We derive computationally simple and intuitive expressions for score tests of neglected serial correlation in common and idiosyncratic factors in dynamic factor models using frequency domain techniques. The implied time domain orthogonality conditions are analogous to the conditions obtained by...