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 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 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...

We generalise the spectral EM algorithm for dynamic factor models in Fiorentini, Galesi and Sentana (2014) to bifactor models with pervasive global factors complemented by regional ones. We exploit the sparsity of the loading matrices so that researchers can estimate those models by maximum...

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 information matrix is singular under the null we derive extremum tests that are...