We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent...

We consider the dynamic factor model where the loading matrix, the dynamic factors and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the efficient shrinkage-based estimation of the loadings and the factors. We show that our estimates...

Dynamic interactions among stock return, Research and Development (R&D) expenses, patent applications based on R&D investment, and the propensity to patent are studied in this work for a panel of firms from the United States. The panel includes technologically similar firms, neck-to-neck, mostly...