This paper studies the dynamic relationship between input and output of innovation in Dutch manufacturing using an unbalanced panel of enterprise data from five waves of the Community Innovation Survey during 1994-2004. We estimate by maximum likelihood a dynamic panel data bivariate tobit with...

This paper proposes a method to implement maximum likelihood estimation of the dynamic panel data type 2 and 3 tobit models. The likelihood function involves a two-dimensional indefinite integral evaluated using "two-step" Gauss-Hermite quadrature. A Monte Carlo study shows that the quadrature...

In this paper we extend the concept of serial correlation common features to panel data models. This analysis is motivated both by the need to develop a methodology to systematically study and test for common structures and comovements in panel data with autocorrelation present and by an...

The aim of this paper is to investigate the long run relationship between the development of banks and stock markets and economic growth. We make use of a Johansen-based panel cointegration methodology allowing for cross-country dependence to test the number of cointegrating vectors among these...

This paper introduces dynamics in the R&D-to-innovation and innovation-to-productivity relationships, which have mostly been estimated on cross-sectional data. It considers four nonlinear dynamic simultaneous equations models that include individual effects and idiosyncratic errors correlated...

This paper studies the dynamic relationship between input and output of innovation in Dutch manufacturing using an unbalanced panel of enterprise data from five waves of the Community Innovation Survey during 1994-2004. We estimate by maximum likelihood a dynamic panel data bivariate tobit with...