R&D spillovers in an endogenous growth model with physical capital, human capital and varieties

There is a family of models with Physical, Human capital and R&D for which convergence properties have been discussed (Arnold, 2000a; Gómez, 2005). However, spillovers in R&D have been ignored in this context. We introduce spillovers in this model and derive its steady-state and stability properties. This new feature implies that the model is characterized by a system of four differential equations. A unique Balanced Growth Path along with a two dimensional stable manifold are obtained under simple and reasonable conditions. Transition is oscillatory toward the steady-state for plausible values of parameters.

Urban land cover change detection analysis and modeling spatio-temporal Growth dynamics using Remote Sensing and GIS Techniques: A case study of Dhaka, Bangladesh

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Absorption in human capital and r&d effects in an endogenous growth model

Until now, in models of endogenous growth with physical capital, human capital and R&D such as in Arnold [Journal of Macroeconomics 20 (1998)] and followers, steady-state growth is independent of innovation activities. We introduce absorption in human capital accumulation and describe the steady-state and transition of the model. We show that this new feature provides an effect of R&D in growth, consumption and welfare. We compare the quantitative effects of R&D productivity with the quantitative effects of Human Capital productivity in wealth and welfare.

Transitional dynamics of an endogenous growth model with an erosion effect

The convergence features of an Endogenous Growth model with Physical capital, Human Capital and R&D have been studied. We add an erosion effect (supported by empirical evidence) to this model, and fully characterize its convergence properties. The dynamics is described by a fourth-order system of differential equations. We show that the model converges along a one-dimensional stable manifold and that its equilibrium is saddle-path stable. We also argue that one of the implications of considering this “erosion effect” is the increase in the adherence of the model to data.