Dynamics and Welfare in Recombinant Growth Models with Intellectual Property Rights: a Computational Method

We consider the extended continuous time endogenous recombinant growth model with a basic IPRs system introduced by Marchese et al. (2014). In order to analyze the effect on social welfare of different IPRs policy regimes, we must carefully study the transition dynamics associated to different values of the IPRs policy parameter. To this aim, we exploit the computational method recently developed by Privileggi (2011, 2013), based on Projection methods, Gauss-Chebyshev and Gauss-Legendre quadrature, along with standard Runge-Kutta type algorithms, to approximate such transitional dynamic paths and perform Skiba-point analysis. Our simulations show that softer IPRs policy regimes generate higher welfare levels.