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Takeoff vs. stagnation in endogenous recombinant growth models

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  • Privileggi, Fabio

Abstract

This paper concludes the study of transition paths in the continuous-time recombinant endogenous growth model by providing numerical methods to estimate the threshold initial value of capital (a Skiba-type point) above which the economy takes off toward sustained growth in the long run, while it is doomed to stagnation otherwise. The model is based on the setting first introduced by Tsur and Zemel and then further specified by Privileggi, in which knowledge evolves according to the Weitzman recombinant process. We pursue a direct approach based on the comparison of welfare estimations along optimal consumption trajectories either diverging to sustained growth or converging to a steady state. To this purpose, we develop and test three algorithms capable of numerically simulating the initial Skiba-value of capital, each corresponding to initial stock of knowledge values belonging to three different ranges, thus covering all possible scenarios.

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  • Privileggi, Fabio, 2015. "Takeoff vs. stagnation in endogenous recombinant growth models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 184-214.
    • Handle: RePEc:eee:matcom:v:108:y:2015:i:c:p:184-214
    DOI: 10.1016/j.matcom.2014.05.012
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    1. Marchese, Carla & Marsiglio, Simone & Privileggi, Fabio & Ramello, Giovanni B., 2019. "Endogenous Recombinant Growth And Intellectual Property Rights," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 2035-2067, July.
    2. Marchese, Carla & Marsiglio, Simone & Privileggi, Fabio & Ramello, Giovanni, 2014. "Endogenous Recombinant Growth through Market Production of Knowledge and Intellectual Property Rights," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201413, University of Turin.
    3. Privileggi, Fabio & Marsiglio, Simone, 2014. "Dynamics and Welfare in Recombinant Growth Models with Intellectual Property Rights: a Computational Method," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201414, University of Turin.

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