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Transition dynamics in endogenous recombinant growth models by means of projection methods

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  • Privileggi, Fabio

Abstract

This paper provides a step further in the computation of the transition path of a continuous time endogenous growth model discussed by Privileggi (2010) – based on the setting first introduced by Tsur and Zemel (2007) – in which knowledge evolves according to the Weitzman (1998) recombinant process. A projection method, based on the least squares of the residual function corresponding to the ODE defining the optimal policy of the 'detrended' model, allows for the numeric approximation of such policy for a positive Lebesgue measure range of values of the efficiency parameter characterizing the probability function of the recombinant process. Although the projection method's performance rapidly degenerates as one departs from a benchmark value for the efficiency parameter, we are able to numerically compute time-path trajectories which are sufficiently regular to allow for sensitivity analysis under changes in parameters' values.

Suggested Citation

  • Privileggi, Fabio, 2010. "Transition dynamics in endogenous recombinant growth models by means of projection methods," POLIS Working Papers 153, Institute of Public Policy and Public Choice - POLIS.
    • Handle: RePEc:uca:ucapdv:153
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    Cited by:

    1. 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.
    2. repec:uto:dipeco:201338 is not listed on IDEAS
    3. 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.
    4. 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.
    5. Privileggi, Fabio, 2015. "Takeoff vs. stagnation in endogenous recombinant growth models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 184-214.
    6. Burkhard Heer & Alfred Maußner, 2024. "Dynamic General Equilibrium Modeling," Springer Texts in Business and Economics, Springer, edition 3, number 978-3-031-51681-8, March.

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    Keywords

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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