Transition dynamics in endogenous recombinant growth models by means of projection methods
AbstractThis paper provides a step further in the computation of the transition path of a continuous time endogenous growth model discussed by Privileggi (2010) â€“ based on the setting first introduced by Tsur and Zemel (2007) â€“ 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.
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Bibliographic InfoPaper provided by Institute of Public Policy and Public Choice - POLIS in its series POLIS Working Papers with number 153.
Length: 21 pages
Date of creation: Dec 2010
Date of revision:
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Web page: http://polis.unipmn.it
Knowledge Production; Endogenous Recombinant Growth; Transition Dynamics; Projection Methods; Least Squares.;
Other versions of this item:
- Fabio Privileggi, 2011. "Transition Dynamics in Endogenous Recombinant Growth Models by Means of Projection Methods," Computational Economics, Society for Computational Economics, vol. 38(3), pages 367-387, October.
- 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, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
- O41 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
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- Privileggi, Fabio, 2008. "On the transition dynamics in endogenous recombinant growth models," POLIS Working Papers 120, Institute of Public Policy and Public Choice - POLIS.
- Tsur, Yacov & Zemel, Amos, 2007. "Towards endogenous recombinant growth," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3459-3477, November.
- Martin L. Weitzman, 1995.
Harvard Institute of Economic Research Working Papers
1722, Harvard - Institute of Economic Research.
- Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979.
- 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.
- 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.
- Privileggi, Fabio, 2013. "Takeoff vs. Stagnation in Endogenous Recombinant Growth Models," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201338, University of Turin.
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