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Transition Dynamics in Endogenous Recombinant Growth Models by Means of Projection Methods

  • Fabio Privileggi

    ()

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.

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File URL: http://hdl.handle.net/10.1007/s10614-011-9278-7
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Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 38 (2011)
Issue (Month): 3 (October)
Pages: 367-387

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Handle: RePEc:kap:compec:v:38:y:2011:i:3:p:367-387
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  1. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979, March.
  2. Privileggi, Fabio, 2008. "On the transition dynamics in endogenous recombinant growth models," POLIS Working Papers 120, Institute of Public Policy and Public Choice - POLIS.
  3. Weitzman, Martin L., 1998. "Recombinant Growth," Scholarly Articles 3708468, Harvard University Department of Economics.
  4. Tsur, Yacov & Zemel, Amos, 2007. "Towards endogenous recombinant growth," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3459-3477, November.
  5. Ellen R. McGrattan, 1998. "Application of weighted residual methods to dynamic economic models," Staff Report 232, Federal Reserve Bank of Minneapolis.
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