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Fractals and Self-Similarity in Economics: the Case of a Stochastic Two-Sector Growth Model

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Author Info

  • La Torre, Davide

    ()

  • Marsiglio, Simone

    ()

  • Privileggi, Fabio

    ()

Abstract

We study a stochastic, discrete-time, two-sector optimal growth model in which the production of the homogeneous consumption good uses a Cobb-Douglas technology, combining physical capital and an endogenously determined share of human capital. Education is intensive in human capital as in Lucas (1988), but the marginal returns of the share of human capital employed in education are decreasing, as suggested by Rebelo (1991). Assuming that the exogenous shocks are i.i.d. and affect both physical and human capital, we build specific configurations for the primitives of the model so that the optimal dynamics for the state variables can be converted, through an appropriate log-transformation, into an Iterated Function System converging to an invariant distribution supported on a generalized Sierpinski gasket.

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Bibliographic Info

Paper provided by Institute of Public Policy and Public Choice - POLIS in its series POLIS Working Papers with number 157.

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Length: 16 pages
Date of creation: Jun 2011
Date of revision:
Handle: RePEc:uca:ucapdv:157

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Web page: http://polis.unipmn.it

Related research

Keywords: fractals; iterated function system; self-similarity; Sierpinski gasket; stochastic growth;

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References

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  1. Mitra, Tapan & Privileggi, Fabio, 2005. "Cantor Type Attractors in Stochastic Growth Models," POLIS Working Papers 43, Institute of Public Policy and Public Choice - POLIS.
  2. Nishimura, Kazuo & Yano, Makoto, 1995. "Nonlinear Dynamics and Chaos in Optimal Growth: An Example," Econometrica, Econometric Society, vol. 63(4), pages 981-1001, July.
  3. Davide LA TORRE & Franklin MENDIVIL, 2007. "Iterated function systems on multifunctions and inverse problems," Departmental Working Papers 2007-32, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  4. Gardini, L. & Hommes, C.H. & Tramontana, F. & de Vilder, R., 2009. "Forward and Backward Dynamics in implicitly defined Overlapping Generations Models," CeNDEF Working Papers 09-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  5. Davide LA TORRE & Edward R. VRSCAY & Mehran EBRAHIMI & Michael F. BARNSLEY, 2008. "Measure-valued images, associated fractal transforms and the affine self-similarity of images," Departmental Working Papers 2008-45, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  6. Nishimura Kazuo & Sorger Gerhard, 1996. "Optimal Cycles and Chaos: A Survey," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-20, April.
  7. Mitra, Tapan & Privileggi, Fabio, 2009. "On Lipschitz continuity of the iterated function system in a stochastic optimal growth model," Journal of Mathematical Economics, Elsevier, vol. 45(1-2), pages 185-198, January.
  8. Stefano Maria Iacus & Davide La Torre, 2002. "Approximating distribution functions by iterated function systems," Departmental Working Papers 2002-03, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  9. Boldrin, Michele & Montrucchio, Luigi, 1986. "On the indeterminacy of capital accumulation paths," Journal of Economic Theory, Elsevier, vol. 40(1), pages 26-39, October.
  10. Tapan Mitra & Luigi Montrucchio & Fabio Privileggi, 2003. "The nature of the steady state in models of optimal growth under uncertainty," Economic Theory, Springer, vol. 23(1), pages 39-71, December.
  11. Mitra, Tapan & Privileggi, Fabio, 2003. "Cantor Type Invariant Distributions in the Theory of Optimal Growth under Uncertainty," Working Papers 03-09, Cornell University, Center for Analytic Economics.
  12. Davide LA TORRE & Edward R. VRSCAY, 2008. "A generalized fractal transform for measure-valued images," Departmental Working Papers 2008-38, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
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