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On Learning and Growth

  • Leonard J. Mirman
  • Kevin Reffett
  • Marc Santugini

We embed learning (without experimentation) in optimal growth. We extend the Mirman-Zilcha results of stochastic optimal growth to the learning case. We use recursive methods to study the effect of learning on the dynamic program by considering the case of iso-elastic utility and linear production, for general distributions of the random shocks and beliefs (i.e., there is no conjugate priors) and for any horizon. We finally address the issue of experimentation by providing a solution to an infinite-horizon optimal dynamic program.

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Paper provided by CIRPEE in its series Cahiers de recherche with number 1336.

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Date of creation: 2013
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Handle: RePEc:lvl:lacicr:1336
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  1. Manjira Datta & Leonard J. Mirman & Edward E. Schlee, 2002. "Optimal Experimentation in Signal Dependent Decision Problems," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(2), pages 577-608, May.
  2. Fishman, Arthur & Gandal, Neil, 1994. "Experimentation and learning with networks effects," Economics Letters, Elsevier, vol. 44(1-2), pages 103-108.
  3. Aghion, P. & Bolton, P. & Harris, C. & Jullien, B., 1990. "Optimal Learning By Experimentation," DELTA Working Papers 90-10, DELTA (Ecole normale supérieure).
  4. Beck, Gunter W. & Wieland, Volker, 2002. "Learning and control in a changing economic environment," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1359-1377, August.
  5. G. Berttocchi, 1995. "Growth Under Uncertainty with Experimentation," Working Papers 95-12, Brown University, Department of Economics.
  6. Kiefer, Nicholas M & Nyarko, Yaw, 1989. "Optimal Control of an Unknown Linear Process with Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 571-86, August.
  7. Creane, Anthony, 1994. "Experimentation with Heteroskedastic Noise," Economic Theory, Springer, vol. 4(2), pages 275-86, March.
  8. Balvers, Ronald J & Cosimano, Thomas F, 1990. "Actively Learning about Demand and the Dynamics of Price Adjustment," Economic Journal, Royal Economic Society, vol. 100(402), pages 882-98, September.
  9. Leonard J Mirman & Olivier F. Morand & Kevin L. Reffett, 2004. "A Qualitative Approach to Markovian Equilibrium in Infinite Horizon Economies with Capital," Levine's Bibliography 122247000000000224, UCLA Department of Economics.
  10. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
  11. Mirman, L.J. & Samuelson, L. & Urbano, A., 1989. "Monopoly Experimentation," Papers 8-89-7, Pennsylvania State - Department of Economics.
    • Mirman, Leonard J & Samuelson, Larry & Urbano, Amparo, 1993. "Monopoly Experimentation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(3), pages 549-63, August.
  12. Hopenhayn, Hugo A & Prescott, Edward C, 1992. "Stochastic Monotonicity and Stationary Distributions for Dynamic Economies," Econometrica, Econometric Society, vol. 60(6), pages 1387-406, November.
  13. Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
  14. Grossman, Sanford J & Kihlstrom, Richard E & Mirman, Leonard J, 1977. "A Bayesian Approach to the Production of Information and Learning by Doing," Review of Economic Studies, Wiley Blackwell, vol. 44(3), pages 533-47, October.
  15. Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-58, November.
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