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On Learning and Growth

  • Leonard J. Mirman
  • Kevin Reffett
  • Marc Santugini

We study optimal growth under learning. We extend the Mirman-Zilcha stochastic growth results characterizing optimal programs for general utility and production functions to the case of learning. We then 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., without the use of conjugate priors), for any horizon. Finally, we 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
Date of revision:
Handle: RePEc:lvl:lacicr:1336
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  1. Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. Mirman, Leonard J. & Morand, Olivier F. & Reffett, Kevin L., 2008. "A qualitative approach to Markovian equilibrium in infinite horizon economies with capital," Journal of Economic Theory, Elsevier, vol. 139(1), pages 75-98, March.
  8. Bertocchi, Graziella & Spagat, Michael, 1998. "Growth under uncertainty with experimentation," Journal of Economic Dynamics and Control, Elsevier, vol. 23(2), pages 209-231, September.
  9. Aghion Philippe & Bolton, Patrick & Harris Christopher & Jullien Bruno, 1991. "Optimal learning by experimentation," CEPREMAP Working Papers (Couverture Orange) 9104, CEPREMAP.
  10. 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.
  11. Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-58, November.
  12. Arthur Fishman & Neil Gandal, 1993. "Experimentation and Learning with Network Effects," Industrial Organization 9309001, EconWPA.
  13. 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.
  14. 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.
  15. Creane, Anthony, 1994. "Experimentation with Heteroskedastic Noise," Economic Theory, Springer, vol. 4(2), pages 275-86, March.
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