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Learning by doing and the value of optimal experimentation

Author

Listed:
  • Volker W. Wieland
Abstract
Research on learning-by-doing has typically been restricted to cases where estimation and control can be treated separately. Recent work has provided convergence results for more general learning problems where experimentation is an important aspect of optimal control. However the associated optimal policy cannot be derived analytically because Bayesian learning introduces a nonlinearity in the dynamic programming problem. This paper characterizes the optimal policy numerically and shows that it incorporates a substantial degree of experimentation. Dynamic simulations indicate that optimal experimentation dramatically improves the speed of learning, while separating control and estimation frequently induces a long-lasting bias in the control and target variables.

Suggested Citation

  • Volker W. Wieland, 1996. "Learning by doing and the value of optimal experimentation," Finance and Economics Discussion Series 96-5, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:96-5
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    References listed on IDEAS

    as
    1. Philippe Aghion & Patrick Bolton & Christopher Harris & Bruno Jullien, 1991. "Optimal Learning by Experimentation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(4), pages 621-654.
    2. Jovanovic, Boyan & Nyarko, Yaw, 1996. "Learning by Doing and the Choice of Technology," Econometrica, Econometric Society, vol. 64(6), pages 1299-1310, November.
    3. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    4. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
    5. Bertocchi, Graziella & Spagat, Michael, 1993. "Learning, experimentation, and monetary policy," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 169-183, August.
    6. Kendrick, David, 1978. "Non-convexities from probing in adaptive control problems," Economics Letters, Elsevier, vol. 1(4), pages 347-351.
    7. Rustichini, Aldo & Wolinsky, Asher, 1995. "Learning about variable demand in the long run," Journal of Economic Dynamics and Control, Elsevier, vol. 19(5-7), pages 1283-1292.
    8. Alfred L. Norman & M. R. Norman & Carl Palash, 1979. "Multiple relative maxima in optimal macroeconomic policy: an illustration," Special Studies Papers 134, Board of Governors of the Federal Reserve System (U.S.).
    9. El-Gamal, Mahmoud A. & Sundaram, Rangarajan K., 1993. "Bayesian economists ... Bayesian agents : An alternative approach to optimal learning," Journal of Economic Dynamics and Control, Elsevier, vol. 17(3), pages 355-383, May.
    10. John B. Taylor, 1976. "Methods of Efficient Parameter Estimation in Control Problems," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 3, pages 339-347, National Bureau of Economic Research, Inc.
    11. Trefler, Daniel, 1993. "The Ignorant Monopolist: Optimal Learning with Endogenous Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(3), pages 565-581, August.
    12. Kendrick, David, 1982. "Caution and probing in a macroeconomic model," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 149-170, November.
    13. McLennan, Andrew, 1984. "Price dispersion and incomplete learning in the long run," Journal of Economic Dynamics and Control, Elsevier, vol. 7(3), pages 331-347, September.
    14. Balvers, Ronald J. & Cosimano, Thomas F., 1993. "Periodic learning about a hidden state variable," Journal of Economic Dynamics and Control, Elsevier, vol. 17(5-6), pages 805-827.
    15. Amman, Hans M. & Kendrick, David A., 1994. "Active learning Monte Carlo results," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 119-124, January.
    16. Taylor, John B, 1974. "Asymptotic Properties of Multiperiod Control Rules in the Linear Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(2), pages 472-484, June.
    17. Mizrach, Bruce, 1991. "Nonconvexities in a stochastic control problem with learning," Journal of Economic Dynamics and Control, Elsevier, vol. 15(3), pages 515-538, July.
    18. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, April.
    19. Alfred L. Norman, 1976. "First Order Dual Control," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 3, pages 311-321, National Bureau of Economic Research, Inc.
    20. Kiefer, Nicholas M., 1989. "A value function arising in the economics of information," Journal of Economic Dynamics and Control, Elsevier, vol. 13(2), pages 201-223, April.
    21. Volker Wieland, 2005. "A Numerical Dynamic Programming Algorithm for Optimal Learning Problems," Computing in Economics and Finance 2005 193, Society for Computational Economics.
    22. Tucci, Marco P., 1997. "Adaptive control in the presence of time-varying parameters," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 39-47, November.
    23. 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 882-898, September.
    24. Amman, Hans M & Kendrick, David A, 1995. "Nonconvexities in Stochastic Control Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(2), pages 455-475, May.
    25. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-1064, September.
    26. Ronald J. Balvers & Thomas F. Cosimano, 1994. "Inflation Variability and Gradualist Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 721-738.
    27. Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-1058, November.
    28. 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 571-586, August.
    29. Anderson, T W & Taylor, John B, 1976. "Some Experimental Results on the Statistical Properties of Least Squares Estimates in Control Problems," Econometrica, Econometric Society, vol. 44(6), pages 1289-1302, November.
    30. Jovanovic, Boyan & Nyarko, Yaw, 1994. "The Bayesian Foundations of Learning by Doing," Working Papers 94-15, C.V. Starr Center for Applied Economics, New York University.
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