Learning by doing and the value of optimal experimentation
AbstractResearch 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 24 (2000)
Issue (Month): 4 (April)
Contact details of provider:
Web page: http://www.elsevier.com/locate/jedc
Other versions of this item:
- Volker 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.).
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Aldo Rustichini & Asher Wolinsky, 1992.
"Learning about Variable Demand in the Long Run,"
1015, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
- Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
- 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.
- Mark Rosenzweig & Andrew D. Foster, . "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Home Pages _068, University of Pennsylvania.
- 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 455-75, May.
- Volker Wieland, 2005. "A Numerical Dynamic Programming Algorithm for Optimal Learning Problems," Computing in Economics and Finance 2005 193, Society for Computational Economics.
- Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-64, September.
- Jovanovic, B. & Nyarko, Y., 1996.
"Learning by Doing and the Choice of Technology,"
96-25, C.V. Starr Center for Applied Economics, New York University.
- Bertocchi, Graziella & Spagat, Michael, 1991.
"Learning, Experimentation and Monetary Policy,"
Discussion Papers (IRES - Institut de Recherches Economiques et Sociales)
1991018, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
- 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.
- Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-58, November.
- Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
- 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.
- 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.
- 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.
- Balvers, Ronald J & Cosimano, Thomas F, 1994. "Inflation Variability and Gradualist Monetary Policy," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 721-38, October.
- 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.
- Kendrick, David, 1982. "Caution and probing in a macroeconomic model," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 149-170, November.
- 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 472-84, June.
- Kendrick, David, 1978. "Non-convexities from probing in adaptive control problems," Economics Letters, Elsevier, vol. 1(4), pages 347-351.
- A.L. Norman & M.R. Norman & C.J. 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.).
- 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.
- 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.
- 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.
- Aghion Philippe & Bolton, Patrick & Harris Christopher & Jullien Bruno, 1991.
"Optimal learning by experimentation,"
CEPREMAP Working Papers (Couverture Orange)
- 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 565-81, August.
- 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.
- 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.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wendy Shamier).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.