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Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem

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  • Cosimano, Thomas F.

Abstract

The perturbation method is used to approximate optimal experimentation problems. The approximation is in the neighborhood of the linear regulator (LR) problem. The first order perturbation of the optimal decision under experimentation is a combination of the LR solution and a term that captures the impact of the uncertainty on the agent's value function. An algorithm is developed in a companion paper to quickly implement this procedure on the computer. As a result, the impact of optimal experimentation on an agent's decisions can be quantified and estimated for a large class of problems encountered in economics.

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Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 32 (2008)
Issue (Month): 6 (June)
Pages: 1857-1894

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Handle: RePEc:eee:dyncon:v:32:y:2008:i:6:p:1857-1894
Contact details of provider: Web page: http://www.elsevier.com/locate/jedc

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  1. Brock, William A. & Durlauf, Steven N., 2005. "Local robustness analysis: Theory and application," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 2067-2092, November.
  2. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
  3. MacRae, Elizabeth Chase, 1975. "An Adaptive Learning Rule for Multiperiod Decision Problems," Econometrica, Econometric Society, vol. 43(5-6), pages 893-906, Sept.-Nov.
  4. Aghion Philippe & Bolton, Patrick & Harris Christopher & Jullien Bruno, 1991. "Optimal learning by experimentation," CEPREMAP Working Papers (Couverture Orange) 9104, CEPREMAP.
  5. Wieland, Volker, 2000. "Monetary policy, parameter uncertainty and optimal learning," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 199-228, August.
  6. Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 435-445 National Bureau of Economic Research, Inc.
  7. Santos, Manuel S., 1994. "Smooth dynamics and computation in models of economic growth," Journal of Economic Dynamics and Control, Elsevier, vol. 18(3-4), pages 879-895.
  8. William A. Brock & Steven N. Durlauf & Kenneth D. West, 2003. "Policy Evaluation in Uncertain Economic Environments," NBER Working Papers 10025, National Bureau of Economic Research, Inc.
  9. Lars Peter Hansen & Thomas J. Sargent, 2001. "Acknowledging Misspecification in Macroeconomic Theory," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 4(3), pages 519-535, July.
  10. Wieland, Volker, 2000. "Learning by doing and the value of optimal experimentation," Journal of Economic Dynamics and Control, Elsevier, vol. 24(4), pages 501-534, April.
  11. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-59, September.
  12. Godfrey Keller & Sven Rady, 1997. "Optimal Experimentation in a Changing Environment," STICERD - Theoretical Economics Paper Series /1997/333, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  13. Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
  14. Wieland Volker, 2006. "Monetary Policy and Uncertainty about the Natural Unemployment Rate: Brainard-Style Conservatism versus Experimental Activism," The B.E. Journal of Macroeconomics, De Gruyter, vol. 6(1), pages 1-34, March.
  15. Lars Peter Hansen & Ellen R. McGrattan & Thomas J. Sargent, 1994. "Mechanics of forming and estimating dynamic linear economies," Staff Report 182, Federal Reserve Bank of Minneapolis.
  16. 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.
  17. Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-58, November.
  18. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
  19. Gaspar, Jess & L. Judd, Kenneth, 1997. "Solving Large-Scale Rational-Expectations Models," Macroeconomic Dynamics, Cambridge University Press, vol. 1(01), pages 45-75, January.
  20. Patrick Bolton & Christopher Harris, 1999. "Strategic Experimentation," Econometrica, Econometric Society, vol. 67(2), pages 349-374, March.
  21. Kendrick, David A., 2005. "Stochastic control for economic models: past, present and the paths ahead," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 3-30, January.
  22. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-64, September.
  23. 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.
  24. Klemperer, Paul, 1995. "Competition When Consumers Have Switching Costs: An Overview with Applications to Industrial Organization, Macroeconomics, and International Trade," Review of Economic Studies, Wiley Blackwell, vol. 62(4), pages 515-39, October.
  25. McGrattan, Ellen R., 1994. "A note on computing competitive equilibria in linear models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 149-160, January.
  26. 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.
  27. Chen, Yu & Cosimano, Thomas F. & Himonas, Alex A., 2008. "Analytic solving of asset pricing models: The by force of habit case," Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3631-3660, 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 571-86, August.
  29. 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.
  30. Giuseppe Moscarini & Lones Smith, 2001. "The Optimal Level of Experimentation," Econometrica, Econometric Society, vol. 69(6), pages 1629-1644, November.
  31. 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.
  32. Hansen, Lars Peter & Sargent, Thomas J., 2003. "Robust control of forward-looking models," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 581-604, April.
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Cited by:

  1. H.M. Amman & D.A. Kendrick, 2012. "Conjectures on the policy function in the presence of optimal experimentation," Working Papers 12-09, Utrecht School of Economics.
  2. Tucci, Marco P. & Kendrick, David A. & Amman, Hans M., 2010. "The parameter set in an adaptive control Monte Carlo experiment: Some considerations," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1531-1549, September.
  3. D.A. Kendrick & H.M. Amman, 2008. "Comparison of Policy Functions from the Optimal Learning and Adaptive Control Frameworks," Working Papers 08-19, Utrecht School of Economics.
  4. BRECHET, Thierry & HRITONENKO, Natali & YATSENKO, Yuri, . "Adaptation and mitigation in long-term climate policy," CORE Discussion Papers RP -2479, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Dia, Enzo, 2013. "How do banks respond to shocks? A dynamic model of deposit-taking institutions," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3623-3638.
  6. Tim Willems, 2013. "Actively Learning by Pricing: A Model of an Experimenting Seller," Economics Series Working Papers 687, University of Oxford, Department of Economics.

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