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Abstract

This chapter of the Handbook of Computational Economics is mostly about research on active learning and is confined to discussion of learning in dynamic models in which the systems equations are linear, the criterion function is quadratic and the additive noise terms are Gaussian. Though there is much work on learning in more general systems, it is useful here to focus on models with these specifications since more general systems can be approximated in this way and since much of the early work on learning has been done with these quadratic-linear-gaussian systems. We begin with what has been learned about learning in dynamic economic models in the last few decades. Then we progress to a discussion of what we hope to learn in the future from a new project that is just getting underway. However before doing either of these it is useful to provide a short description of the mathematical framework that will be used in the chapter.

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Bibliographic Info

Paper provided by Utrecht School of Economics in its series Working Papers with number 08-20.

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Length: 40 pages
Date of creation: Aug 2008
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Handle: RePEc:use:tkiwps:0820

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Related research

Keywords: Active learning; dual control; optimal experimentation; stochastic optimization; time-varying parameters; forward looking variables; numerical experiments.;

Find related papers by JEL classification:

• C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
• E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination

This paper has been announced in the following NEP Reports:

• NEP-ALL-2008-09-20 (All new papers)
• NEP-CBA-2008-09-20 (Central Banking)
• NEP-CMP-2008-09-20 (Computational Economics)
• NEP-HPE-2008-09-20 (History & Philosophy of Economics)
• NEP-MAC-2008-09-20 (Macroeconomics)

References

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1. Hans M. Amman & David A. Kendrick, 1997. "Linear Quadratic Optimization for Models with Rational Expectations," CARE Working Papers 9708, The University of Texas at Austin, Center for Applied Research in Economics.
   
   • Amman, Hans & Kendrick, David, 1999. "Linear-Quadratic Optimization For Models With Rational Expectations," Macroeconomic Dynamics, Cambridge University Press, vol. 3(04), pages 534-543, December.
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.
   
   • Marco P. Tucci & David A. Kendrick & Hans M. Amman, 2007. "The Parameter Set in an Adaptive Control Monte Carlo Experiment: Some Considerations," Department of Economics University of Siena 507, Department of Economics, University of Siena.
3. Tucci, Marco P., 2002. "A note on global optimization in adaptive control, econometrics and macroeconomics," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1739-1764, August.
4. Hans M. Amman & David Kendrick, . "Should Macroeconomic Policy Makers Consider Parameter Covariances?," Computing in Economics and Finance 1997 8, Society for Computational Economics.
   
   • Amman, Hans M & Kendrick, David A, 1999. "Should Macroeconomic Policy Makers Consider Parameter Covariances?," Computational Economics, Society for Computational Economics, vol. 14(3), pages 263-67, December.
   • Hans M. Amman & David A. Kendrick, 1997. "Should Macroeconomic Policy Makers Consider Parameter Covariances?," CARE Working Papers 9701, The University of Texas at Austin, Center for Applied Research in Economics.
5. Amman, Hans M. & Kendrick, David A., 2003. "Mitigation of the Lucas critique with stochastic control methods," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2035-2057, September.
   
   • Hans Amman & David Kendrick, 2000. "Mitigation Of The Lucas Critique With Stochastic Control Methods," Computing in Economics and Finance 2000 182, Society for Computational Economics.
6. 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.
   
   • 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.).
7. Aghion, P. & Bolton, P. & Harris, C. & Jullien, B., 1990. "Optimal Learning By Experimentation," DELTA Working Papers 90-10, DELTA (Ecole normale supérieure).
   
   • Aghion Philippe & Bolton, Patrick & Harris Christopher & Jullien Bruno, 1991. "Optimal learning by experimentation," CEPREMAP Working Papers (Couverture Orange) 9104, CEPREMAP.
8. Mewael F. Tesfaselassie & Eric Schaling & Sylvester Eijffinger, 2011. "Learning about the Term Structure and Optimal Rules for Inflation Targeting," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(8), pages 1685-1706, December.
   
   • Tesfaselassie, M.F. & Schaling, E. & Eijffinger, S.C.W., 2006. "Learning about the Term Structure and Optimal Rules for Inflation Targeting," Discussion Paper 2006-88, Tilburg University, Center for Economic Research.
   • Tesfaselassie, M.F. & Schaling, E. & Eijffinger, S.C.W., 2006. "Learning About the Term Structure and Optimal Rules for Inflation Targeting," Research Paper ERS-2006-058-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
   • Mewael F. Tesfaselassie & Eric Schaling & Sylvester Eijffinger, 2007. "Learning About the Term Structure and Optimal Rules for Inflation Targeting," Working Papers 62, Economic Research Southern Africa.
   • Eijffinger, Sylvester C W & Schaling, Eric & Tesfaselassie, Mewael F., 2006. "Learning About the Term Structure and Optimal Rules for Inflation Targeting," CEPR Discussion Papers 5896, C.E.P.R. Discussion Papers.
9. Kendrick, David, 2000. "Control theory with applications to economics," Handbook of Mathematical Economics, in: K. J. Arrow & M.D. Intriligator (ed.), Handbook of Mathematical Economics, edition 4, volume 1, chapter 4, pages 111-158 Elsevier.
10. Amman, Hans, 1996. "Numerical methods for linear-quadratic models," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 13, pages 587-618 Elsevier.
11. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-85, July.
    
    • Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Cowles Foundation Discussion Papers 564, Cowles Foundation for Research in Economics, Yale University.
    • Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models," NBER Technical Working Papers 0005, National Bureau of Economic Research, Inc.
12. 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.
13. 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.
14. David Kendrick, 1976. "Applications of Control Theory to Macroeconomics," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 2, pages 171-190 National Bureau of Economic Research, Inc.
15. Gunter Coenen, Volker Wieland, Andrew Levin, 2001. "Evaluating Information Variables for Monetary Policy in a Noisy Economic Environment," Computing in Economics and Finance 2001 131, Society for Computational Economics.
16. Hans M. Amman & David A. Kendrick, 1996. "The DUALI/DUALPC Software for Optimal Control Models: Introduction," CARE Working Papers 9602, The University of Texas at Austin, Center for Applied Research in Economics.
17. 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.
18. Fisher, P. G. & Holly, S. & Hughes Hallett, A. J., 1986. "Efficient solution techniques for dynamic non-linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 10(1-2), pages 139-145, June.
19. 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.
20. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-11, July.
21. Hans M. Amman & David A. Kendrick, 2003. "A Classification System for Economic Stochastic Control Models," Computing in Economics and Finance 2003 114, Society for Computational Economics.
    
    • David Kendrick & Hans Amman, 2006. "A Classification System for Economic Stochastic Control Models," Computational Economics, Society for Computational Economics, vol. 27(4), pages 453-481, June.
22. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
23. 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.
24. Amman, Hans M. & Kendrick, David A., 1997. "Active learning: A correction," Journal of Economic Dynamics and Control, Elsevier, vol. 21(10), pages 1613-1614, August.
25. Thomas F. Cosimano, 2003. "Optimal Experimentation and the Perturbation Method," Computing in Economics and Finance 2003 71, Society for Computational Economics.
26. Tucci, Marco P, 1998. "The Nonconvexities Problem in Adaptive Control Models: A Simple Computational Solution," Computational Economics, Society for Computational Economics, vol. 12(3), pages 203-22, December.
27. 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.
28. MacRae, Elizabeth Chase, 1975. "An Adaptive Learning Rule for Multiperiod Decision Problems," Econometrica, Econometric Society, vol. 43(5-6), pages 893-906, Sept.-Nov.
29. 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.
30. 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.
31. 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.
32. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
33. Pindyck, Robert S, 1973. "Optimal Policies for Economic Stabilization," Econometrica, Econometric Society, vol. 41(3), pages 529-60, May.
34. 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.
35. Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
36. Hans M. Amman & David A. Kendrick, 1997. "Linear Quadratic Optimization for Models with Rational Expectations," Tinbergen Institute Discussion Papers 97-102/2, Tinbergen Institute.

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