Bayesian Learning in Optimal Growth Models Under Uncertainty

  • Sardar M. N. Islam
Part of the Advances in Computational Economics book series (AICE, volume 11)

Abstract

This paper discusses the computational techniques to model Bayesian learning in optimal growth models under uncertainty. The essential characteristics of the modelling approach adopted here are the following.

Keywords

Assimilation Kelly OECD Univer 

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References

  1. Amman, H., Kendrick, D. and Rust, J.: 1996, Handbook of Computational Economics. Amsterdam: Elsevier.Google Scholar
  2. Aoki, M.: 1989, Optimization of Stochastic Systems. San Diego: Academic Press.Google Scholar
  3. Arrow, K.J.: 1951, ‘Alternative Approaches to the Theory of Choice Under Risk-Taking Situations’. Econometrica 29, 404–431.CrossRefGoogle Scholar
  4. Azariadis, C.: 1993, Intertemporal Macroeconomics. Oxford: Blackwell.Google Scholar
  5. Barro, R.J. and Salai-i-Martin, X.: 1995, Economic Growth. New York: McGraw-Hill.Google Scholar
  6. Bayes, T.: 1763, ‘An Essay Toward Solving a Problem in the Doctrine of Chances’. Philosophical Transactions of the Royal Society 53, 370–418.CrossRefGoogle Scholar
  7. Bharucha-Reid, A.T.: 1960, Elements of the Theory of Markov Processes and Their Applications. New York: McGraw-Hill Book Co.Google Scholar
  8. Blanchard, O. and Fisher, S.: 1989, Lectures on Macroeconomics. Cambridge: MIT Press.Google Scholar
  9. Boyer M. and Khilstrom, R. (eds.): 1984, Bayesian Models in Economic Theory. Amsterdam: North Holland.Google Scholar
  10. Brooke, A. Kendrick, D. Meeraus, A. and Raman, R.: 1997, GAMS: A User’s Guide. Massachusetts: Boyd and Fraser Publishing Co..Google Scholar
  11. Burmeister, E. and Dobell, A.: 1970, Mathematical Theories of Economic Growth. London: Macmillan.Google Scholar
  12. Cesar, S.: 1994, Control and Game Models of the Greenhouse Effect. Heidelberg: Springer Verlag.CrossRefGoogle Scholar
  13. Christensen, G.S., El-Hawary, M.E. and Soliman, S.A.: 1987, Optimal Control Applications in Electric Power Systems. Mathematical Concepts and Methods in Science and Engineering: vol. 35.Google Scholar
  14. Conrad, J.M. and Clark, C.W.: 1987, Natural Resource Economics. New York: Cambridge University Press.Google Scholar
  15. Craven, B.: 1995, Control and Optimization. U.K.: Chapman and Hall.Google Scholar
  16. Dasgupta, P. and Stoneman, P. (eds.): 1987, Economic Policy and Technological Performance. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  17. Edmonds, B. and Moss, S.: 1998, ‘Modelling Economic Learning as Modelling’. Systems and Cybernetics 29, 5–37.CrossRefGoogle Scholar
  18. Faucheux, S., Pearce, D. and Proops, J.: 1996, Models of Sustainable Development. Hants, UK: Edward Elgar.Google Scholar
  19. Fox, K.A., Sengupta, J.K. and Thorbecke, E.: 1973, The Theory of Quantitative Economic Policy with Applications to Economic Growth, Stabilization and Planning. Amsterdam: North-Holland Publishing Co..Google Scholar
  20. Freixas, X. and Laffont, J.J.: 1984, ‘The Irreversibility Effect’. In: M. Boyer and R. Khilstrom, (eds.), Bayesian Models in Economic Theory,Amsterdam, Netherlands: North Holland, pp. 105–114.Google Scholar
  21. Gass, S. I. (ed.): 1980, Validation and Assessment Issues of Energy Models. Washington D.C.: National Bureau of Standards Special Publication 569.Google Scholar
  22. Guest, R.: 1996, ‘Applying a Model of the Socially Optimum Levels of Savings, Investment, and the Current Account Deficit to Australia for the Period: 1960–61 to 1993–94’. Ph.D. thesis, Department of Economics, University of Melbourne, Melbourne.Google Scholar
  23. Haavelmo, T.: 1954, Studies in the Theory of Economic Evolution. Amsterdam: North-Holland Publishing Co..Google Scholar
  24. Harasanyi, J.C.: 1978, ‘Bayesian Decision Theory and Utilitarian Ethics’. American Economic Review, Papers and Proceedings 68, 223–228.Google Scholar
  25. Hocking, L.M.: 1991, Optimal Control: An Introduction to the Theory with Applications. Oxford: Clarendon Press.Google Scholar
  26. Huang, C.C. and Cai, D.: 1994, ‘Constant-Returns, Endogenous Growth with Pollution Control’. Environmental and Resource Economics 4, 383–400.CrossRefGoogle Scholar
  27. Huy, V.C.: 1995, ‘Modelling Technological Change: Learning and Advancing by Investing’. paper presented at International Conference in honour of Professor Kenneth Arrow, 7–8 September 1995, Australian National University.Google Scholar
  28. Intriligator, M.D.: 1971, Mathematical Optimization and Economic Theory. N.J.: Prentice-Hall Inc.Google Scholar
  29. Islam, S.M.N.: 1998, ‘Optimal Growth Economics, Manuscript’. Doctor of Business Administration Lecture Notes, Victoria University of Technology, Melbourne.Google Scholar
  30. Kall, P. and Wallace S.W.: 1994, Stochastic Programming. Chichester: John Wiley Sons.Google Scholar
  31. Kelly, D.L. and Kolstad, C.D.: 1997, ‘Bayesian Learning, Growth, and Pollution’. Department of Economics, University of California, Santa Barbara.Google Scholar
  32. Kendrick, D.: 1981, Stochastic Control for Economic Models. New York: McGraw Hill Book Cornpany.Google Scholar
  33. Kendrick, D.: 1994, ‘Computational Approaches to Learning with Control Theory’. In:, Computational Techniques for Econometrics and Economic Analysis, Netherlands: Kluwer Academic Publishers, pp. 75–87.Google Scholar
  34. Kolstad, C.D.: 1993, ‘Looking vs Leaping: The Timing of CO2 Control in the Face of Uncertainty and Learning’. In: Y. Kaya, N. Nakicenovic, W. D. Nordhaus and E L. Toth (eds.), The Costs, Impacts, and Benefits of CO2 Mitigation, Laxenburg, Austria: Proceedings of a Workshop Held on 28–30 September 1992, IIASA, pp. 63–81.Google Scholar
  35. Kolstad, C.D.: 1994, ‘Mitigating Climate Change Impacts: The Conflicting Effects of Irreversibilities in CO2 Accumulation and Emission Control Investment’. In: N. Nakicenovic, W.D. Nordhaus, R. Richels and E L. Toth (eds.), Integrative Assessment of Mitigation, Impacts, and Adaptation to Climate Change, Laxenburg, Austria: IIASA, pp. 205–218.Google Scholar
  36. Koopmans, T.: 1967, ‘Objectives, Constraints and Outcomes in Optimal Growth Models’. Econometrica 35, 1–15.CrossRefGoogle Scholar
  37. Malinvaud, E. and Bacharach M.O.L. (eds.): 1967, Activity Analysis in the Theory of Growth and Planning. London: Macmillan.Google Scholar
  38. Manne, A.S.: 1985, Economic Equilibrium: Model Formulation and Solution. Amsterdam: Elsevier.CrossRefGoogle Scholar
  39. Manne, A.S.: 1992, ‘Global 2100: Alternative Scenarios for Reducing Carbon Emissions’. OECD Economics Department Working Papers, No.111, Paris.CrossRefGoogle Scholar
  40. McKibbin, W.J. and Sachs, J.D.: 1991, ‘Global Linkages: Macroeconomic Interdependence and Cooperation in the World Economy’. The Brookings Institute, Washington.Google Scholar
  41. Messner, S.: 1995, ‘Endogenized Technical Learning in an Energy Systems Model’. Working Paper WP-95–114, International Institute for Applied Systems Analysis, Laxenburg, Austria.Google Scholar
  42. Miller, J.R. and Lad, F.: 1984, ‘Flexibility, Learning and Irreversibility in Environmental Decisions: A Bayesian Approach’. Journal of Environmental Economics and Management 11, 161–172.CrossRefGoogle Scholar
  43. Nordhaus, W.: 1994, Managing the Global Commons: The Economics of Climate Change. London: MIT Press.Google Scholar
  44. Nordhaus, W.D. and Yang, Z.: 1996, ‘RICE: A Regional Dynamic General Equilibrium Model of Optimal Climate-Change Policy’. Yale University and MIT.Google Scholar
  45. Obstfeld, M. and Rogoff, K.: 1996, Foundations of International Macroeconomics. Massachusetts: MIT Press.Google Scholar
  46. Radner, R.: 1982, ‘Equilibrium Under Uncertainty’. In: K.J. Arrow and M.D. Intriligator (eds.), Handbook of Mathematical Economics, Vol. 1, Amsterdam: North-Holland Publishing Company, pp. Ch. 20.Google Scholar
  47. Ramanathan, R.: 1985, An Introduction to the Theory of Economic Growth. New York: Springer-Verlag.Google Scholar
  48. Schwartz, A., Polak, E. and Chen, Y.: 1997, Recursive Integration Optimal Trajectory Solver 95: A Matlab Toolbox for Solving Optimal Control Problems, Version 1.0 for Windows. California: Stanford University.Google Scholar
  49. Schoonbeek, L. Sterken, E. and Kuipers, S.K. (Eds.): 1995, Methods and Applications of Economic Dynamics. Amsterdam: North Holland.Google Scholar
  50. Sengupta, J.K. and Fanchon, P.: 1997, Control Theory Methods in Economics. Boston: Kluwer Academic Publishers.CrossRefGoogle Scholar
  51. Siebert, H.: 1998, Economics of the Environment: Theory and Policy. Berlin: Springer-Verlag.Google Scholar
  52. Smulders, J.A.: 1994, ‘Growth, Market Structure, and the Environment’. Ph.D. thesis, Tillburg University, Tillburg.Google Scholar
  53. Tapiero, C.S.: 1998, Applied Stochastic Models and Control for Insurance and Finance. London: Kluwer Academic Publishers.CrossRefGoogle Scholar
  54. Tintner, G. and Sengupta, J.K.: 1969, Stochastic Economics: Stochastic Processes Control and Programming. New York: Academic Press.Google Scholar
  55. Wagner, H.M.: 1975, Principles of Operations Research. New Jersey: Prentice-Hall.Google Scholar
  56. Xepapadeas, A.: 1997, Advanced Principles in Environmental Policy. Cheltenham: Edward Elgar Publishing.Google Scholar

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Sardar M. N. Islam

There are no affiliations available

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