Bayesian Methods and Entropy in Economics and Econometrics

  • Arnold Zellner
Part of the Fundamental Theories of Physics book series (FTPH, volume 43)


A discussion of some previous and current uses of Bayesian methods and entropy in economics and econometrics is presented.


Maximum Entropy Bayesian Method Posterior Density Side Condition Prior Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Aigner, D.J. and C.N. Morris (eds.): 1979, ‘Experimental Design in Econometrics’, Annals J. of Econometrics 11, 205 pp.Google Scholar
  2. Aigner, D.J. and A. Zellner (eds.): 1988, ‘Causality’, Annals, J. of Econometrics 39 234 pp.Google Scholar
  3. Bawa, V.S., S.J. Brown, and R.W. Klein: 1979, Estimation Risk and Optimal Portfolio Choice, North-Holland, Amsterdam.zbMATHGoogle Scholar
  4. Berger, J.O.: 1985, Statistical Decision Theory (2nd ed.), Springer-Verlag, New York.zbMATHGoogle Scholar
  5. Bernardo, J.: 1979, ‘Reference Posterior Distributions for Bayesian Inference’, J. Royal Statistical Society B, 41, 113–147.MathSciNetGoogle Scholar
  6. Boyer, M. and R.E. Kihlstrom (ed.): 1984, Bayesian Models in Economic Theory, North-Holland, Amsterdam.zbMATHGoogle Scholar
  7. Cobb, L., P. Koppstein, and N.H. Chen: 1983, ‘Estimation and Moment Recursion Relations for Multimodal Distributions of the Exponential Family’, J. American Statistical Association 78, 124–130.MathSciNetzbMATHCrossRefGoogle Scholar
  8. Cohen, M. and J.Y. Jaffray: 1980, ‘Rational Behavior Under Complete Ignorance’, Econometrica 48, 1281–1300.MathSciNetzbMATHCrossRefGoogle Scholar
  9. Cox, R.T.: 1961, The Algebra of Probable Inference, John Hopkins Press, Baltimore.zbMATHGoogle Scholar
  10. Cyert, R.M. and M.H. DeGroot: 1987, Bayesian Analysis and Uncertainty in Economic Theory, Chapman and Hall Ltd., London.CrossRefGoogle Scholar
  11. Davis, H.T.: 1941, The Theory of Econometrics, Principia Press, Bloomington, Indiana.zbMATHGoogle Scholar
  12. Fienberg, S.E. and A. Zellner: 1975, Studies in Bayesian Econometrics and Statistics in Honor of Leonard J. Savage, North-Holland, Amsterdam.zbMATHGoogle Scholar
  13. Feigl, H.: 1953, ‘Notes on Causality’, in Readings in the Philosophy of Science, H. Feigl and M. Brodbeck (eds.), Appleton-Century-Crofts, New York, 408–418.Google Scholar
  14. Friedman, M.: 1953, Essays in Positive Economics, University of Chicago Press, Chicago.Google Scholar
  15. Garcia-Ferrer, A.P., R.A. Highfield, F. Palm, and A. Zellner: 1987, ‘Macroeconomic Forecasting Using Pooled International Data’, J. of Business and Economic Statistics 5, 53–67.Google Scholar
  16. Geisel, M.S.: 1975, ‘Bayesian Comparisons of Simple Macroeconomic Models’, Studies in Bayesian Econometrics and Statistics in Honor of Leonard J. Savage, S.E. Fienberg and A. Zellner (eds.), North-Holland, Amsterdam, 227–256.Google Scholar
  17. Geisser, S., J. Hodges, S.J. Press, and A. Zellner (eds.): 1990, Bayesian and Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard, North-Holland, Amsterdam.zbMATHGoogle Scholar
  18. Goel, P.K. and A. Zellner (eds.): 1986, Bayesian Inference and Decision Techniques: Essays in Honor of Bruno de Finetti, North-Holland, Amsterdam.zbMATHGoogle Scholar
  19. Golan, A.: 1988, A Discrete Stochastic Model of Economic Production and a Model of Fluctuations in Production-Theory and Empirical Evidence, Ph.D. Thesis, Department of Agricultural Economics, University of Haifa, Haifa, Israel.Google Scholar
  20. Grandy, C.: 1991, ‘The Principle of Maximum Entropy and the Difference Between Risk and Uncertainty’, Proceedings, Tenth International MaxEnt Workshop, Laramie, Wyoming, Kluwer, Dordrecht.Google Scholar
  21. Green, W.H.: 1990, Econometric Analysis, Macmillan, New York.Google Scholar
  22. Haavelmo, T.: 1944, ‘The Probability Approach in Econometrics’, Supplement to Econometrica 12, 115 pp.Google Scholar
  23. Hill, B.M.: 1988, ‘Comment’, American Statistician 42, 281–282.Google Scholar
  24. Hood, Wm.C. and T.C. Koopmans: 1953, Studies in Econometric Method, John Wiley & Sons, Inc., New York.zbMATHGoogle Scholar
  25. Jaynes, E.T.: 1968, ‘Prior Probabilitites’, IEEE Transactions on Systems Science and Cybernetics, SSC-4, 227–241.CrossRefGoogle Scholar
  26. Jaynes, E.T.: 1982a, ‘How Should We Use Entropy in Economics? (Some Half-Baked Ideas in Need of Criticism)’, manuscript.Google Scholar
  27. Jaynes, E.T.: 1988, ‘Comment’, American Statistician 42, 280–281.Google Scholar
  28. Jeffreys, H.: 1967, Theory of Probability (3rd rev. ed.), Oxford University Press, London.Google Scholar
  29. Judge, G.G., W.E. Griffiths, R.C. Hill, H. Lütkepohl, and T.C. Lee, The Theory and Practice of Econometrics (2nd ed.), John Wiley & Sons, Inc., New York.Google Scholar
  30. Kloek, T. and Y. Haitovsky (eds.): 1988, Competing Statistical Paradigms in Econometrics, papers presented at the International Conference on the Foundations of Statistical Inference, Israel, 1985; Annals, Journal of Econometrics 37, 192 pp.Google Scholar
  31. Lindley, D.V.: 1956, ‘On a Measure of Information Provided by an Experiment’, Annals of Mathematical Statistics 27, 986–1005.MathSciNetzbMATHCrossRefGoogle Scholar
  32. Lisman, J.H.C.: 1949, ‘Econometrics and Thermodynamics: A Remark on Davis’ Theory of Budgets’, Econometrica 17, 59–62.CrossRefGoogle Scholar
  33. Maasoumi, E.: 1990, ‘Information Theory’, The New Palgrave Econometrics, J. Eatwell, M. Millgate, and P. Newman (eds.), W.W. Norton & Co., New York, 101–112.Google Scholar
  34. Min, C.K. and A. Zellner: 1990, ‘Bayesian and Non-Bayesian Methods for Combining Models and Forecasts with Applications to Forecasting International Growth Rates’, manuscript, H.G.B. Alexander Research Foundation, University of Chicago.Google Scholar
  35. Monahan, J.F.: 1983, ‘Fully Bayesian Analysis of ARMA Time Series Models’, J. of Econometrics 21, 307–331.zbMATHCrossRefGoogle Scholar
  36. Pearson, K.: 1938, The Grammar of Science, Everyman, London.Google Scholar
  37. Poirier, D.J.: 1989, ‘A Report from the Battlefront’, J. of Business and Economic Statistics 7, 137–140.Google Scholar
  38. Press, S.J.: 1989, Bayesian Statistics: Principles, Models and Applications, John Wiley & Sons, Inc., New York.zbMATHGoogle Scholar
  39. Rao, C.R.: 1987, ‘Differential Metrics in Probability Spaces’, Differential Geometry in Statistical Inference 10, Institute of Mathematical Statistics Lecture Notes-Monograph Series, Institute of Mathematical Statistics, Hayward, California, Chapter 5, 217–240.CrossRefGoogle Scholar
  40. Ryu, H.K.: 1990, Orthogonal Basis and Maximum Entropy Estimation of Probability Density and Regression Functions, doctoral dissertation, Department of Economics, University of Chicago.Google Scholar
  41. Shore, J.E. and R.W. Johnson: 1980, ‘Axiomatic Derivation of the Principle of maximum Entropy and the Principle of Cross-Entropy’, IEEE Transactions on Information Theory IT-26, 26–37.MathSciNetCrossRefGoogle Scholar
  42. Theil, H.: 1967, Economics and Information Theory, North-Holland, Amsterdam.Google Scholar
  43. Zellner, A.: 1971, An Introduction to Bayesian Inference in Econometrics, John Wiley & Sons, Inc., New York; reprinted in 1987 by Krieger Publishing Co., Malabar, Florida.zbMATHGoogle Scholar
  44. Zellner, A.: 1977, ‘Maximal Data Information Prior Distributions’, New Developments in the Applications of Bayesian Methods, A. Aykac and C. Brumat (eds.), North-Holland, Amsterdam, 211–232.Google Scholar
  45. Zellner, A. (ed.): 1980, Bayesian Analysis in Econometrics and Statistics: Essays in Honor of Harold Jeffreys, North-Holland, Amsterdam.zbMATHGoogle Scholar
  46. Zellner, A.: 1984, Basic Issues in Econometrics, University of Chicago Press, Chicago.Google Scholar
  47. Zellner, A.: 1985, ‘Bayesian Econometrics’, Econometrica 53, 253–269.MathSciNetzbMATHCrossRefGoogle Scholar
  48. Zellner, A.: 1986a: Presentation to Bayesian Study Year Meeting, Warwick University, Warwick, England.Google Scholar
  49. Zellner, A.: 1986b: ‘Bayesian Estimation and Prediction Using Asymmetric Loss Functions’, J. of the American Statistical Association 81, 446–451.MathSciNetzbMATHCrossRefGoogle Scholar
  50. Zellner, A.: 1988, ‘Optimal Information Processing and Bayes Theorem’, American Statistician 42, 278–284.MathSciNetGoogle Scholar
  51. Zellner, A. and R.A. Highfield: 1982, ‘Calculation of Maximum Entropy Distributions and Approximation of Marginal Posterior Distributions’, presented in NBER-NSF Seminar on Bayesian Inference, October, 1982 and published in J. of Econometrics 37 (1988), 195–210.Google Scholar
  52. Zellner, A., C. Hong, and G.M. Gulati: 1990, ‘Turning Points in Economic Time Series Loss Structures and Bayesian Forecasting’, Bayesian and Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard, S. Geisser, J. Hodges, S.J. Press, and A. Zellner (eds.), North-Holland, Amsterdam, 371–396.Google Scholar
  53. Zellner, A., C. Hong, and C. Min: 1989, ‘Forecasting Turning Points in International Output Growth Rates Using Bayesian Exponentially Weighted Autoregresion, Time Varying Parameter and Pooling Techniques’, manuscript, Graduate School of Business, University of Chicago, to appear in J. of Econometrics.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1991

Authors and Affiliations

  • Arnold Zellner
    • 1
  1. 1.Graduate School of BusinessUniversity of ChicagoChicagoUSA

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