Maximum entropy and Bayesian approaches to the ratio problem

Journal of Econometrics

Volumn 104, Issue 2, 2001, Pages 289-313

  Shen, Edward Z ^a   Perloff, Jeffrey M ^b  

^a Gatorcom   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Agricultural supply response; Bayesian estimation; BMOM; Generalized maximum entropy; MELO; Shrinkage; Simulation

Indexed keywords

EID: 0347156636     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-4076(01)00082-3     Document Type: Article

References (39)

1. Askari, A., Cummings, T., 1977. Estimating agricultural supply response with the Nerlove model: a survey. International Economic Review 18, 257-329.
2. Bewley, R., Fiebig, D., 1990. Why are long-run parameter estimates so disparate? Review of Economics and Statistics 72, 345-349.
3. Bresnahan, T.F., 1982. The oligopoly solution concept is identified. Economics Letters 10, 87-92.
4. Csiszár, I., 1991. Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems. The Annals of Statistics 19, 2032-2066.
5. Diebold, F.X., Lamb, R.L., 1997. Why are estimates of agricultural supply response so variable? Journal of Econometrics 76, 357-373.
6. Geweke, J., 1986. Exact inference in the inequality constrained normal linear regression model. Journal of Applied Econometrics 1, 127-141.
7. Golan, A., Judge, G., Miller, D., 1996. Maximum Entropy Econometrics: Robust Estimation with Limited Data. Wiley, New York.
8. Golan, A., Judge, G., Miller, D., 1997a. Information recovery in simultaneous equation models. In: Ullah, A., Giles, D. (Eds.), Handbook of Applied Economic Statistics. Marcel Dekker, New York.
9. Golan, A., Judge, G., Perloff, J.M., 1997b. Recovering information from censored and ordered multinomial response data. Journal of Econometrics 79, 23-51.
10. Jaynes, E.T., 1957a. Information theory and statistical mechanics. Physics Review 106, 620-630.
11. Jaynes, E.T., 1957b. Information theory and statistical mechanics, II. Physics Review 108, 171-190.
12. Jaynes, E.T., 1984. Prior information and ambiguity in inverse problems. In: McLaughin, D.W. (Ed.), Inverse Problems. American Mathematical Society, Providence, RI.
13. Kullback, J., 1959. Information Theory and Statistics. Wiley, New York.
14. LaFrance, J.T., 1999. Inferring the nutrient content of food with prior information. American Journal of Agricultural Economics 81, 728-734.
15. Lehmann, E.L., Popper Shaffer, J., 1988. Inverted distributions. American Statistician 42, 191-194.
16. Levine, R.D., 1980. An information theoretical approach to inversion problems. Journal of Physics A 13, 91-108.
17. Marsaglia, G., 1965. Ratios of normal variables and ratios of sums of uniform variables. American Statistical Association Journal 60, 193-204.
18. Muth, J., 1960. Optimal properties of exponentially weighted forecasts. Journal of the American Statistical Association 66, 299-305.
19. Nerlove, M., 1979. The dynamics of supply: retrospect and prospect. American Journal of Agricultural Economics 61, 874-888.
20. Nerlove, M., Addison, W., 1958. Statistical estimator of long-run elasticities of supply and demand. Journal of Farm Economics 40, 861-880.
21. Shannon, C.E., 1948. A mathematical theory of communication. Bell System Technical Journal 27, 379-423.
22. Shen, Z., 1999. Essays of empirical studies in agricultural and resource economics. Ph.D. Dissertation, University of California, Berkeley.
23. Shore, J.E., Johnson, R.W., 1980. Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy. IEEE Transactions on Information Theory IT-26, 26-37.
24. Skilling, J., 1989. The axioms of maximum entropy. In: Skilling, J. (Ed.), Maximum Entropy and Bayesian Methods in Science and Engineering. Kluwer Academic, Dordrecht, pp. 173-187.
25. Zaman, A., 1981. Estimators without moments. Journal of Econometrics 15, 289-298.
26. Zellner, A., 1963. Decision rules for economic forecasting. Econometrica 31, 111-130.
27. Zellner, A., 1978. Estimator of functions of population means and regression coefficients including structural coefficients: a minimum expected loss approach. Journal of Econometrics 8, 127-158. Reprinted in Zellner, A., 1997. Bayesian Analysis in Econometrics and Statistics. Elgar.
28. Zellner, A., 1978. Estimator of functions of population means and regression coefficients including structural coefficients: a minimum expected loss approach. Journal of Econometrics 8, 127-158. Reprinted in Zellner, A., 1997. Bayesian Analysis in Econometrics and Statistics. Elgar.
29. Zellner, A., 1985. Bayesian econometrics. Econometrica 53, 253-269.
30. Zellner, A., 1986. Further results on Bayesian minimum expected loss estimates and posterior distributions for structural coefficients. In: Slottje, D.J. (Ed.), Advances in Econometrics. JAI Press, Greenwich, CT, pp. 171-182.
31. Zellner, A., 1994. Bayesian and non-Bayesian estimation using balanced loss functions. In: Gupta, S.S., Berger, J.O. (Eds.), Statistic Decision Theory and Related Topics, Vol. V. Springer, New York, NY, pp. 377-390.
32. Zellner, A., 1996. Bayesian method of moments/instrumental variables (BMOM/IV) analysis of mean and regression models. In: Lee, J., Johnson, W., Zellner, A. (Eds.), Modeling and Prediction: Honoring Seymour Geisser. Springer, Berlin.
33. Zellner, A., 1997. The finite sample properties of simultaneous equations estimates and estimators: Bayesian and non-Bayesian approaches. In: Bayesian Analysis in Econometrics and Statistics: The Zellner View and Papers. Edward Elgar Publishing Limited, Cheltenham, UK.
34. Zellner, A., 1999. New information-based econometric methods in agricultural economics: discussion. American Journal of Agricultural Economics 81, 742-746.
35. Zellner, A., Geisel, M.S., 1970. Analysis of distributed lag models with applications to consumption function estimation. Econometrica 38, 865-888.
36. Zellner, A., Park, S.B., 1979. Minimum expected loss (MELO) estimators for functions of parameters and structural coefficients of econometric models. Journal of the American Statistical Association 74, 185-193.
37. Zellner, A., Rossi, P.E., 1984. Bayesian analysis of dichotomous quantal response models. Journal of Econometrics 25, 365-393.
38. Zellner, A., Tiao, G.C., 1964. Bayesian analysis of the regression model with autocorrelated errors. Journal of the American Statistical Association 59, 763-778.
39. Zellner, A., Tobias, J., 2001. Further results on Bayesian method of moments analysis of the multiple regression model. International Economic Review 42, 121-140.