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Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model

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Author Info

  • Tobias, Justin
  • Zellner, Arnold

Abstract

In this article we extend previous BMOM results by showing how information about a variance parameter and its relation to regression coefficients produces a rich class of postdata densities for regression parameters. Prediction and model selection techniques are also described. We also discuss the well-documented link between cross-entropy and the average log odds and then use this criterion in an experiment to compare results obtained from BMOM and Bayes approaches using data generated from known models.

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Bibliographic Info

Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12021.

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Date of creation: 01 Jan 2001
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Publication status: Published in International Economic Review 2001, vol. 42, pp. 121-139
Handle: RePEc:isu:genres:12021

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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
Phone: +1 515.294.6741
Fax: +1 515.294.0221
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Web page: http://www.econ.iastate.edu
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Cited by:
  1. Zellner, Arnold, 2007. "Some aspects of the history of Bayesian information processing," Journal of Econometrics, Elsevier, vol. 138(2), pages 388-404, June.
  2. Antoine, Bertille & Bonnal, Helene & Renault, Eric, 2007. "On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood," Journal of Econometrics, Elsevier, vol. 138(2), pages 461-487, June.
  3. Frank Kleibergen & Eric Zivot, 1998. "Bayesian and Classical Approaches to Instrumental Variable Regression," Working Papers 0063, University of Washington, Department of Economics.
  4. Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Bayesian measurement of productivity and efficiency in the presence of undesirable outputs: crediting electric utilities for reducing air pollution," Journal of Econometrics, Elsevier, vol. 126(2), pages 445-468, June.
  5. Agee, Mark D. & Atkinson, Scott E. & Crocker, Thomas D. & Williams, Jonathan W., 2014. "Non-separable pollution control: Implications for a CO2 emissions cap and trade system," Resource and Energy Economics, Elsevier, vol. 36(1), pages 64-82.
  6. Komunjer, Ivana & Ragusa, Giuseppe, 2009. "Existence and Uniqueness of Semiparametric Projections," University of California at San Diego, Economics Working Paper Series qt0wg3j51c, Department of Economics, UC San Diego.
  7. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
  8. Wu, Ximing, 2003. "Calculation of maximum entropy densities with application to income distribution," Journal of Econometrics, Elsevier, vol. 115(2), pages 347-354, August.
  9. Zellner, Arnold, 2010. "Bayesian shrinkage estimates and forecasts of individual and total or aggregate outcomes," Economic Modelling, Elsevier, vol. 27(6), pages 1392-1397, November.
  10. LaFrance, Jeffrey T., 1999. "An Econometric Model of the Demand for Food and Nutrition," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2z5516c2, Department of Agricultural & Resource Economics, UC Berkeley.
  11. Gao, Chuanming & Lahiri, Kajal, 2002. "A note on the double k-class estimator in simultaneous equations," Journal of Econometrics, Elsevier, vol. 108(1), pages 101-111, May.
  12. LaFrance, J. T. & Beatty, T. K. M. & Pope, R. D. & Agnew, G. K., 2002. "Information theoretic measures of the income distribution in food demand," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 235-257, March.
  13. Tack, Jesse, 2013. "A Nested Test for Common Yield Distributions with Applications to U.S. Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), April.
  14. Shen, Edward Z. & Perloff, Jeffrey M., 2001. "Maximum entropy and Bayesian approaches to the ratio problem," Journal of Econometrics, Elsevier, vol. 104(2), pages 289-313, September.
  15. R. A. L. Carter & A. Zellner, 2002. "The ARAR Error Model for Univariate Time Series and Distributed Lag Models," UWO Department of Economics Working Papers 20025, University of Western Ontario, Department of Economics.
  16. Zellner, Arnold, 2006. "S. James Press And Bayesian Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 10(05), pages 667-684, November.

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