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

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  • Zellner, Arnold
  • Tobias, Justin

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. Copyright 2001 by American Economic Association.

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 42 (2001)
Issue (Month): 1 (February)
Pages: 121-40

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Handle: RePEc:ier:iecrev:v:42:y:2001:i:1:p:121-40

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Cited by:
  1. 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.
  2. Kleibergen, Frank & Zivot, Eric, 2003. "Bayesian and classical approaches to instrumental variable regression," Journal of Econometrics, Elsevier, vol. 114(1), pages 29-72, May.
  3. Lahiri, Kajal & Gao, Chuanming, 2002. "A note on the double k-class estimator in simultaneous equations," MPRA Paper 22323, University Library of Munich, Germany.
  4. 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.
  5. Zellner, Arnold, 2006. "S. James Press And Bayesian Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 10(05), pages 667-684, November.
  6. Zellner, Arnold, 2007. "Some aspects of the history of Bayesian information processing," Journal of Econometrics, Elsevier, vol. 138(2), pages 388-404, June.
  7. 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.
  8. 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.
  9. Hélène Bonnal & Éric Renault, 2004. "On the Efficient Use of the Informational Content of Estimating Equations: Implied Probabilities and Euclidean Empirical Likelihood," CIRANO Working Papers 2004s-18, CIRANO.
  10. 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.
  11. 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.
  12. 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.
  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. Wu, Ximing, 2003. "Calculation of maximum entropy densities with application to income distribution," Journal of Econometrics, Elsevier, vol. 115(2), pages 347-354, August.
  16. 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.

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