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Recent Progress in Applied Bayesian Econometrics

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  • Koop, Gary

Abstract

Bayesian methods are widely used by theoretical econometricians and statisticians but have not won widespread acceptance from applied researchers. After briefly describing the basics of the Bayesian approach, we discuss several issues relating to the empirical application of Bayesian methods. The existing Bayesian empirical literature is also partially summarized. The remainder of the paper offers a non-technical survey of some recent computational advances in Bayesian econometrics. The overall goal is to persuade economists that Bayesian methods are both computationally feasible and easy to implement in empirical research. Copyright 1994 by Blackwell Publishers Ltd

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Economic Surveys.

Volume (Year): 8 (1994)
Issue (Month): 1 (March)
Pages: 1-34

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Handle: RePEc:bla:jecsur:v:8:y:1994:i:1:p:1-34

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0950-0804

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Cited by:
  1. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
  2. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
  3. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
  4. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Hospital efficiency analysis through individual effects: A Bayesian approach," Discussion Paper 1994-47, Tilburg University, Center for Economic Research.
  5. Nalan Basturk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute.
  6. KOOP , Gary & OSIEWALSKI , Jacek & STEEL , Mark, 1995. "Bayesian Efficiency Analysis through Individual Effects : Hospital Cost Frontiers," CORE Discussion Papers 1995036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
  8. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
  9. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676.
  10. Hanrahan, Kevin F. & Westhoff, Patrick C. & Young, Robert E., II, 2001. "Trade Allocation Modeling: Comparing The Results From Armington And Locally Regular Ai Demand System Specifications Of A Uk Beef Import Demand Allocation Model," 2001 Annual meeting, August 5-8, Chicago, IL 20510, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  11. Francis W. Ahking, 2002. "Is the Bayesian Approach Necessarily Better than the Classical Approach in Unit-Root Test?," Working papers 2002-18, University of Connecticut, Department of Economics.
  12. Francis W. Ahking, 2004. "The Power of the "Objective" Bayesian Unit-Root Test," Working papers 2004-14, University of Connecticut, Department of Economics.
  13. Davis, George C., 2001. "Confirmation And Falsification Of Equilibrium Displacement Models," 2001 Annual meeting, August 5-8, Chicago, IL 20525, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  14. Loukia Meligkotsidou & Elias Tzavalis & Ioannis D. Vrontos, 2004. "A Bayesian Analysis of Unit Roots and Structural Breaks in the Level and the Error Variance of Autoregressive Models," Working Papers 514, Queen Mary, University of London, School of Economics and Finance.
  15. Heckelei, Thomas & Mittelhammer, Ronald C. & Wahl, Thomas I., 1997. "Bayesian Analysis of a Japanese Meat Demand System: A Robust Likelihood Approach," Discussion Papers 18783, University of Bonn, Institute for Food and Resource Economics.

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