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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

Suggested Citation

  • Koop, Gary, 1994. "Recent Progress in Applied Bayesian Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 8(1), pages 1-34, March.
    • Handle: RePEc:bla:jecsur:v:8:y:1994:i:1:p:1-34
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    Cited by:

    1. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    2. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Hospital efficiency analysis through individual effects : A Bayesian approach," Other publications TiSEM dd6fed13-3fda-461f-9393-e, Tilburg University, School of Economics and Management.
    3. Francis W. Ahking, 2004. "The Power of the "Objective" Bayesian Unit-Root Test," Working papers 2004-14, University of Connecticut, Department of Economics.
    4. 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.
    5. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    6. Grassi, S. & Proietti, T., 2014. "Characterising economic trends by Bayesian stochastic model specification search," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 359-374.
    7. 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).
    8. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(3), pages 409-431, August.
    9. 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.
    10. Marta Arbelo-Pérez & Pilar Pérez-Gómez & Antonio Arbelo, 2023. "Profit efficiency and its determinants in the agricultural sector: A Bayesian approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(11), pages 436-445.
    11. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    12. Thabo M. Mokoena & Rangan Gupta & Reneé Van Eyden, 2009. "Testing For Ppp Using Sadc Real Exchange Rates," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 351-362, September.
    13. Phuc Trong Ho & Michael Burton & Atakelty Hailu & Chunbo Ma, 2024. "Transient and Persistent Technical Efficiencies in Rice Farming: A Generalized True Random-Effects Model Approach," Econometrics, MDPI, vol. 12(3), pages 1-18, August.
    14. Justel, Ana & Sánchez, María Jesús, 1994. "Grupos atípicos en modelos econométricos," DES - Documentos de Trabajo. Estadística y Econometría. DS 10755, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Marta Arbelo-Pérez & Pilar Pérez-Gómez & Antonio Arbelo, . "Profit efficiency and its determinants in the agricultural sector: A Bayesian approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 0.
    16. 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).
    17. 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.
    18. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    19. Justin L. Tobias & Mingliang Li, 2004. "Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures," Journal of Economic Surveys, Wiley Blackwell, vol. 18(2), pages 153-180, April.
    20. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    21. 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.
    22. 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.

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