IDEAS home Printed from https://ideas.repec.org/a/bla/jecsur/v8y1994i1p1-34.html
   My bibliography  Save this article

Recent Progress in Applied Bayesian Econometrics

Author

Listed:
  • 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
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    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. Francis W. Ahking, 2004. "The Power of the "Objective" Bayesian Unit-Root Test," Working papers 2004-14, University of Connecticut, Department of Economics.
    13. 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.
    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. 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.
    16. 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.
    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. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676.
    19. 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.
    20. Justel, Ana & Peña, Daniel & 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.
    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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jecsur:v:8:y:1994:i:1:p:1-34. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0950-0804 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.