IDEAS home Printed from https://ideas.repec.org/p/qut/auncer/2006-6.html
   My bibliography  Save this paper

Limited Information Estimation and Evaluation of DSGE Models. Working paper #6

Author

Listed:
  • Martin Fukac
  • Adrian Pagan

    (National Centre for Econometric Research)

Abstract

We advance the proposal that DSGE models should not just be estimated and evaluated with reference to full information methods. These make strong assumptions and therefore there is uncertainty about their impact upon results. Some limited information analysis which can be used in a complementary way seems important. Because it is sometimes difficult to implement limited information methods when there are unobservable non-stationary variables in the system we present a simple method of overcoming this that involves normalizing the non-stationary variables with their permanent components and then estimating the estimating the resulting Euler equations. We illustrate the interaction between full and limited information methods in the context of a well-known open economy model of Lubik and Schorfheide. The transformation was effective in revealing possible mis-specifications in the equations of LS\'s system and the limited information analysis highlighted the role of priors in having a major influence upon the estimates.

Suggested Citation

  • Martin Fukac & Adrian Pagan, 2006. "Limited Information Estimation and Evaluation of DSGE Models. Working paper #6," NCER Working Paper Series 6, National Centre for Econometric Research.
    • Handle: RePEc:qut:auncer:2006-6
    as

    Download full text from publisher

    File URL: http://www.ncer.edu.au/papers/documents/WPNo6.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Singleton, Kenneth J., 1988. "Econometric issues in the analysis of equilibrium business cycle models," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 361-386.
    2. Binder,M. & Pesaran,H.M., 1995. "Multivariate Rational Expectations Models and Macroeconomic Modelling: A Review and Some New Results," Cambridge Working Papers in Economics 9415, Faculty of Economics, University of Cambridge.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Milani, Fabio, 2009. "Expectations, learning, and the changing relationship between oil prices and the macroeconomy," Energy Economics, Elsevier, vol. 31(6), pages 827-837, November.
    2. Martin Fukač & Adrian Pagan, 2010. "Limited information estimation and evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 55-70, January.
    3. Mardi Dungey & Adrian Pagan, 2009. "Extending a SVAR Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 85(268), pages 1-20, March.
    4. Andreas Beyer & Roger E. A. Farmer & Jérôme Henry & Massimiliano Marcellino, 2008. "Factor analysis in a model with rational expectations," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 271-286, July.
    5. Luca Fanelli, 2009. "Estimation of quasi-rational DSGE monetary models," Quaderni di Dipartimento 3, Department of Statistics, University of Bologna.
    6. A. R. Pagan & Mr. Douglas Laxton & Mr. Luis Catão, 2008. "Monetary Transmission in an Emerging Targeter: The Case of Brazil," IMF Working Papers 2008/191, International Monetary Fund.
    7. Gorodnichenko, Yuriy & Ng, Serena, 2010. "Estimation of DSGE models when the data are persistent," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 325-340, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martin Fukač & Adrian Pagan, 2010. "Limited information estimation and evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 55-70, January.
    2. Michael T. Kiley, 1997. "Staggered price setting and real rigidities," Finance and Economics Discussion Series 1997-46, Board of Governors of the Federal Reserve System (U.S.).
    3. Gary Koop & M. Hashem Pesaran & Ron P. Smith, 2013. "On Identification of Bayesian DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 300-314, July.
    4. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    5. Mariano Kulish & James Morley & Tim Robinson, 2014. "Estimating the expected duration of the zero lower bound in DSGE models with forward guidance," Discussion Papers 2014-32, School of Economics, The University of New South Wales.
    6. Karl Whelan, 2007. "Staggered Price Contracts And Inflation Persistence: Some General Results," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 111-145, February.
    7. Richard Mash, 2003. "A Note on Simple MSV Solution Methods for Rational Expectations Models of Monetary Policy," Economics Series Working Papers 173, University of Oxford, Department of Economics.
    8. Kapetanios, G. & Pagan, A. & Scott, A., 2007. "Making a match: Combining theory and evidence in policy-oriented macroeconomic modeling," Journal of Econometrics, Elsevier, vol. 136(2), pages 565-594, February.
    9. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    10. Adam Cagliarini & Mariano Kulish, 2013. "Solving Linear Rational Expectations Models with Predictable Structural Changes," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 328-336, March.
    11. Boehl, Gregor, 2022. "Efficient solution and computation of models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    12. Gregory, Allan W. & Smith, Gregor W., 1996. "Measuring business cycles with business-cycle models," Journal of Economic Dynamics and Control, Elsevier, vol. 20(6-7), pages 1007-1025.
    13. De Grauwe, Paul, 2008. "DSGE-Modelling: when agents are imperfectly informed," Working Paper Series 897, European Central Bank.
    14. McCallum, Bennett T., 2004. "On the relationship between determinate and MSV solutions in linear RE models," Economics Letters, Elsevier, vol. 84(1), pages 55-60, July.
    15. Ghysels, E., 1992. "Charistmas, Spring and the Dawning of Economic Recovery," Cahiers de recherche 9215, Universite de Montreal, Departement de sciences economiques.
    16. Mariano Kulish & Adrian Pagan, 2017. "Estimation and Solution of Models with Expectations and Structural Changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 255-274, March.
    17. Andersen, Kaare Guttorm & Männistö, Hanna-Leena, 1995. "Output gaps and the government budget balance: The case of Finland," Bank of Finland Research Discussion Papers 27/1995, Bank of Finland.
    18. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    19. Luca Fanelli & Giulio Palomba, 2011. "Simulation‐based tests of forward‐looking models under VAR learning dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 762-782, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:qut:auncer:2006-6. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: School of Economics and Finance (email available below). General contact details of provider: https://edirc.repec.org/data/ncerrau.html .

    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.