IDEAS home Printed from https://ideas.repec.org/p/bfr/banfra/461.html
   My bibliography  Save this paper

Choosing the variables to estimate singular DSGE models

Author

Listed:
  • Canova, F.
  • Ferroni, F.
  • Matthes, C.

Abstract

We propose two methods to choose the variables to be used in the estimation of the structural parameters of a singular DSGE model. The first selects the vector of observables that optimizes parameter identification; the second the vector that minimizes the informational discrepancy between the singular and non-singular model. An application to a standard model is discussed and the estimation properties of different setups compared. Practical suggestions for applied researchers are provided.

Suggested Citation

  • Canova, F. & Ferroni, F. & Matthes, C., 2013. "Choosing the variables to estimate singular DSGE models," Working papers 461, Banque de France.
  • Handle: RePEc:bfr:banfra:461
    as

    Download full text from publisher

    File URL: https://publications.banque-france.fr/sites/default/files/medias/documents/working-paper_461_2013.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Luca Sala & Ulf Soderstrom & Antonella Trigari, 2010. "The Output Gap, the Labor Wedge, and the Dynamic Behavior of Hours," Working Papers 365, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Canova, Fabio & Sala, Luca, 2009. "Back to square one: Identification issues in DSGE models," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 431-449, May.
    3. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2009. "New Keynesian Models: Not Yet Useful for Policy Analysis," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 242-266, January.
    4. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    5. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
    6. Iskrev, Nikolay, 2010. "Local identification in DSGE models," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 189-202, March.
    7. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    8. Pablo A. Guerron-Quintana, 2010. "What you match does matter: the effects of data on DSGE estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 774-804.
    9. John H. Cochrane, 2011. "Determinacy and Identification with Taylor Rules," Journal of Political Economy, University of Chicago Press, vol. 119(3), pages 565-615.
    10. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    11. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    12. Zhongjun Qu & Denis Tkachenko, 2010. "Identification and Frequency Domain QML Estimation of Linearized DSGE Models," Boston University - Department of Economics - Working Papers Series WP2010-053, Boston University - Department of Economics.
    13. Kleibergen, Frank & Mavroeidis, Sophocles, 2009. "Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 293-311.
    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. Albonico, Alice & Calès, Ludovic & Cardani, Roberta & Croitorov, Olga & Ferroni, Filippo & Giovannini, Massimo & Hohberger, Stefan & Pataracchia, Beatrice & Pericoli, Filippo & Raciborski, Rafal & Rat, 2017. "The Global Multi-Country Model (GM): an Estimated DSGE Model for the Euro Area Countries," Working Papers 2017-10, Joint Research Centre, European Commission (Ispra site).
    2. repec:eee:macchp:v2-527 is not listed on IDEAS
    3. Monti, Francesca, 2015. "Can a data-rich environment help identify the sources of model misspecification?," LSE Research Online Documents on Economics 86320, London School of Economics and Political Science, LSE Library.
    4. Thorsten Drautzburg, 2014. "A Narrative Approach to a Fiscal DSGE Model," 2014 Meeting Papers 791, Society for Economic Dynamics.
    5. Yongquan Cao & Grey Gordon, 2016. "A Practical Approach to Testing Calibration Strategies," Caepr Working Papers 2016-004 Classification-C, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
    6. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    7. Massimo Franchi, 2013. "Comment on: Ravenna, F., 2007. Vector autoregressions and reduced form representations of DSGE models. Journal of Monetary Economics 54, 2048-2064," DSS Empirical Economics and Econometrics Working Papers Series 2013/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
    8. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, Elsevier.
    9. Wolters, Maik Hendrik, 2016. "How the Baby Boomers' Retirement Wave Distorts Model-Based Output Gap Estimates," Annual Conference 2016 (Augsburg): Demographic Change 145812, Verein für Socialpolitik / German Economic Association.
    10. Nikolay, Iskrev, 2014. "Choosing the variables to estimate singular DSGE models: Comment," Dynare Working Papers 41, CEPREMAP.
    11. Zhongjun Qu & Fan Zhuo, 2015. "Likelihood Ratio Based Tests for Markov Regime Switching," Boston University - Department of Economics - Working Papers Series wp2015-003, Boston University - Department of Economics.
    12. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.
    13. Zhongjun Qu, 2015. "A Composite Likelihood Framework for Analyzing Singular DSGE Models," Boston University - Department of Economics - Working Papers Series wp2015-002, Boston University - Department of Economics.
    14. Francesca Monti, 2015. "Can a data-rich environment help identify the sources of model misspecification?," Discussion Papers 1505, Centre for Macroeconomics (CFM).
    15. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    More about this item

    Keywords

    ABCD representation; Identification; Density ratio; DSGE models.;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:bfr:banfra:461. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael brassart). General contact details of provider: http://edirc.repec.org/data/bdfgvfr.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.