[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2011-219.html
   My bibliography  Save this paper

Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model

Author

Listed:
  • Mr. Maxym Kryshko
Abstract
When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simple monetary DSGE model on a richer data set. Using post-1983 U.S.data on real output, inflation, nominal interest rates, measures of inverse money velocity, and a large panel of informational series, we compare the data-rich DSGE model with the regular - few observables, perfect measurement - DSGE model in terms of deep parameter estimates, propagation of monetary policy and technology shocks and sources of business cycle fluctuations. We document that the data-rich DSGE model generates a higher implied duration of Calvo price contracts and a lower slope of the New Keynesian Phillips curve. To reduce the computational costs of the likelihood-based estimation, we employed a novel speedup as in Jungbacker and Koopman (2008) and achieved the time savings of 60 percent.

Suggested Citation

  • Mr. Maxym Kryshko, 2011. "Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model," IMF Working Papers 2011/219, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2011/219
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=25250
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Mr. Maxym Kryshko, 2011. "Data-Rich DSGE and Dynamic Factor Models," IMF Working Papers 2011/216, International Monetary Fund.
    2. Zhicheng Zhou & Prapatchon Jariyapan, 2013. "The impact of macroeconomic policies to real estate market in People's Republic of China," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 2(3), pages 75-92, September.
    3. Sacha Gelfer, 2019. "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 18-41, April.
    4. Bowen Fu, Ivan Mendieta-Muñoz, 2023. "Structural shocks and trend inflation," Working Paper Series, Department of Economics, University of Utah 2023_04, University of Utah, Department of Economics.

    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:imf:imfwpa:2011/219. 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: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.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.