IDEAS home Printed from https://ideas.repec.org/c/dge/qmrbcd/171.html
 

Matlab Code for Solving Linear Rational Expectation Models with Lagged Expectations Quickly and Easily

Author

Listed:
  • Alexander Meyer-Gohde

    (Technical University Berlin)

Abstract

This program contains a solution and an estimation method for linear rational expectations models with lagged expectations (e.g., sticky information). The solution method is a synthetic approach, combining state-space and infinite-MA representations with a simple system of linear equations. The advantage of the approach lies in its particular combination of methods familiar elsewhere in the literature to provide faster execution, more general applicability, and more straightforward usage than with existing algorithms. Bayesian methods are employed for estimation without the Kalman filter by using an alternative recursive algorithm to evaluate the likelihood function. The software provides impulse responses to anticipated and unanticipated innovations, simulations, and frequency-domain and simulated moments.

Suggested Citation

  • Alexander Meyer-Gohde, 2007. "Matlab Code for Solving Linear Rational Expectation Models with Lagged Expectations Quickly and Easily," QM&RBC Codes 171, Quantitative Macroeconomics & Real Business Cycles, revised Apr 2010.
  • Handle: RePEc:dge:qmrbcd:171
    as

    Download full text from publisher

    File URL: http://dge.repec.org/codes/meyer-gohde/Linlagex_Release_published.zip
    File Function: program code, examples and manual (published version)
    Download Restriction: none

    File URL: http://dge.repec.org/codes/meyer-gohde/LinLagEx_Release_1_1.zip
    File Function: program code, examples and manual (update)
    Download Restriction: none

    File URL: http://dge.repec.org/codes/meyer-gohde/LinLagEx_0_1.zip
    File Function: program code, examples and manual
    Download Restriction: none

    Other versions of this item:

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    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:dge:qmrbcd:171. 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: (Christian Zimmermann). General contact details of provider: http://edirc.repec.org/data/efrblus.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.