IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-3-662-63982-5_10.html
   My bibliography  Save this book chapter

Empirical Methods: Frequentist Estimation

In: Economic Growth

Author

Listed:
  • Alfonso Novales

    (Complutense University of Madrid)

  • Esther Fernández

    (Complutense University of Madrid)

  • Jesús Ruiz

    (Complutense University of Madrid)

Abstract

The chapter starts with the Generalized Method of Moments estimator, describing its main properties, and applying it to the estimation of an equilibrium asset pricing model. After that, we explain the implementation of the Maximum Likelihood estimator. The Kalman filter, the main tool for the numerical evaluation of the likelihood on the state-space representation of the model, is discussed in detail. We estimate cyclical and trend components in US GDP and the unemployment rate. Finally, we compute the ML estimator to the Hansen (Journal of Monetary Economics 16:309–327, 1985) model of indivisible labor. We explain MATLAB programs provided to estimate structural parameters and generate some interesting properties of Growth models, as impulse responses to supply and demand shocks, and the decomposition of the variance of forecast errors.

Suggested Citation

  • Alfonso Novales & Esther Fernández & Jesús Ruiz, 2022. "Empirical Methods: Frequentist Estimation," Springer Texts in Business and Economics, in: Economic Growth, edition 3, chapter 10, pages 539-579, Springer.
    • Handle: RePEc:spr:sptchp:978-3-662-63982-5_10
    DOI: 10.1007/978-3-662-63982-5_10
    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.

    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:spr:sptchp:978-3-662-63982-5_10. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.