IDEAS home Printed from https://ideas.repec.org/p/qsh/wpaper/309271.html
   My bibliography  Save this paper

How to use economic theory to improve estimators

Author

Listed:
  • Pirmin Fessler
  • Kasy, Maximilian

Abstract

We propose to use economic theories to construct estimators that perform well when the theories' empirical implications are approximately correct, but are robust even if the theories are completely wrong. We describe a general construction of such estimators using the empirical Bayes paradigm. We implement this construction in various settings, including labor demand and wage inequality, asset pricing, economic decision theory, and structural discrete choice models. We provide theoretical characterizations of the behavior of the proposed estimators, and evaluate them using Monte Carlo simulations. Our approach is an alternative to the use of theory as something to be tested or to be imposed on estimates. Our approach complements uses of theory for identification and extrapolation.

Suggested Citation

  • Pirmin Fessler & Kasy, Maximilian, 2017. "How to use economic theory to improve estimators," Working Paper 309271, Harvard University OpenScholar.
  • Handle: RePEc:qsh:wpaper:309271
    as

    Download full text from publisher

    File URL: http://scholar.harvard.edu/kasy/node/309271
    Download Restriction: no

    Citations

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


    Cited by:

    1. Denni Tommasi & Alexander Wolf, 2016. "Overcoming Weak Identification in the Estimation of Household Resource Shares," Working Papers ECARES ECARES 2016-12, ULB -- Universite Libre de Bruxelles.
    2. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2018.
    3. St├ęphane Bonhomme & Martin Weidner, 2018. "Minimizing sensitivity to model misspecification," CeMMAP working papers CWP59/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 33-49, March.
    5. repec:eee:ecolet:v:163:y:2018:i:c:p:75-78 is not listed on IDEAS

    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:qsh:wpaper:309271. 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: (Richard Brandon). General contact details of provider: http://edirc.repec.org/data/cbrssus.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.

    We have no 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.

    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.