Advanced Search
MyIDEAS: Login

Two-stage regression without exclusion restrictions

Contents:

Author Info

  • Michael Barker

    (Georgetown University, Economics Department)

Registered author(s):

    Abstract

    Klein and Vella (2010) propose an estimator to fit a triangular system of two simultaneous linear equations with a single endogenous regressor. Models of this form are generally analyzed with two-stage least squares or IV methods, which require one or more exclusion restriction. In practice, the assumptions required to construct valid instruments are frequently difficult to justify. The KV estimator does not require an exclusion restriction; the same set of independent variables may appear in both equations. To account for endogeneity, the estimator constructs a control function using information from the conditional distribution of the error terms. Conditional variance functions are estimated semiparametrically, so distributional assumptions are minimized. I will present my Stata implementation of the semiparametric control function estimator, kvreg, and discuss the assumptions that must hold for consistent estimation. The kvreg estimator contains an undocumented implementation of Ichimura’s (1993) semiparametric least squares estimator, which I plan to fill-out into a stand-alone command.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://repec.org/norl13/barker.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by Stata Users Group in its series 2013 Stata Conference with number 15.

    as in new window
    Length:
    Date of creation: 01 Aug 2013
    Date of revision:
    Handle: RePEc:boc:norl13:15

    Contact details of provider:
    Web page: http://stata.com/meeting/new-orleans13/
    More information through EDIRC

    Related research

    Keywords:

    This paper has been announced in the following NEP Reports:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:boc:norl13:15. 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: (Christopher F Baum).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.