IDEAS home Printed from https://ideas.repec.org/p/boc/usug20/15.html
   My bibliography  Save this paper

kinkyreg: Instrument-free inference for linear regression models with endogenous regressors

Author

Listed:
  • Sebastian Kripfganz

    () (University of Exeter Business School)

  • Jan F. Kiviet

    () (Amsterdam School of Economics)

Abstract

In models with endogenous regressors, a standard regression approach is to exploit just- or over-identifying orthogonality conditions by using instrumental variables. In just-identified models, the identifying orthogonality assumptions cannot be tested without the imposition of other non-testable assumptions. While formal testing of over-identifying restrictions is possible, its interpretation still hinges on the validity of an initial set of untestable just-identifying orthogonality conditions. We present the kinkyreg Stata program for kinky least squares (KLS) inference that adopts an alternative approach to identification. By exploiting non-orthogonality conditions in the form of bounds on the admissible degree of endogeneity, feasible test procedures can be constructed that do not require instrumental variables. The KLS confidence bands can be more informative than confidence intervals obtained from instrumental variable estimation, in particular when the instruments are weak. Moreover, the approach facilitates a sensitivity analysis for the standard instrumental variable inference. In particular, it allows assessment of the validity of previously untestable just-identification exclusion restrictions. Further KLS-based tests include heteroskedasticity, function form, and serial correlation tests.

Suggested Citation

  • Sebastian Kripfganz & Jan F. Kiviet, 2020. "kinkyreg: Instrument-free inference for linear regression models with endogenous regressors," London Stata Conference 2020 15, Stata Users Group.
  • Handle: RePEc:boc:usug20:15
    as

    Download full text from publisher

    File URL: http://repec.org/usug2020/Kripfganz_u20.pdf
    File Function: presentation materials
    Download Restriction: no

    More about this item

    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:boc:usug20:15. 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). General contact details of provider: http://edirc.repec.org/data/stataea.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.