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

Author

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  • 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
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    References listed on IDEAS

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    3. Adrian Mander, 2000. "3D surface plots," Stata Technical Bulletin, StataCorp LP, vol. 9(51).
    4. Marcelo J. Moreira & Brian P. Poi, 2003. "Implementing tests with correct size in the simultaneous equations model," Stata Journal, StataCorp LP, vol. 3(1), pages 57-70, March.
    5. Parente, Paulo M.D.C. & Santos Silva, J.M.C., 2012. "A cautionary note on tests of overidentifying restrictions," Economics Letters, Elsevier, vol. 115(2), pages 314-317.
    6. Liyang Sun, 2018. "Implementing valid two-step identification-robust confidence sets for linear instrumental-variables models," Stata Journal, StataCorp LP, vol. 18(4), pages 803-825, December.
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    Cited by:

    1. Jan F. Kiviet, 2020. "Causes Of Haze And Its Health Effects In Singapore: A Replication Study," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(06), pages 1367-1387, December.

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