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Consistently bounding parameter values with one instrument and two endogenous explanatory variables

Author

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  • Richard A Dunn

    () (Texas A&M University)

Abstract

The current paper considers a linear regression framework with two endogenous regressors, but only one instrument that is correlated with both. I demonstrate that under reasonable conditions, some of which are testable from the data, these different sources of endogeneity act in opposing directions and hence IV regression can generate economically meaningful bounds.

Suggested Citation

  • Richard A Dunn, 2012. "Consistently bounding parameter values with one instrument and two endogenous explanatory variables," Economics Bulletin, AccessEcon, vol. 32(2), pages 1074-1081.
  • Handle: RePEc:ebl:ecbull:eb-11-00833
    as

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    File URL: http://www.accessecon.com/Pubs/EB/2012/Volume32/EB-12-V32-I2-P101.pdf
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    References listed on IDEAS

    as
    1. Victor Chernozhukov & Sokbae Lee & Adam M. Rosen, 2013. "Intersection Bounds: Estimation and Inference," Econometrica, Econometric Society, vol. 81(2), pages 667-737, March.
    2. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
    3. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    4. Richard Ashley, 2009. "Assessing the credibility of instrumental variables inference with imperfect instruments via sensitivity analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 325-337, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    endogeneity; instrumental variables; bounding; under-identification;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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