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Identification of sensitivity to variation in endogenous variables

Author

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  • Andrew Chesher

    (Institute for Fiscal Studies and University College London)

Abstract

This lecture explores conditions under which there is identification of the impact on an outcome of exogenous variation in a variable which is endogenous when data are gathered. The starting point is the Cowles Commission linear simultaneous equations model. The parametric and additive error restrictions of that model are successively relaxed and modifications to covariation,order and rank conditions that maintain identifiability are presented. Eventually a just-identifying, non-falsifiable model permitting nonseparablity of latent vari-ates and devoid of parametric restrictions is obtained. The model requires the endogenous variable to be continuously distributed. It is shown that relaxing this restriction results in loss of point identification but set identification is possible if an additional covariation restriction is introduced. Relaxing other restrictions presents significant challenges. The A.W.H. Phillips Lecture, presented at the Australasian Meetings of the Econometric Society, July 7th 2004.

Suggested Citation

  • Andrew Chesher, 2004. "Identification of sensitivity to variation in endogenous variables," CeMMAP working papers CWP10/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:10/04
    as

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    File URL: http://cemmap.ifs.org.uk/wps/cwp102004.pdf
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    References listed on IDEAS

    as
    1. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, September.
    2. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
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    7. Andrew Chesher, 2002. "Semiparametric identification in duration models," CeMMAP working papers 20/02, Institute for Fiscal Studies.
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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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