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Instrumental Values

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  • Andrew Chesher

Abstract

This paper studies the identification of partial differences of nonseparable structural functions. The paper considers triangular structures with no more stochastic unobservables than observable outcomes, that exhibit a degree of monotonicity with respect to variation in certain stochastic unobservables. It is shown that, the existence of a set of instrumental values of covariates, over which the stochastic unobservables exhibit local quantile invariance and over which a local order condition holds, defines a model which identifies certain partial differences of structural functions. This result is useful when covariates exhibit discrete variation. The paper also considers the identification of partial derivatives in smooth structures when covariates exhibit continuous variation.

Suggested Citation

  • Andrew Chesher, 2002. "Instrumental Values," CeMMAP working papers 17/02, Institute for Fiscal Studies.
  • Handle: RePEc:azt:cemmap:17/02
    DOI: 10.1920/wp.cem.2002.1702
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    References listed on IDEAS

    as
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    Cited by:

    1. Kasey S. Buckles & Daniel M. Hungerman, 2013. "Season of Birth and Later Outcomes: Old Questions, New Answers," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 711-724, July.
    2. David M. Kaplan & Matt Goldman, 2015. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1503, Department of Economics, University of Missouri.
    3. Andrew Chesher, 2004. "Identification of sensitivity to variation in endogenous variables," Econometric Society 2004 Australasian Meetings 353, Econometric Society.
    4. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    5. Horowitz, Joel L. & Lee, Sokbae, 2009. "Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative," Journal of Econometrics, Elsevier, vol. 152(2), pages 141-152, October.
    6. Andrew Chesher, 2005. "Nonparametric Identification under Discrete Variation," Econometrica, Econometric Society, vol. 73(5), pages 1525-1550, September.
    7. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
    8. Santos, Andres, 2011. "Instrumental variable methods for recovering continuous linear functionals," Journal of Econometrics, Elsevier, vol. 161(2), pages 129-146, April.
    9. Andrew Chesher, 2003. "Nonparametric identification with discrete endogenous variables," CeMMAP working papers 06/03, Institute for Fiscal Studies.
    10. Lee, Jinhyun, 2013. "Sharp Bounds on Heterogeneous Individual Treatment Responses," SIRE Discussion Papers 2013-89, Scottish Institute for Research in Economics (SIRE).
    11. Jia-Young Michael Fu & Joel L. Horowitz & Matthias Parey, 2015. "Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions," CeMMAP working papers 68/15, Institute for Fiscal Studies.
    12. Xavier d'Haultfoeuille & Philippe Février, 2011. "Identification of Nonseparable Modes with Endogeneity and Discrete Instruments," Working Papers 2011-28, Center for Research in Economics and Statistics.
    13. Chesher, Andrew, 2009. "Excess heterogeneity, endogeneity and index restrictions," Journal of Econometrics, Elsevier, vol. 152(1), pages 37-45, September.
    14. Brunello, Giorgio & Fort, Margherita & Weber, Guglielmo, 2007. "“For One More Year with You”: Changes in Compulsory Schooling, Education and the Distribution of Wages in Europe," IZA Discussion Papers 3102, Institute of Labor Economics (IZA).
    15. Jinhyun Lee, 2013. "Sharp Bounds on Heterogeneous Individual Treatment Responses," Discussion Paper Series, School of Economics and Finance 201310, School of Economics and Finance, University of St Andrews.

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