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Exogenous impact and conditional quantile functions

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  • Andrew Chesher

    (University College London)

Abstract

An exogenous impact function is defined as the derivative of a structural function with respect to an endogenous variable, other variables, including unobservable variables held fixed. Unobservable variables are fixed at specific quantiles of their marginal distributions. Exogenous impact functions reveal the impact of an exogenous shift in a variable perhaps determined endogenously in the data generating process. They provide information about the variation in exogenous impacts across quantiles of the distributions of the unobservable variables that appear in the structural model. This paper considers nonparametric identification of exogenous impact functions under quantile independence conditions. It is shown that, when valid instrumental variables are present, exogenous impact functions can be identified as functionals of conditional quantile functions that involve only observable random variables. This suggests parametric, semiparametric and nonparametric strategies for estimating exogenous impact functions.

Suggested Citation

  • Andrew Chesher, 2001. "Exogenous impact and conditional quantile functions," Econometrics 0108001, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0108001
    Note: Type of Document - Acrobat PDF; prepared on Windows 2000 Professional PC; to print on A4 paper; pages: 13 ; figures: none
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    References listed on IDEAS

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    1. Amemiya, Takeshi, 1982. "Two Stage Least Absolute Deviations Estimators," Econometrica, Econometric Society, vol. 50(3), pages 689-711, May.
    2. Newey, Whitney K. & Powell, James L., 1990. "Efficient Estimation of Linear and Type I Censored Regression Models Under Conditional Quantile Restrictions," Econometric Theory, Cambridge University Press, vol. 6(3), pages 295-317, September.
    3. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
    4. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    5. Jesse Levin, 2001. "For whom the reductions count: A quantile regression analysis of class size and peer effects on scholastic achievement," Empirical Economics, Springer, vol. 26(1), pages 221-246.
    6. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    7. Khan, Shakeeb, 2001. "Two-stage rank estimation of quantile index models," Journal of Econometrics, Elsevier, vol. 100(2), pages 319-355, February.
    8. Powell, James L, 1983. "The Asymptotic Normality of Two-Stage Least Absolute Deviations Estimators," Econometrica, Econometric Society, vol. 51(5), pages 1569-1575, September.
    9. repec:cup:etheor:v:6:y:1990:i:3:p:295-317 is not listed on IDEAS
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    Cited by:

    1. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    2. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
    3. Brunello, Giorgio & Fabbri, Daniele & Fort, Margherita, 2009. "Years of Schooling, Human Capital and the Body Mass Index of European Females," IZA Discussion Papers 4667, Institute of Labor Economics (IZA).
    4. Giorgio Brunello & Margherita Fort & Guglielmo Weber, 2009. "Changes in Compulsory Schooling, Education and the Distribution of Wages in Europe," Economic Journal, Royal Economic Society, vol. 119(536), pages 516-539, March.
    5. 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).

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    More about this item

    Keywords

    endogeneity; quantile regression; identification; structural models; instrumental variables; quantile independence;
    All these keywords.

    JEL classification:

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

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