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Identifying Structural Effects in Nonseparable Systems Using Covariates

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  • Halbert White
  • Karim Chalak

    (Boston College)

Abstract

This paper demonstrates the extensive scope of an alternative to standard instrumental variables methods, namely covariate-based methods, for identifying and estimating effects of interest in general structural systems. As we show, commonly used econometric methods, specifically parametric, semi-parametric, and nonparametric extremum or moment-based methods, can all exploit covariates to estimate well-identified structural e§ects. The systems we consider are general, in that they need not impose linearity, separability, or monotonicity restrictions on the structural relations. We consider effects of multiple causes; these may be binary, categorical, or continuous. For continuous causes, we examine both marginal and non-marginal effects. We analyze effects on aspects of the response distribution generally, designed by explicit or implicit moments or as optimizers (e.g., quantiles). Key for identification is a specific conditional exogeneity relation. We examine what happens in its absence and find that identification generally fails. Nevertheless, local and near identification results hold in its absence, as we show.

Suggested Citation

  • Halbert White & Karim Chalak, 2008. "Identifying Structural Effects in Nonseparable Systems Using Covariates," Boston College Working Papers in Economics 734, Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:734
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    References listed on IDEAS

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    Cited by:

    1. Karim Chalak & Halbert White, 2011. "Viewpoint: An extended class of instrumental variables for the estimation of causal effects," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 44(1), pages 1-51, February.
    2. Schennach, Susanne & White, Halbert & Chalak, Karim, 2012. "Local indirect least squares and average marginal effects in nonseparable structural systems," Journal of Econometrics, Elsevier, vol. 166(2), pages 282-302.
    3. Lu, Xun & White, Habert, 2015. "Testing For Treatment Dependence Of Effects Of A Continuous Treatment," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1016-1053, October.
    4. Huang, Meng & Sun, Yixiao & White, Halbert, 2016. "A Flexible Nonparametric Test For Conditional Independence," Econometric Theory, Cambridge University Press, vol. 32(6), pages 1434-1482, December.
    5. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    6. White, Halbert & Chalak, Karim, 2010. "Testing a conditional form of exogeneity," Economics Letters, Elsevier, vol. 109(2), pages 88-90, November.

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    More about this item

    Keywords

    conditional exogeneity; extremum estimator; identification; method of moments; nonparametric estimation; structural equations.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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