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Local Indirect Least Squares and Average Marginal Effects in Nonseparable Structural Systems

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  • Susanne Schennach

    (University of Chicago)

  • Halbert White

    (University of California-San Diego)

  • Karim Chalak

    () (Boston College)

Abstract

We study the scope of local indirect least squares (LILS) methods for nonparametrically estimating average marginal effects of an endogenous cause X on a response Y in triangular structural systems that need not exhibit linearity, separability, or monotonicity in scalar unobservables. One main finding is negative: in the fully nonseparable case, LILS methods cannot recover the average marginal effect. LILS methods can nevertheless test the hypothesis of no effect in the general nonseparable case. We provide new nonparametric asymptotic theory, treating both the traditional case of observed exogenous instruments Z and the case where one observes only error-laden proxies for Z.

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Bibliographic Info

Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 680.

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Date of creation: 03 Dec 2007
Date of revision: 26 Dec 2009
Handle: RePEc:boc:bocoec:680

Note: Previously circulated as "Estimating average marginal effects in nonseparable structural systems"
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Keywords: indirect least squares; instrumental variables; measurement error; nonparametric estimator; nonseparable structural equations;

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References

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Cited by:
  1. Susanne Schennach, 2012. "Measurement error in nonlinear models- a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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