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Identifying the Average Treatment Effect in a Two Threshold Model

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  • Arthur Lewbel

    ()
    (Boston College)

  • Thomas Tao Yang

    (Boston College)

Abstract

Assume individuals are treated if a latent variable, containing a continuous instrument, lies between two thresholds. We place no functional form restrictions on the latent errors. Here unconfoundedness does not hold and identification at infinity is not possible. Yet we still show nonparametric point identification of the average treatment effect. We provide an associated root-n consistent estimator. We apply our model to reinvestigate the inverted-U relationship between competition and innovation, estimating the impact of moderate competitiveness on innovation without the distributional assumptions required by previous analyses. We find no evidence of an inverted-U in US data.

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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 825.

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Date of creation: 01 Jul 2013
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Handle: RePEc:boc:bocoec:825

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Related research

Keywords: Average treatment effect; Ordered choice model; Special regressor; Semiparametric; Competition and innovation; Identification.;

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  1. Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
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  13. Marianne Bertrand, 2004. "From the Invisible Handshake to the Invisible Hand? How Import Competition Changes the Employment Relationship," Journal of Labor Economics, University of Chicago Press, vol. 22(4), pages 723-766, October.
  14. Aamir Rafique Hashmi, 2013. "Competition and Innovation: The Inverted-U Relationship Revisited," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1653-1668, December.
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