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Nonparametric identification under discrete variation

Authors: Andrew Chesher
Date: 14 December 2003
Type: cemmap Working Paper, CWP19/03
DOI: 10.1920/wp.cem.2003.1903


This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function which depends on a discrete endogenous variable and is nonseparable in a latent variate. The function may deliver values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter of birth instruments used by Angrist and Krueger (1991) in their study of the returns to schooling. Download full version
Now published:
Andrew Chesher September 2005, Nonparametric identification under discrete variation, Journal article, Econometric Society
Previous version:
Andrew Chesher December 2003, Nonparametric identification with discrete endogenous variables, cemmap Working Paper, IFS

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