This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates. The function delivers 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 in Angrist and Krueger's 1991 study of the returns to schooling.
Authors
Andrew Chesher
Research Fellow University College London
Andrew is the Director of the ESRC Centre for Microdata Methods and Practice (cemmap) and Professor of Economics and Economic Measurement at UCL.
Journal article details
- Publisher
- Econometric Society
- Issue
- September 2005
Suggested citation
Chesher, A. (2005). 'Nonparametric identification under discrete variation' (2005)
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