Nonparametric identification with discrete endogenous variables
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.
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- Chesher, Andrew, 2007.
Journal of Econometrics,
Elsevier, vol. 139(1), pages 15-34, July.
- David Card, 2000.
"Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems,"
NBER Working Papers
7769, National Bureau of Economic Research, Inc.
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- Lee, Sokbae, 2003. "Efficient Semiparametric Estimation Of A Partially Linear Quantile Regression Model," Econometric Theory, Cambridge University Press, vol. 19(01), pages 1-31, February.
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- Barry R. Chiswick, 1974. "Income Inequality: Regional Analyses within a Human Capital Framework," NBER Books, National Bureau of Economic Research, Inc, number chis74-1, July.
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