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.
|Date of creation:||Dec 2003|
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- Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, 09.
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Elsevier, vol. 139(1), pages 15-34, July.
- 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.
- Card, David, 2001.
"Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems,"
Econometric Society, vol. 69(5), pages 1127-60, September.
- David Card, 2000. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," NBER Working Papers 7769, National Bureau of Economic Research, Inc.
- Chiswick, Barry R & Mincer, Jacob, 1972. "Time-Series Changes in Personal Income Inequality in the United States from 1939, with Projections to 1985," Journal of Political Economy, University of Chicago Press, vol. 80(3), pages S34-S66, Part II, .
- Barry R. Chiswick, 1974. "Income Inequality: Regional Analyses within a Human Capital Framework," NBER Books, National Bureau of Economic Research, Inc, number chis74-1, December.
- Khan, Shakeeb, 2001. "Two-stage rank estimation of quantile index models," Journal of Econometrics, Elsevier, vol. 100(2), pages 319-355, February.
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