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Nonparametric identification under discrete variation

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  • Andrew Chesher

Abstract

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.

Suggested Citation

  • Andrew Chesher, 2003. "Nonparametric identification under discrete variation," CeMMAP working papers 19/03, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:19/03
    DOI: 10.1920/wp.cem.2003.1903
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    1. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    2. Machado, Jose A.F. & Silva, J. M. C. Santos, 2005. "Quantiles for Counts," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1226-1237, December.
    3. Lee, Sokbae, 2003. "Efficient Semiparametric Estimation Of A Partially Linear Quantile Regression Model," Econometric Theory, Cambridge University Press, vol. 19(1), pages 1-31, February.
    4. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, September.
    5. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    6. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    7. Guido W. Imbens & Charles F. Manski, 2004. "Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 72(6), pages 1845-1857, November.
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
    10. S. Darolles & Y. Fan & J. P. Florens & E. Renault, 2011. "Nonparametric Instrumental Regression," Econometrica, Econometric Society, vol. 79(5), pages 1541-1565, September.
    11. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    12. 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 34-66, Part II, .
    13. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, September.
    14. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    15. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    16. Whitney K. Newey & James L. Powell & Francis Vella, 1999. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Econometrica, Econometric Society, vol. 67(3), pages 565-604, May.
    17. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, March.
    18. Mitali Das, 2000. "Instrumental Variables Estimation of Nonparametric Models with Discrete Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1008, Econometric Society.
    19. Roehrig, Charles S, 1988. "Conditions for Identification in Nonparametric and Parametic Models," Econometrica, Econometric Society, vol. 56(2), pages 433-447, March.
    20. Roger W. Koenker & Vasco D'Orey, 1987. "Computing Regression Quantiles," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 383-393, November.
    21. Barry R. Chiswick, 1974. "Income Inequality: Regional Analyses within a Human Capital Framework," NBER Books, National Bureau of Economic Research, Inc, number chis74-1, March.
    22. Whitney K. Newey & James L. Powell, 2003. "Instrumental Variable Estimation of Nonparametric Models," Econometrica, Econometric Society, vol. 71(5), pages 1565-1578, September.
    23. E. Tamer & V. Chernozhukov & H. Hong, 2004. "Parameter Set Inference in a Class of Econometric Models," Econometric Society 2004 North American Winter Meetings 382, Econometric Society.
    24. Khan, Shakeeb, 2001. "Two-stage rank estimation of quantile index models," Journal of Econometrics, Elsevier, vol. 100(2), pages 319-355, February.
    25. repec:fth:harver:1473 is not listed on IDEAS
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