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Nonparametric Censored and Truncated Regression

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Author Info

  • Arthur Lewbel

    ()
    (Dept. of Economics, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, U.S.A.)

  • Oliver Linton

    ()
    (Dept. of Economics, London School of Economics, Houghton Street, London WC2A 2AE, United Kingdom)

Abstract

The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x)+e], where both the regression function m(x) and the distribution of the error e are unknown. This paper provides consistent estimators of m(x) and its derivatives. The convergence rate is the same as for an uncensored nonparametric regression and its derivatives. We also provide root n estimates of weighted average derivatives of m(x), which equal the coefficients in linear or partly linear specifications for m(x). An extension permits estimation in the presence of a general form of heteroskedasticity. We also extend the estimator to the nonparametric truncated regression model, in which only uncensored data points are observed.

(This abstract was borrowed from another version of this item.)

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Bibliographic Info

Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 70 (2002)
Issue (Month): 2 (March)
Pages: 765-779

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Handle: RePEc:ecm:emetrp:v:70:y:2002:i:2:p:765-779

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  7. Arthur Lewbel, 1999. "Semiparametric Qualitative Response Model Estimation with Unknown Heteroskedasticity or Instrumental Variables," Boston College Working Papers in Economics 454, Boston College Department of Economics.
  8. Lewbel, Arthur, 1995. "Consistent nonparametric hypothesis tests with an application to Slutsky symmetry," Journal of Econometrics, Elsevier, vol. 67(2), pages 379-401, June.
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