Nonparametric Censored and Truncated Regression

Arthur Lewbel and Oliver Linton

No 439, Boston College Working Papers in Economics from Boston College Department of Economics

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.

JEL-codes: C13 C14 C24 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2000-01-05
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Nonparametric Censored and Truncated Regression (2002)
Working Paper: Nonparametric Censored and Truncated Regression (2000)
Working Paper: Nonparametric Censored and Truncated Regression (2000)
Working Paper: Nonparametric censored and truncated regression (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:boc:bocoec:439

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