Nonparametric regression with nonparametrically generated covariates

Arbeitspapier

We analyze the properties of non- and semiparametric estimation procedures involving nonparametric regression with generated covariates. Such estimators appear in numerous econometric applications, including nonparametric estimation of simultaneous equation models, sample selection models, treatment effect models, and censored regression models, but so far there seems to be no unified theory to establish their statistical properties. Our paper provides such results, allowing to establish asymptotic properties like rates of consistency or asymptotic normality for a wide range of semi- and nonparametric estimators. We also show how to account for the presence of nonparametrically generated regressors when computing standard errors.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2010-059

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
• Subject: empirical process ; propensity score ; control variable methods ; semiparametric estimation ; Regression ; Nichtparametrisches Verfahren ; Varianzanalyse ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Mammen, Enno ; Rothe, Christoph ; Schienle, Melanie
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/56748
• Last update: 10.03.2025, 11:43 AM CET