|This centre is a member of The LSE Research Laboratory [RLAB]: CASE | CVER | CEP | SERC | STICERD||Cookies?|
Paper No' EM600: | Full paper
Save Reference as: BibTeX File | EndNote Import File
Keywords: Additive model, Measurement error, Deconvolution
JEL Classification: C14; C13
Is hard copy/paper copy available? NO - Paper Copy Out Of Print.
This Paper is published under the following series: Econometrics
Share this page: Google Bookmarks | Facebook | Twitter
Abstract:In estimation of nonparametric additive models, conventional methods, such as backfitting and series approximation, cannot be applied when measurement errors are present in covariates. We propose an estimator for such models by extending Horowitz and Mammen’s (2004) two stage estimator for the errors-in-variables case. In the first stage, to adept to the additive structure, we use a series method together with a ridge approach to deal with ill-posedness brought by the mismeasurement. The uniform convergence rate for the first stage estimator is derived. To establish the limiting distribution, we consider the second stage estimator obtained by the one-step backfitting with a deconvolution kernel based on the first stage estimator.
Copyright © RLAB & LSE 2003 - 2019 | LSE, Houghton Street, London WC2A 2AE | Contact: RLAB | Site updated 16 February 2019