Advanced Search
MyIDEAS: Login to save this paper or follow this series

On Deconvolution as a First Stage Nonparametric Estimator

Contents:

Author Info

  • Yingyao Hu
  • Geert Ridder

Abstract

We reconsider Taupin’s (2001) Integrated Nonlinear Regression (INLR) estimator for a nonlinear regression with a mismeasured covariate. We find that if we restrict the distribution of the measurement error to the class of range-restricted distributions, then weak smoothness assumptions suffice to ensure sqrt(n) consistency of the estimator. The restriction to such distributions is innocuous, because it does not affect the fit to the data. Our results show that deconvolution can be used in a nonparametric first step without imposing restrictive smoothness assumptions on the parametric model.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.usc.edu/dept/LAS/economics/IEPR/Working%20Papers/IEPR_05.29_%5BHu,Ridder%5D.pdf
File Function: First version, 2005
Download Restriction: no

Bibliographic Info

Paper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 05.29.

as in new window
Length: 30 pages
Date of creation: Aug 2005
Date of revision:
Handle: RePEc:scp:wpaper:05-29

Contact details of provider:
Phone: (213) 740-3521
Fax: (213) 740-3522
Web page: http://www.usc.edu/dept/LAS/economics/IEPR/
More information through EDIRC

Related research

Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Li, Tong, 2002. "Robust and consistent estimation of nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 110(1), pages 1-26, September.
  2. Horowitz, Joel L & Markatou, Marianthi, 1996. "Semiparametric Estimation of Regression Models for Panel Data," Review of Economic Studies, Wiley Blackwell, vol. 63(1), pages 145-68, January.
  3. Newey, W.K., 1989. "The Asymptotic Variance Of Semiparametric Estimotors," Papers 346, Princeton, Department of Economics - Econometric Research Program.
  4. Xiaohong Chen & Han Hong & Elie Tamer, 2005. "Measurement Error Models with Auxiliary Data," Review of Economic Studies, Oxford University Press, vol. 72(2), pages 343-366.
  5. Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
  6. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, 01.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. An, Yonghong & Hu, Yingyao, 2012. "Well-posedness of measurement error models for self-reported data," Journal of Econometrics, Elsevier, vol. 168(2), pages 259-269.
  2. Susanne Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:scp:wpaper:05-29. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Farideh Motamedi).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.