Kernel Estimation of Partial Means and a General Variance Estimator
Econometric applications of kernel estimators are proliferating, suggesting the need for convenient variance estimates and conditions for asymptotic normality. This paper develops a general “delta-method” variance estimator for functionals of kernel estimators. Also, regularity conditions for asymptotic normality are given, along with a guide to verify them for particular estimators. The general results are applied to partial means, which are averages of kernel estimators over some of their arguments with other arguments held fixed. Partial means have econometric applications, such as consumer surplus estimation, and are useful for estimation of additive nonparametric models.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||1992|
|Contact details of provider:|| Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), DEPARTMENT OF ECONOMICS, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA|
Phone: (617) 253-3361
Fax: (617) 253-1330
Web page: http://econ-www.mit.edu/
More information through EDIRC
|Order Information:|| Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), DEPARTMENT OF ECONOMICS, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA|
When requesting a correction, please mention this item's handle: RePEc:mit:worpap:93-3. 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: (Linda Woodbury)
If references are entirely missing, you can add them using this form.