Proposed separability restriction tests using nonparametric regression methods
Applied Economics Letters, 2008, vol. 15, issue 12, 949-954
This article proposes some tests for separability restriction incorporating nonparametric regression methods, as well as offering their general statistic characteristics. An effective separability restriction test is essential for appropriate model specification or appropriate implementation of semi-parametric estimation. In this article, I describe two procedures to yield the estimated residuals, which is very sensitive to separability restriction, upon which one test statistics is proposed. In some benchmark models of sine/cosine functions, I simulate out the probability density function of test statistics in a small sample. These presented results and analysis show that the proposed estimator is robust and effective to variable functional form of regression curves and to variable scale factors, broader than the 'optimal' level, and can be put conveniently and widely into a practical use.
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://www.informaworld.com/openurl?genre=article& ... 40C6AD35DC6213A474B5 (text/html)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:15:y:2008:i:12:p:949-954
Ordering information: This journal article can be ordered from
Access Statistics for this article
Applied Economics Letters is currently edited by Anita Phillips
More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().