Robust nonnested hypothesis testing

Sunil Sapra ()

Applied Economics Letters, 2008, vol. 15, issue 1, pages 1-4

Abstract: This article presents robust J and encompassing tests for testing nonnested hypotheses in the presence of outliers in the data. The proposed tests are based on least absolute deviations (LAD) and M-estimators unlike the conventional J and encompassing tests, which are based on least squares or maximum likelihood estimators. These tests can lead to more reliable inference in the presence of outliers than tests based on nonrobust estimators. The tests are illustrated with applications to two economic data sets and an artificially generated data set and compared with their nonrobust counterparts.

Downloads: (external link)
http://www.informaworld.com/openurl?genre=article& ... 40C6AD35DC6213A474B5 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Ordering information: This journal article can be ordered from
http://www.tandf.co.uk/journals/subscription.html

Access Statistics for this article

Applied Economics Letters is edited by Mark Taylor

More articles in Applied Economics Letters from Taylor and Francis Journals
Series data maintained by Christopher F. Baum ().