Testing competing models for non-negative data with many zeros
João Santos Silva (),
Silvana Tenreyro () and
Frank Windmeijer ()
LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library
In economic applications it is often the case that the variate of interest is non-negative and its distribution has a mass-point at zero. Many regression strategies have been proposed to deal with data of this type but, although there has been a long debate in the literature on the appropriateness of different models, formal statistical tests to choose between the competing specifications are not often used in practice. We use the non-nested hypothesis testing framework of Davidson and MacKinnon (Davidson and MacKinnon 1981. “Several Tests for Model Specification in the Presence of Alternative Hypotheses.” Econometrica 49: 781–793.) to develop a novel and simple regression-based specification test that can be used to discriminate between these models.
Keywords: health economics; international trade; non-nested hypotheses; C test; P test (search for similar items in EconPapers)
JEL-codes: C12 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12) Track citations by RSS feed
Published in Journal of Econometric Methods, January, 2015, 4(1), pp. 29-46. ISSN: 2156-6674
Downloads: (external link)
http://eprints.lse.ac.uk/63663/ Open access version. (application/pdf)
Journal Article: Testing Competing Models for Non-negative Data with Many Zeros (2015)
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:ehl:lserod:63663
Access Statistics for this paper
More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().