Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses
Quang H Vuong
Econometrica, 1989, vol. 57, issue 2, 307-33
Using the Kullback-Leibler information criterion to measure the closeness of a model to the truth, the author proposes new likelihood-ratio-based statistics for testing the null hypothesis that the competing models are as close to the true data generating process against the alternative hypothesis that one model is closer. The tests are directional and are derived for the cases where the competing models are non-nested, overlapping, or nested and whether both, one, or neither is misspecified. As a prerequisite, the author fully characterizes the asymptotic distribution of the likelihood ratio statistic under the most general conditions. Copyright 1989 by The Econometric Society.
References: Add references at CitEc
Citations: View citations in EconPapers (1177) Track citations by RSS feed
Downloads: (external link)
http://links.jstor.org/sici?sici=0012-9682%2819890 ... O%3B2-J&origin=repec full text (application/pdf)
Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
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:ecm:emetrp:v:57:y:1989:i:2:p:307-33
Ordering information: This journal article can be ordered from
https://www.economet ... ordering-back-issues
Access Statistics for this article
Econometrica is currently edited by Daron Acemoglu
More articles in Econometrica from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().