 Using mixtures in econometric models: a brief review and some new resultsGiovanni Compiani and Yuichi Kitamura Econometrics Journal, 2016, vol. 19, issue 3, C95-C127 Abstract: This paper is concerned with applications of mixture models in econometrics. Focused attention is given to semiparametric and nonparametric models that incorporate mixture distributions, where important issues about model specifications arise. For example, there is a significant difference between a finite mixture and a continuous mixture in terms of model identifiability. Likewise, the dimension of the latent mixing variables is a critical issue, in particular when a continuous mixture is used. We present applications of mixture models to address various problems in econometrics, such as unobserved heterogeneity and multiple equilibria. New nonparametric identification results are developed for finite mixture models with testable exclusion restrictions without relying on an identification‐at‐infinity assumption on covariates. The results apply to mixtures with both continuous and discrete covariates, delivering point identification under weak conditions. Date: 2016 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:wly:emjrnl:v:19:y:2016:i:3:p:c95-c127 Ordering information: This journal article can be ordered from Access Statistics for this article Econometrics Journal is currently edited by Jaap Abbring, Victor Chernozhukov, Michael Jansson and Dennis Kristensen More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC. |
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