Regression Analysis of Multivariate Fractional Data

Joaquim Ramalho ()

CEFAGE-UE Working Papers from University of Evora, CEFAGE-UE (Portugal)

Abstract: The present article discusses alternative regression models and estimation methods for dealing with multivariate fractional response variables. Both conditional mean models, estimable by quasi-maximum likelihood, and fully parametric models (Dirichlet and Dirichletmultinomial), estimable by maximum likelihood, are considered. A new parameterization is proposed for the parametric models, which accommodates the most common specifications for the conditional mean (e.g., multinomial logit, nested logit, random parameters logit, dogit). The text also discusses at some length the specification analysis of fractional regression models, proposing several tests that can be performed through artificial regressions. Finally, an extensive Monte Carlo study evaluates the finite sample properties of most of the estimators and tests considered.

JEL-codes: C35 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2013
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
https://api.cefage.uevora.pt/assets/2b120f6a-bcd8-42ad-8c40-ba7089b15ef5 (application/pdf)

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

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cfe:wpcefa:2013_05

Access Statistics for this paper

More papers in CEFAGE-UE Working Papers from University of Evora, CEFAGE-UE (Portugal) Contact information at EDIRC.
Bibliographic data for series maintained by Angela Pacheco ().