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A restricted Liu estimator for binary regression models and its application to an applied demand system
Jönköping University.
Florida International University, USA.
Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för nationalekonomi och statistik (NS). Jönköping University. (Statistics)ORCID-id: 0000-0002-3416-5896
2016 (engelsk)Inngår i: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, nr 6, s. 1119-1127Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this article, we propose a restricted Liu regression estimator (RLRE) for estimating the parameter vector, β, in the presence of multicollinearity, when the dependent variable is binary and it is suspected that β may belong to a linear subspace defined by =r. First, we investigate the mean squared error (MSE) properties of the new estimator and compare them with those of the restricted maximum likelihood estimator (RMLE). Then we suggest some estimators of the shrinkage parameter, and a simulation study is conducted to compare the performance of the different estimators. Finally, we show the benefit of using RLRE instead of RMLE when estimating how changes in price affect consumer demand for a specific product.

sted, utgiver, år, opplag, sider
Taylor & Francis, 2016. Vol. 43, nr 6, s. 1119-1127
HSV kategori
Forskningsprogram
Statistik; Ekonomi
Identifikatorer
URN: urn:nbn:se:lnu:diva-46116DOI: 10.1080/02664763.2015.1092110ISI: 000371182400009Scopus ID: 2-s2.0-84958944234OAI: oai:DiVA.org:lnu-46116DiVA, id: diva2:851560
Tilgjengelig fra: 2015-09-06 Laget: 2015-09-06 Sist oppdatert: 2017-12-04bibliografisk kontrollert

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