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Dummy variables vs. category-wise models
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
2014 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 41, no 2, 233-241 p.Article in journal (Refereed) Published
Abstract [en]

Empirical research frequently involves regression analysis with binary categorical variables, which are traditionally handled through dummy explanatory variables. This paper argues that separate category-wise models may provide a more logical and comprehensive tool for analysing data with binary categories. Exploring different aspects of both methods, we contrast the two with a Monte Carlo simulation and an empirical example to provide a practical insight.

Place, publisher, year, edition, pages
2014. Vol. 41, no 2, 233-241 p.
Keyword [en]
regression analysis, dummy variables, group heterogeneity, parameter restrictions
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hj:diva-21802DOI: 10.1080/02664763.2013.838665ISI: 000327237200001Scopus ID: 2-s2.0-84889096817OAI: oai:DiVA.org:hj-21802DiVA: diva2:643077
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2016-02-05Bibliographically approved

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Holgersson, ThomasNordström, LouiseÖner, Özge
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