An Ordinal Regression Model using Dealer Satisfaction Data

Alexander Staus ()

No 15, Hohenheimer Agrarökonomische Arbeitsberichte from University of Hohenheim, Institute for Agricultural Policy and Agricultural Markets

Abstract: This article analyses dealer satisfaction data in the agricultural technology market in Germany. The dealers could rate their suppliers in the 'overall satisfaction' and in 38 questions which can be summarized in 8 dimensions. An ordinal regression model which is also known as the proportional odds model is used to analyse the ordinal scaled rating of the dealers. The ordinal regression model is a well examined method in econometric theory, but many authors prefer using a linear regression model due to better interpretation, even the assumptions of a linear regression do not fit the data. Since the estimated coefficients of an ordinal regression model can not be properly interpreted we show other methods for a better insight of the relationship of the dealer satisfaction and the influencing variables. These methods are easy to use and it is recommended to list some of them in empirical papers.

Keywords: ordinal regression; dealer satisfaction; interpretation (search for similar items in EconPapers)
JEL-codes: C25 C51 Q13 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2007-05
New Economics Papers: this item is included in nep-agr
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Related works:
Working Paper: An Ordinal Regression Model using Dealer Satisfaction Data (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:hoh:hoh420:15

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