An Ordinal Regression Model using Dealer Satisfaction Data
AbstractThis 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.
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Bibliographic InfoPaper provided by Universitaet Hohenheim, Institute of Agricultural Policy and Agricultural Markets in its series Working Papers with number 98632.
Date of creation: May 2007
Date of revision:
Keywords: ordinal regression; dealer satisfaction; interpretation; Agricultural and Food Policy; Marketing; C25; C51; Q13;
Find related papers by JEL classification:
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
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