Ordered logit analysis for selectively sampled data
AbstractWhen customers are classified into ordered categories, which are defined from the outset, it may happen that the majority belongs to a single category. If a market researcher is interested in the correlation between the classification and individual characteristics, the natural question is whether one needs to collect data for all customers in that particular category. We address this question for the ordered logit model. We show that there is no need to consider all those customers. All that is required is a simple modification of the log-likelihood, which is based on Bayes' rule. We illustrate our proposed method on simulated data and on data concerning risk profiles of customers of an investment bank.
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Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 9933/A.
Date of creation: 10 Aug 1999
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ordered logit model; selective sampling; Bayes' rule;
Other versions of this item:
- Fok, Dennis & Franses, Philip Hans, 2002. "Ordered logit analysis for selectively sampled data," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 477-497, September.
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- Jain, Dipak C & Vilcassim, Naufel J & Chintagunta, Pradeep K, 1994. "A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 317-28, July.
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- Fidrmuc, J.P. & Roosenboom, P.G.J. & Dijk, D.J.C. van, 2007. "When Do Managers Seek Private Equity Backing in Public-to-Private Transactions?," Research Paper ERS-2007-028-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
- Jacek Kotlowski, 2005. "Reaction functions of the Polish central bankers. A logit approach," Working Papers 18, Department of Applied Econometrics, Warsaw School of Economics.
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