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Ordered logit analysis for selectively sampled data

Author

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  • Fok, D.
  • Franses, Ph.H.B.F.
  • Cramer, J.S.

Abstract

When 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.

Suggested Citation

  • Fok, D. & Franses, Ph.H.B.F. & Cramer, J.S., 1999. "Ordered logit analysis for selectively sampled data," Econometric Institute Research Papers EI 9933/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1602
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    References listed on IDEAS

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    1. Franses, Ph.H.B.F. & Slagter, E. & Cramer, J.S., 1999. "Censored regression analysis in large samples with many zero observations," Econometric Institute Research Papers EI 9939-A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    Cited by:

    1. Jana P. Fidrmuc & Alessandro Palandri & Peter Roosenboom & Dick van Dijk, 2013. "When Do Managers Seek Private Equity Backing in Public-to-Private Transactions?," Review of Finance, European Finance Association, vol. 17(3), pages 1099-1139.
    2. 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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