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Ordered response models

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  • Stefan Boes
  • Rainer Winkelmann

Abstract

We discuss regression models for ordered responses, such as ratings of bonds, schooling attainment, or measures of subjective well-being. Commonly used models in this context are the ordered logit and ordered probit regression models. They are based on an underlying latent model with single index function and constant thresholds. We argue that these approaches are overly restrictive and preclude a flexible estimation of the effect of regressors on the discrete outcome probabilities. For example, the signs of the marginal probability effects can only change once when moving from the smallest category to the largest one. We then discuss several alternative models that overcome these limitations. An application illustrates the benefit of these alternatives.
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Suggested Citation

  • Stefan Boes & Rainer Winkelmann, 2006. "Ordered response models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 167-181, March.
    • Handle: RePEc:spr:alstar:v:90:y:2006:i:1:p:167-181
    DOI: 10.1007/s10182-006-0228-y
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    More about this item

    Keywords

    Marginal effects; generalized threshold; sequential model; random coefficients; latent class analysis; happiness. JEL C25; 125;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I29 - Health, Education, and Welfare - - Education - - - Other

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