文章基本信息

标题：Ordered Response Models and Non-Random Personality Traits: Monte Carlo Simulations and a Practical Guide
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作者：Ingo Geishecker ; Maximilian Riedl
期刊名称：CeGE-Discussion Paper
印刷版ISSN：1439-2305
出版年度：2010
卷号：2010
出版社：Center for European, Governance and Economic Development
摘要：Ordered Response Models and Non-Random Personality Traits: Monte Carlo Simulations and a Practical Guide
The paper compares diﬀerent estimation strategies of ordered response models in the presence of non-random unobserved heterogeneity. By running Monte Carlo simulations with a range of randomly generated panel data of diﬀering cross¬sectional and longitudinal dimension sizes we assess the consistency and eﬃciency of standard models such as linear ﬁxed eﬀects, ordered and conditional logit and several diﬀerent binary recoding procedures. Among the analyzed binary recoding procedures is the conditional ordered logit estimator proposed by Ferrer-i-Carbonell and Frijters (2004) that recently has gained some popularity in the analysis of individual well-being. The Ferrer-i-Carbonell and Frijters estimator (FCF) performs best if the number of observations is large and the number of categories on the ordered scale is small. However, a much simpler individual mean based binary recoding scheme performs similarly well and even outperforms the FCF estimator if the number of categories on the ordered scale becomes large. If the researcher is, however, only interested in the relative size of coeﬃcients with respect to a baseline the easy to compute linear ﬁxed eﬀect model essentially delivers the same results as the more elaborate binary recoding schemes.
关键词：ﬁxed eﬀects ordered logit, ordered responses, happiness