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DOI：10.1111/j.1468-0297.2012.02545.x.png)
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摘要
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We consider a revealed preference-based method that will bound the minimal partition of consumer microdata into a set of preference types such that the data are perfectly rationalisable by standard utility theory. This provides a simple, non-parametric and theory-driven way of investigating unobserved preference heterogeneity in empirical data, and easily extends to any choice model which has a revealed preference characterisation. We illustrate the approach using survey data and find that the number of types is remarkably few relative to the sample size only four or five types are necessary to fully rationalise all observed choices in a data set with 500 observations of choice vectors.
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NONPARAMETRIC-ESTIMATION
DEMAND SYSTEMS
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NUMBER
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分享收藏A METHOD FOR MINIMIZING THE IMPACT OF DISTRIBUTIONAL ASSUMPTIONS IN ECONOMETRIC-MODELS FOR DURATION DATA.png)
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