A concentrated, nonlinear information-theoretic estimator for the sample selection model (Q657475)
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scientific article; zbMATH DE number 5995884
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A concentrated, nonlinear information-theoretic estimator for the sample selection model |
scientific article; zbMATH DE number 5995884 |
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A concentrated, nonlinear information-theoretic estimator for the sample selection model (English)
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9 January 2012
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Summary: This paper develops a semi-parametric, information-theoretic method for estimating parameters for nonlinear data generated under a sample selection process. Considering the sample selection as a set of inequalities makes this model inherently nonlinear. This estimator (i) allows for a whole class of different priors, and (ii) is constructed as an unconstrained, concentrated model. This estimator is easy to apply and works well with small or complex data. We provide a number of explicit analytical examples for different priors' structures and an empirical example.
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concentrated model
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inequalities
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information
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maximum entropy
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priors
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sample selection
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