Nonparametric Likelihood: Efficiency and Robustness

被引:0
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作者
Yuichi Kitamura
机构
[1] Yale University,
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C14;
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摘要
Nonparametric likelihood is a natural generalization of parametric likelihood and it offers effective methods for analysing economic models with nonparametric components. This is of great interest, since econometric theory rarely suggests a parametric form of the probability law of data. Being a nonparametric method, nonparametric likelihood is robust to misspecification. At the same time, it often achieves good properties that are analogous to those of parametric likelihood. This paper explores various applications of nonparametric likelihood, with some emphasis on the analysis of biased samples and data combination problems.
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页码:26 / 46
页数:20
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