More efficient estimation of nonparametric panel data models with random effects
We propose a class of two-step estimators for nonparametric panel data models with random effects that are more efficient than the conventional least squares estimators. We establish asymptotic normality for the proposed estimators and derive the most efficient estimator in the class.
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2007
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/soe_research/2043 https://ink.library.smu.edu.sg/context/soe_research/article/3042/viewcontent/More_efficient_estimation_of_nonparametric_random_2007_afv.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | We propose a class of two-step estimators for nonparametric panel data models with random effects that are more efficient than the conventional least squares estimators. We establish asymptotic normality for the proposed estimators and derive the most efficient estimator in the class. |
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