More efficient estimation of nonparametric panel data models with random effects

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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Bibliographic Details
Main Authors: SU, Liangjun, ULLAH, Aman
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
Subjects:
Nonparametrics
Panel data models
Random effects
Efficiency
Econometrics
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

Internet

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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