.png){kind=icon}
返回
Nonparametric estimation and testing of fixed effects panel data models
.png){kind=icon}
OA
AI
DOI：10.1016/j.jeconom.2008.01.005.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test between the three alternatives in practice. We further propose a test statistic for testing the null hypothesis of random effects against fixed effects in a nonparametric panel data regression model. Simulations are used to examine the finite sample performance of the proposed estimators and the test statistics. Published by Elsevier B.V.
Keyword:
fixed effects models
model specification tests
nonparametric kernel method
panel data
partially linear model
profile method
random effects models
semiparametric efficiency bound
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
5.3K
被引数:
3.0W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏分享收藏
查看更多内容