.png){kind=icon}
返回
Split-panel Jackknife Estimation of Fixed-effect Models
.png){kind=icon}
OA
AI
DOI：10.1093/restud/rdv007.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Maximum-likelihood estimation of nonlinear models with fixed effects is subject to the incidental-parameter problem. This typically implies that point estimates suffer from large bias and confidence intervals have poor coverage. This article presents a jackknife method to reduce this bias and to obtain confidence intervals that are correctly centred under rectangular-array asymptotics. The method is explicitly designed to handle dynamics in the data, and yields estimators that are straightforward to implement and can be readily applied to a range of models and estimands. We provide distribution theory for estimators of model parameters and average effects, present validity tests for the jackknife, and consider extensions to higher-order bias correction and to two-step estimation problems. An empirical illustration relating to female labour-force participation is also provided.
Keyword:
Bias reduction
Dependent data
Incidental-parameter problem
Jackknife
Nonlinear model
期刊
IF:
6.4
论文数:
2.5K
被引数:
2.1W
机构
引用论文
State dependence, serial correlation and heterogeneity in intertemporal labor force participation of married women.png)
ECONOMETRICA
ECONOMETRICAIF7.1
PREAI
分享收藏分享收藏THE SENSITIVITY OF CONSUMPTION TO TRANSITORY INCOME - ESTIMATES FROM PANEL DATA ON HOUSEHOLDSECONOMETRICA
OAAI
ECONOMETRICAIF7.1
OAAI分享收藏ARE THERE POSITIVE SPILLOVERS FROM DIRECT FOREIGN-INVESTMENT - EVIDENCE FROM PANEL-DATA FOR MOROCCO
PREAI
分享收藏
查看更多内容