.png){kind=icon}
返回
Inference with Many Weak Instruments
.png){kind=icon}
OA
AI
DOI：10.1093/restud/rdab097.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We develop a concept of weak identification in linear instrumental variable models in which the number of instruments can grow at the same rate or slower than the sample size. We propose a jackknifed version of the classical weak identification-robust Anderson-Rubin (AR) test statistic. Large-sample inference based on the jackknifed AR is valid under heteroscedasticity and weak identification. The feasible version of this statistic uses a novel variance estimator. The test has uniformly correct size and good power properties. We also develop a pre-test for weak identification that is related to the size property of a Wald test based on the Jackknife Instrumental Variable Estimator. This new pre-test is valid under heteroscedasticity and with many instruments.
Keyword:
Instrumental variables
Weak identification
Dimensionality asymptotics
C12
C36
C55
期刊
IF:
6.4
论文数:
2.5K
被引数:
2.1W
机构
引用论文
Optimal two-sided invariant similar tests for instrumental variables regression工具变量回归的最优双侧不变相似检验.png)
ECONOMETRICA
OAAI
ECONOMETRICAIF7.1
OAAI分享收藏
查看更多内容