Inference with Many Weak Instruments

• Tác giả: Anna Mikusheva, Liyang Sun
• Ngôn ngữ: eng
• Ký hiệu phân loại: 530.7 Instrumentation
• Thông tin xuất bản: 2020
• Bộ sưu tập: Metadata
• ID: 164306

Tóm tắt

Comment: 37 pages, 2 figure, 6 tablesWe develop a concept of weak identification in linear IV 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 (JIVE). This new pre-test is valid under heteroscedasticity and with many instruments.