Ridge regularization for Mean Squared Error Reduction in Regression with Weak Instruments

• Tác giả: Karthik Rajkumar
• Ngôn ngữ: eng
• Ký hiệu phân loại: 526.5 Mathematical geography
• Thông tin xuất bản: 2019
• Bộ sưu tập: Metadata
• ID: 162820

Tóm tắt

Comment: 20 pagesIn this paper, I show that classic two-stage least squares (2SLS) estimates are highly unstable with weak instruments. I propose a ridge estimator (ridge IV) and show that it is asymptotically normal even with weak instruments, whereas 2SLS is severely distorted and un-bounded. I motivate the ridge IV estimator as a convex optimization problem with a GMM objective function and an L2 penalty. I show that ridge IV leads to sizable mean squared error reductions theoretically and validate these results in a simulation study inspired by data designs of papers published in the American Economic Review.