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- W4288366564 abstract "In 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." @default.
- W4288366564 created "2022-07-29" @default.
- W4288366564 creator A5006065222 @default.
- W4288366564 date "2019-04-17" @default.
- W4288366564 modified "2023-09-28" @default.
- W4288366564 title "Ridge regularization for Mean Squared Error Reduction in Regression with Weak Instruments" @default.
- W4288366564 doi "https://doi.org/10.48550/arxiv.1904.08580" @default.
- W4288366564 hasPublicationYear "2019" @default.
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