12 citations · 46 across the 19 of their papers we have counts for
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math.ST2017
Bias Reduction in Instrumental Variable Estimation through First-Stage Shrinkage
Jann Spiess
The two-stage least-squares (2SLS) estimator is known to be biased when its first-stage fit is poor. I show that better first-stage prediction can alleviate this bias. In a two-sta…
math.ST2017
Unbiased Shrinkage Estimation
Jann Spiess
Shrinkage estimation usually reduces variance at the cost of bias. But when we care only about some parameters of a model, I show that we can reduce variance without incurring bias…
stat.ML2017★ 7 cited
Machine-Learning Tests for Effects on Multiple Outcomes
Jens Ludwig, Sendhil Mullainathan, Jann Spiess
In this paper we present tools for applied researchers that re-purpose off-the-shelf methods from the computer-science field of machine learning to create a "discovery engine" for…