Instrumental variables estimation with many weak instruments using regularized JIVE

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Machine Learning: An Applied Econometric Approach (2017, background): “In particular, a set of papers has already introduced regularization into the first stage in a high-dimensional setting, including the LASSO (Belloni, Chen, Chernozhukov, and Hansen 2012) and ridge regression (Carrasco 2012; Hansen and Kozbur 2014).”
High-dimensional econometrics and regularized GMM (2018, unknown): “See, for example, [41], [100], [37], and [71] for approaches that explicitly use regularized first-stage estimation within a dense model framework.”
Targeted Undersmoothing. (2017, background): “7See for instance, [33], which allows more instruments than observations but does not impose sparsity in the first stage.”