Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments

91 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Minimizing Sensitivity to Model Misspecification (2018, background): “Although asymptotic linearity is satisfied by many econometric estimators, it can fail in certain semiparametric problems (e.g., Cattaneo et al., 2014) and in problems involving model selection or shrinkage (e.g., Liao, 2013, Cheng and Liao, 2015), for example.”
Sensitivity analysis using approximate moment condition models (2018, background): “This contrasts sharply with point estimation, for which significant improvements in the mean squared error are possible when ‖c̃‖ is small (Liao, 2013; Cheng and Liao, 2015; DiTraglia, 2016).”
Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects (2016, unknown): “Liao (2013) provides a shrinkage GMM method for moment selection and Cheng and Liao (2015) consider the selection of valid and relevant moments via penalized GMM. Liao and Phillips (2015) apply adaptive shrinkage techniques to cointegrated systems.”