LASSO-TYPE GMM ESTIMATOR

By Mehmet Caner. Econometric Theory, 2009

146 citations recorded by the source corpus.

Subfields: Demography, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d27b2872950684f58394d06b8cfa44d9bc0fe133

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Citations in the corpus

Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects (2016, unknown): “For example, Caner (2009) and Fan and Liao (2014) consider covariate selection in GMM estimation.”
Two-Step Lasso Estimation of the Spatial Weights Matrix (2015, methodology): “The focused generalized methods of moments (FGMM) developed in Fan and Liao [40] extends shrinkage GMM estimators as in, e.g., [41] to high-dimensional settings.”
Instrumental variables estimation with many weak instruments using regularized JIVE (2014, background): “See also Gautier and Tsybakov (2011) for a different sparsity-based approach to IV estimation related to BCCH. Related ideas also appear in Bai and Ng (2010), Kapetanios and Marcellino (2010), Kapetanios, Khalaf, and Marcellino (2011), and Caner (2009).”
High-dimensional instrumental variables regression and confidence sets (2011, methodology): “ession and by Belloni, Chen, Chernozhukov et al. (2012) who use Lasso type methods to estimate the so-called optimal instruments and obtain optimal conﬁdence for low dimensional structural equations. Caner (2009) studies a Lasso-type GMM estimator. Rosenbaum and Tsybakov (2010) deal with the high-di”
Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain (2012, methodology): “The analysis of Caner (2009) assumes that the number of parameters p is fixed in relation to the sample size, and so it is complementary to our approach where we allow p → ∞ as n → ∞. Other uses of Lasso in econometrics include Bai and Ng (2008), Belloni, Chernozhukov, and Hansen (2011b), Brodie, Da”
On LASSO for predictive regression (2018, unknown): “In econometrics, Caner (2009) and Caner and Zhang (2014) employ the LASSO-type procedures in GMM contexts.”
Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso (2016, unknown): “For example, Caner (2009) and Fan and Liao (2014) consider covariate selection in GMM estimation; Belloni et al. (2012) and García (2011) consider selection of instruments in the GMM framework; Liao (2013) provides a shrinkage GMM method for moment selection and Cheng and Liao (2015) consider the…”
Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments (2013, background): “Caner and Zhang (2012) study adaptive elastic net GMM estimation with an increasing number of parameters.”