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Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions
Feb. 19, 2024, 5:43 a.m. | Heiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Sch\"olkopf
cs.LG updates on arXiv.org arxiv.org
Abstract: Important problems in causal inference, economics, and, more generally, robust machine learning can be expressed as conditional moment restrictions, but estimation becomes challenging as it requires solving a continuum of unconditional moment restrictions. Previous works addressed this problem by extending the generalized method of moments (GMM) to continuum moment restrictions. In contrast, generalized empirical likelihood (GEL) provides a more general framework and has been shown to enjoy favorable small-sample properties compared to GMM-based estimators. To …
abstract arxiv causal inference cs.lg economics functional generalized inference likelihood machine machine learning math.st moments restrictions robust stat.ml stat.th type
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