Large dimensional latent factor modeling with missing observations and applications to causal inference

DOI10.1016/j.jeconom.2022.04.005OpenAlexW2980628834MaRDI QIDQ2688665

Markus Pelger, Ruoxuan Xiong

Publication date: 3 March 2023

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.08273

zbMATH Keywords

matrix completionprincipal componentstreatment effectlarge \(N\) and \(T\)synthetic control

Mathematics Subject Classification ID

Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Related Items (4)

Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion ⋮ Factor-based imputation of missing values and covariances in panel data of large dimensions ⋮ Inference for low-rank completion without sample splitting with application to treatment effect estimation ⋮ Matrix Factor Analysis: From Least Squares to Iterative Projection

Uses Software

• softImpute

Cites Work

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