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econ.EM2026
Partial Identification under Imperfect Measurement: A Distributionally Robust Approach
Isaac Meza
Imperfect measurements allow different underlying distributions to generate the same observations. Restrictions linking unobserved components can make it difficult to characterize…
econ.EM2025
Canonical correlation regression with noisy data
Isaac Meza, Rahul Singh
We study instrumental variable regression in data rich environments. The goal is to estimate a linear model from many noisy covariates and many noisy instruments. Our key assumptio…
econ.EM2025
Residual Balancing for Non-Linear Outcome Models in High Dimensions
Isaac Meza
We extend the approximate residual balancing (ARB) framework to nonlinear models, answering an open problem posed by Athey et al. (2018). Our approach addresses the challenge of es…