Non-Commutative Rough Advanced Econometrics Dynamics (NC-RECON): Superseding Classical Empirical Processes via Banach-Valued Concentration, Neyman Orthogonal Moments, and High-Dimensional M-Estimation
Year: 2026
Type: preprint
Abstract: Classical advanced econometrics anchored by Donsker empirical processes, asymptotic normality, and separate identification assumptions fails in high-dimensional settings, weak identification regimes, and modern machine learning integrations. This paper establishes Non-Commutative Rough Advanced Econometrics Dynamics (NC-RECON)withinthe SMA-∞-Topos. Byintegrating Universal Rough Operator Algebra (UROA), Seonggil Theory of Complex Torsion (STCT), and Rough Quantum Information Geometry (RQIG), we prove that Banach-space valued empirical processes, Neyman orthogonal scores, and high-dimensional oracle inequalities systematically supersede classical asymptotic limitations.
Author: Lee, Seonggil
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7221667795
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