Beyond Greenwashing: Algorithmic Resilience and the Non-Linear Governance Premium in Sovereign Capital Flows
Abstract
Despite the proliferation of sovereign Environmental, Social, and Governance (ESG) metrics, traditional linear macro-financial models systematically misprice Foreign Direct Investment (FDI) tail risks during systemic shocks. This paper demonstrates that sovereign risk transmission is fundamentally non-linear. Using a forward-chained global panel of 147 sovereign entities (2010-2024), we deploy a gradient boosting architecture that compresses forecast errors by over 39% against L1-regularized baselines precisely during extreme macroeconomic tail events. Moving beyond opaque predictive accuracy, we apply dual interpretability frameworks to mathematically map the discrete threshold effects of institutional quality. We identify a strict, non-linear "Governance Premium": incremental environmental and social improvements yield zero capital advantage until a foundational regulatory threshold is breached. Finally, we establish regime-conditional 95% uncertainty bounds that maintain valid marginal coverage even under severe ESG reporting failures. This framework equips policymakers with a distribution-free tool to quantify sovereign tail-risk, proving that global capital markets price institutional resilience as a discrete boundary rather than a continuous premium.
Related
- Cognitive Warfare, Hybrid Pressure, and Sovereign Resilience: An Operations Research Framework Applied to the Iranian Case (2017--2026)
- Assessing the Role of Green Premium and Localized Price Spillovers in Budget Hotels : Evidence from Delhi National Capital Region (NCR)
- Statistical-Algorithmic Phase Transitions in Stochastic L2-Boosting
- Algorithmic List Decoding of Reed-Solomon Codes up to Capacity
- Reed-Solomon Codes at Capacity: Algorithmic List-Decoding and Proximity Gaps
BibTeX
@misc{bose2026beyond,
title = {{Beyond Greenwashing: Algorithmic Resilience and the Non-Linear Governance Premium in Sovereign Capital Flows}},
author = {Sourav Bose and Taoufik Bouraoui},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.35895},
eprint = {2610.35895},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.35895},
}
RIS
TY - UNPB
TI - Beyond Greenwashing: Algorithmic Resilience and the Non-Linear Governance Premium in Sovereign Capital Flows
AU - Sourav Bose
AU - Taoufik Bouraoui
PY - 2026
DA - 2026/10/01
PB - arXiv
DO - 10.48550/arxiv.2610.35895
UR - https://arxiv.org/abs/2610.35895
AB - Despite the proliferation of sovereign Environmental, Social, and Governance (ESG) metrics, traditional linear macro-financial models systematically misprice Foreign Direct Investment (FDI) tail risks during systemic shocks. This paper demonstrates that sovereign risk transmission is fundamentally non-linear. Using a forward-chained global panel of 147 sovereign entities (2010-2024), we deploy a gradient boosting architecture that compresses forecast errors by over 39% against L1-regularized baselines precisely during extreme macroeconomic tail events. Moving beyond opaque predictive accuracy, we apply dual interpretability frameworks to mathematically map the discrete threshold effects of institutional quality. We identify a strict, non-linear "Governance Premium": incremental environmental and social improvements yield zero capital advantage until a foundational regulatory threshold is breached. Finally, we establish regime-conditional 95% uncertainty bounds that maintain valid marginal coverage even under severe ESG reporting failures. This framework equips policymakers with a distribution-free tool to quantify sovereign tail-risk, proving that global capital markets price institutional resilience as a discrete boundary rather than a continuous premium.
ER -