---
title: Partisanship in Financial Regulators
url: https://www.ml-quant.com/papers/repec/oup-rfinst-v-36-y-2023-i-11-p-4373-4416/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:oup:rfinst:v:36:y:2023:i:11:p:4373-4416.
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Frfs%2Fhhad029%3Bh%3Drepec%3Aoup%3Arfinst%3Av%3A36%3Ay%3A2023%3Ai%3A11%3Ap%3A4373-4416.
featured: 2024-10-17
citations: unknown
topic: ML & AI Methods
---


# Partisanship in Financial Regulators

Machine learning analysis of language used in Congress and new SEC rules shows a significant increase in partisanship among SEC Commissioners from 2010-2019, while the Federal Reserve Board remains relatively nonpartisan.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1093%2Frfs%2Fhhad029%3Bh%3Drepec%3Aoup%3Arfinst%3Av%3A36%3Ay%3A2023%3Ai%3A11%3Ap%3A4373-4416.
- Identifier: RePEc:oup:rfinst:v:36:y:2023:i:11:p:4373-4416.
- Released: 2023-09-24
- First featured: Quant Letter No. 70 (2024-10-17): https://www.ml-quant.com/issues/2024-10-17/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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