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Record W3124875129

From Independence to Politics in Financial Regulation

2012· preprint· en· W3124875129 on OpenAlexaboutno aff
Stavros Gadinis

Bibliographic record

VenueCalifornia Law Review · 2012
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Regulation and Crises
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsIndependence (probability theory)Financial regulationFinancial independenceEconomicsPolitical scienceFinancial systemBusinessFinanceLaw
DOInot available

Abstract

fetched live from OpenAlex

Independent agencies have long dominated the institutional structure of financial regulation. But after the 2007-08 crisis, this Article argues, the independent agency paradigm is under attack. To monitor financial institutions more thoroughly and address future failures more effectively, the U.S. and other industrialized nations redesigned the framework of financial regulation. Post-2008 laws allocate new powers not to independent bureaucrats, but to elected politicians and their direct appointees\n.\nTo document this global paradigm shift, the Article examines the laws of fifteen key jurisdictions for international banking: the U.S., the U.K., France, Germany, Japan, Spain, Switzerland, Belgium, Ireland, Italy, Denmark, Canada, Australia, Mexico, and South Korea. This analysis points to a marked increase in the influence of elected politicians over banking. Politicians' new powers extend not only over emergencies, but also over financial institutions' regular operations. Politicians are now at the helm of innovative institutional arrangements, typically in the form of regulatory councils that encompass pre-existing independent agencies. In these councils, supermajority requirements and veto rights designate politicians as the ultimate decision-makers.\nThe Article shows how this paradigm shift resulted from the interplay of factors unique to the 2008 crisis and long run trends. The collapse of institutions in diverse areas of financial activity, including investment banks, insurance companies, and thrifts, created a sense that independent regulators as a class had failed. Concerns about regulatory capture, combined with disillusionment with the markets' potential to self-correct, further undermined confidence in past paradigms. Developments in financial markets attracted great interest from ordinary Americans, who over the last two decades have increasingly relied on the financial system for their pension savings, housing credit, and other investments. Politicians could not remain as distant from financial regulation as in the past.\nFrom a normative standpoint, politicians' greater involvement in financial regulation is in line with calls for enhanced presidential control over independent agencies. Scholars have argued that the President's stamp of approval will increase accountability and boost the legitimacy of hard choices, such as bank bailouts. However, greater political involvement might endanger financial stability, this Article argues. Electoral strategizing can influence politicians' bailout choices, as incumbents might be particularly sensitive to upheavals as elections approach. Politicians are also under pressure from groups at ideological extremes, which often express a deep distrust to the financial system. In this climate, financial institutions are likely to lobby politicians more intensely. Thus, the risk of a financial catastrophe may now hinge upon considerations that have little to do with the health of the financial system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.073
Scholarly communication0.0150.011
Open science0.0010.011
Research integrity0.0080.016
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.272
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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