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Record W2757434889 · doi:10.4478/87394

Why is the canadian banking system more resilient than the U.S. system? a lesson for european competition policy

2017· article· en· W2757434889 on OpenAlexaboutno aff
Oscar Borgogno

Bibliographic record

VenueInstitutional Research Information System University of Turin (University of Turin) · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsCompetition (biology)LuckFinancial regulationFinancial stabilityFinancial crisisFinancial systemWork (physics)Retail bankingBusinessEconomicsEngineeringMacroeconomics

Abstract

fetched live from OpenAlex

The work focuses on the United States and the Canadian banking systems regulatory evolutions and assesses the reasons why two so similar countries ended up with such different banking systems. The aim of the paper is to show that Canada has a greater level of stability compared to the United States because in Canada the relationship between competition policy and the financial system has always been more cautious and less procompetitive. Economic history of United States and Canada will be in part addressed to demonstrate that Canada dodging of the 2008 financial crisis was not just a one-time luck. The United States has experienced several financial crises since XIX century whereas the Canadian financial system has always remained sound and stable. Firstly, I suggest that the two major factors which explain this phenomenon are (i) the strong local lobbies which fought the implementation of a centralized banking system in the U.S. and (ii) the more cautious financial and antitrust policies implemented by Canada throughout its history. Secondly, I submit that a banking oligopoly tightly regulated can prove much more effective in maintaining financial stability than a fragmented system of small and fragile entities. The paper concludes showing that the Canadian system represents a positive model to which E.U. policy makers can look to better shape the regulatory framework of the European Banking 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.253
Teacher spread0.198 · 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 teacher head, not a consensus.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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