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Record W3122871180

Theory and Test on the Corporate Governance of Financial Cooperative Systems: Merger vs. Networks

2003· article· en· W3122871180 on OpenAlexaboutno aff
Martin Desrochers, Klaus Fischer

Bibliographic record

VenueCahiers de recherche · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceTransaction costHierarchyPropositionIndustrial organizationInstitutionEmpirical researchVariance (accounting)BusinessEconomicsTest (biology)MicroeconomicsOrganizational economicsAccountingFinanceMarket economyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a study of the economic organization of systems of financial cooperatives (FC). The first part presents a theoretical framework rooted in principles of transaction cost economics (TCE) that seeks to explain empirical regularities observable in systems of FC worldwide. The second part is an empirical study that compares X-efficiency between members of the Quebec Desjardins movement (DM) and the United States Credit Union system (USCU), the first organized as a tight network of institutions and the second composed largely by independent institutions with few ties. The fundamental proposition is that networks, are a superior form of governance mechanism (over markets and mergers) for relatively wide and relevant ranges of contractual hazard and size of the institutions. Further, that networks provide substitute, hierarchy based, control mechanisms when size of the institution dilutes internal governance mechanisms, discouraging subgoal pursuits and expense preferences by agents, both occurring in large FC. The theory allows us to generate a set of testable hypothesis of which we highlight three: i) For small FC, differences in efficiency will be relatively small, if any. ii) Large institutions should display systematically lower efficiency than similar sized FC members of strategic networks. iii) Networks should display lower variance in the size as well as in performance indicators. Throughout, empirical results are consistent with our central theoretical proposition.

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.926
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.075
GPT teacher head0.255
Teacher spread0.181 · 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.

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
Published2003
Admission routes1
Has abstractyes

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