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Efficiency out of disorder: Contested ownership in incomplete contracts

2009· article· en· W1997073286 on OpenAlexaff
Kurt Annen

Bibliographic record

VenueThe RAND Journal of Economics · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIncomplete contractsInefficiencyEquity (law)BusinessMicroeconomicsCONTESTTransaction costDatabase transactionInvestment (military)EconomicsIncentiveIndustrial organization

Abstract

fetched live from OpenAlex

In many situations, irreconcilable disagreements between players lead to costly ownership disputes over assets—for example, in case of joint ownership. This article studies the role of such disputes in a situation where two players have to make a transaction‐specific investment and when contracts are incomplete. I show that potentially contested ownership may mitigate the inefficiency of investments due to the incompleteness of contracts generating an exchange surplus that comes closer to the first‐best surplus as compared to any other ex ante distribution of ownership typically discussed in the literature following the influential work by Grossman, Hart, and Moore. If the contest is an all‐pay auction, each player makes a transaction‐specific investment as if he or she owns the asset. This article can explain why shared ownership—as for example in equity joint ventures, family firms, start‐up partnerships, and so on—is an important part of today's corporate landscape.

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)0.011
metaresearch head score (Gemma)0.043
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 score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.043
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.012
Scholarly communication0.0050.009
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.041
GPT teacher head0.222
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 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

Citations9
Published2009
Admission routes1
Has abstractyes

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