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Record W2488232302 · doi:10.1111/1475-679x.12124

Public Information Precision and Coordination Failure: An Experiment

2016· article· en· W2488232302 on OpenAlexafffund
Sanjay Banerjee, Michael S. Maier

Bibliographic record

VenueJournal of Accounting Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCoordination failureComplementarity (molecular biology)OperationalizationBusinessCoordination gameAuditEconomicsMicroeconomicsAccountingIndustrial organizationPublic economics

Abstract

fetched live from OpenAlex

ABSTRACT More precise public disclosure reduces uncertainty about economic fundamentals, but it can increase uncertainty about other agents' actions, leading to coordination failure. We conducted a laboratory experiment to study the effects of public information precision and strategic complementarity on coordination failure. Information precision is operationalized in terms of “granularity” (level of detail). We found that (1) granular public disclosure, which is disaggregated and precise, increases the likelihood of coordination failure and decreases coordination efficiency when public information is pessimistic about future economic prospects; (2) the deleterious effect of granular disclosure is stronger when strategic complementarity is high; and (3) higher levels of strategic complementarity decrease coordination efficiency. Overall, the observed likelihood of coordination failure is higher and coordination efficiency is lower than predicted by theory. Our findings have implications for the Federal Reserve's decision to publicly disclose detailed stress test results for distressed banks, and the debate on whether the Public Company Accounting Oversight Board should publicly release reports on firm‐specific quality‐control deficiencies of audit firms.

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)0.006
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.016
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 head0.041
GPT teacher head0.302
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations17
Published2016
Admission routes2
Has abstractyes

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