MétaCan
Menu
Back to cohort
Record W2023254618 · doi:10.1162/jeea.2009.7.1.61

Information Acquisition in Interdependent Value Auctions

2009· article· en· W2023254618 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the European Economic Association · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicAuction Theory and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInterdependenceCommon value auctionMicroeconomicsStochastic gameContext (archaeology)Value (mathematics)Value of informationEconomicsInformation structureComputer scienceMathematical economics

Abstract

fetched live from OpenAlex

We consider an auction environment with interdependent values. Each bidder can learn her payoff type through costly information acquisition. We contrast the socially optimal decision to acquire information with the equilibrium solution in which each agent has to privately bear the cost of information acquisition. In the context of the generalized Vickrey-Clarke-Groves mechanism, we establish that the equilibrium level exceeds the socially optimal level of information with positive interdependence. The individual decisions to acquire information are strategic substitutes. The difference between the equilibrium and the efficient level of information acquisition is increasing in the interdependence of the bidders' valuations and decreasing in the number of informed bidders.

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.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.019
GPT teacher head0.298
Teacher spread0.279 · 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