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Record W2040097983 · doi:10.1257/aer.101.7.3130

Who Thinks about the Competition? Managerial Ability and Strategic Entry in US Local Telephone Markets

2011· article· en· W2040097983 on OpenAlexaff
Avi Goldfarb, Mo Xiao

Bibliographic record

VenueAmerican Economic Review · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsUniversity of Toronto
FundersEwing Marion Kauffman Foundation
KeywordsCompetitor analysisCompetition (biology)Sample (material)EconomicsTelephone surveyMicroeconomicsMarketingIndustrial organizationBusinessManagement

Abstract

fetched live from OpenAlex

We examine US local telephone markets shortly after the Telecommunications Act of 1996. The data suggest that more experienced, better-educated managers tend to enter markets with fewer competitors. This motivates a structural econometric model based on behavioral game theory that allows heterogeneity in managers' ability to conjecture competitor behavior. We find that manager characteristics are key determinants in managerial ability. This estimate of ability predicts out-of-sample success. Also, the measured level of ability rises following a shakeout, suggesting that our behavioral assumptions may be most relevant early in the industry's life cycle. (JEL L96, L98, M10)

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.023
GPT teacher head0.239
Teacher spread0.216 · 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 designObservational
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

Citations222
Published2011
Admission routes1
Has abstractyes

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