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Record W1590468843 · doi:10.17016/feds.2004.46

Competition, Product Differentiation and Quality Provision: An Empirical Equilibrium Analysis of Bank Branching Decisions

2004· article· en· W1590468843 on OpenAlexaff
Andrew Cohen, Michael J. Mazzeo

Bibliographic record

VenueFinance and Economics Discussion Series · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsCompetitor analysisMarket structureProduct differentiationCompetition (biology)Branching (polymer chemistry)EconomicsMicroeconomicsMarket concentrationIndustrial organizationQuality (philosophy)Product (mathematics)Market shareBusinessMonetary economics

Abstract

fetched live from OpenAlex

We analyze the effects of market structure on the branching decisions of three types of depository institution: multimarket banks, single-market banks, and thrift institutions. We argue that additional branches increase quality for an institution's consumers, and examine the interaction between market structure and this particular measure of quality. We account for endogenous market structure using an equilibrium structural model, which corrects for bias caused by correlation in the unobservables that may drive entry and branching activity. We estimate the model using data from over 1,750 concentrated rural markets. Our results demonstrate the importance of product differentiation, as competition from multimarket banks is associated with denser branch networks for all types of firm while the opposite correlation holds when competitors are single-market banks or thrifts.

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.039
GPT teacher head0.281
Teacher spread0.242 · 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 designSimulation or modeling
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

Citations13
Published2004
Admission routes1
Has abstractyes

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