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Record W4394858932 · doi:10.1016/j.econmod.2024.106734

Impact of access regulation on investment reconsidered

2024· article· en· W4394858932 on OpenAlexafffund
Zhihong Chen, Zhiqi Chen

Bibliographic record

VenueEconomic Modelling · 2024
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCompetitor analysisIncentiveEconomicsInvestment (military)MicroeconomicsMarginal costValuation (finance)Industrial organizationMarket powerBusinessFinanceMonopoly

Abstract

fetched live from OpenAlex

In regulated industries like electricity, gas, and telecommunications, regulators often require vertically integrated incumbents to share their infrastructure with competitors in a related market. This paper demonstrates that such access regulation may strengthen an incumbent's incentive to invest in infrastructure even if the regulated access price of an input is set at its marginal cost. Specifically, we reconsider Kotakorpi's (2006) model under an alternative circumstance where downstream rivals would be foreclosed from the market without regulation. We find that the access regulation increases investment and improves social welfare under certain conditions. Our main conclusion is robust to an alternative way of modeling consumers' valuation of products. Furthermore, raising the access price above the marginal cost expands the parameters for which the regulation increases investment. Our analysis suggests that access regulation alone does not reduce an incumbent's investment incentive .

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)0.005
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 score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.000

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 head0.065
GPT teacher head0.295
Teacher spread0.230 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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