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Record W16045334 · doi:10.1177/178359170300400403

Unintended and Persistent Consequences of Regulation: The Case of Cable Television Provision in Canada

2003· article· en· W16045334 on OpenAlexaboutno aff
Stephen M. Law, James Nolan

Bibliographic record

VenueCompetition and Regulation in Network Industries · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDeregulationUnintended consequencesEconomies of scaleIncentiveIndustrial organizationScale (ratio)Cable televisionEconomicsFunction (biology)Competition (biology)BusinessEstimationMicroeconomicsMarketingPublic economicsMarket economyTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Economic regulation can have unintended consequences that are detrimental to subsequent policy change if the regulatory regime has institutionalized certain aspects of firm behaviour. For example, in a post-deregulation environment, unforeseen scalerelated phenomenon may persist in an industry that was formerly regulated according to firm size. Unfortunately, in many industries such effects can be difficult to identify. We examine measures of efficient scale for annual cross-sectional data from the cable television industry in Canada from 1992–1996, a time when the industry was being partially deregulated. Due to sample size problems among some of the size categories of interest, we estimate efficient scale in the industry using both a translog cost function and a non-parametric efficiency estimation method. We find that well after partial deregulation, the points of efficient scale in the industry can still be found at those size categories specified in the repealed rules. We label this phenomenon “regulatory persistence” and offer an explanation specific to this industry: the technology of cable television provision encouraged optimal firm sizes corresponding to the size categories found in the regulatory regime. These findings are further evidence of the existence of complex incentive structures between firms and regulators in the cable television industry.JEL Classification: C61, L82

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.338
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.194
Teacher spread0.175 · 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 teacher head, 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

Citations2
Published2003
Admission routes1
Has abstractyes

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