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Record W1964712274 · doi:10.3386/w16166

Evidence of a Modest Price Decline in US Broadband Services

2010· report· en· W1964712274 on OpenAlexaff
Shane Greenstein, Ryan C. McDevitt

Bibliographic record

VenueNational Bureau of Economic Research · 2010
Typereport
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsBroadbandEconomicsBusinessTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

In this paper, we construct a price index for broadband services in the United States between 2004 and 2009.We analyze over 1500 service contracts offered by DSL and cable providers in the United States.We employ a mix of matched-model methods and hedonic price index estimations to adjust for qualitative improvements.In general, we find some evidence of a quality-adjusted price decline, but the evidence points towards a modest decline at most.Our estimates of the price decline range from 3% to 10% in quality-adjusted terms for the five-year period, which is faster than the BLS estimates for the last three years.These modest price declines look nothing like other parts of electronics, such as computers or integrated circuits, which raises many questions.The results also inform a range of policy discussions about US broadband services.

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)0.010
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 score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.281
GPT teacher head0.499
Teacher spread0.218 · 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

Citations34
Published2010
Admission routes1
Has abstractyes

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