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Record W2560674455

Understanding Strategies in the Combinatorial Clock Auction: The Case of Canada's 700 MHz Auction

2016· article· en· W2560674455 on OpenAlexaboutno aff
Fernando Beltrán

Bibliographic record

VenueSSRN Electronic Journal · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicAuction Theory and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSpectrum auctionAuction theoryCombinatorial auctionReverse auctionComputer scienceRevenue equivalenceBiddingBusinessAuction algorithmVickrey auctionTelecommunicationsMarketing
DOInot available

Abstract

fetched live from OpenAlex

Industry Canada, the authority charged with radio spectrum allocation and assignment in Canada, administered a Combinatorial Clock Auction in 2014 whereby a sizable number of spectrum licenses were awarded to a handful of telecommunications operators to provide 4G cellular service throughout the Canadian provinces.The auction format, the Combinatorial Clock Auction (CCA), is now increasingly replacing the Simultaneous Multiple Round Auction (SMRA) as the preferred method to assign commercial radio spectrum. The CCA has been used in several countries by spectrum authorities to assign spectrum bands for cellular (4G) services and wireless broadband.In its essential design the Canadian CCA consists of two main stages: the Allocation stage and the Assignment stage; in turn the allocation stage is further divided in two: the Clock Rounds and the Supplementary Round. This paper discusses the main features of the CCA and highlights some of the differences with other previously used formats. Next, it uses an extensive repository of data from the results of Canada’s 700 MHz auction in order to analyse the strategic aspects of auction participants' bids occurred during the first stage of the auction, known as the Clock Rounds. Data is publicly available, posted by Industry Canada, and traces every bidder’s demand history throughout the auction represented by the round-to-round demanded bundles and the aggregate bid (bid price) for each bundle. Bidding data also shows a bidder's eligibility and activity levels, two important auction measurements of activity that constrain a bidder's behaviour.

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)0.008
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.077
GPT teacher head0.332
Teacher spread0.255 · 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 designTheoretical or conceptual
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

Citations1
Published2016
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicAuction Theory and ApplicationsFrench-language works237,207