MétaCan
Menu
Back to cohort
Record W4400991723 · doi:10.69554/ecgf9903

Fiscal consequences of scrapping cash

2012· article· en· W4400991723 on OpenAlexaboutno aff
Maurice D. Levi

Bibliographic record

VenueJournal of payments strategy & systems · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCashEconomicsCash conversion cycleCash managementBusinessFinance

Abstract

fetched live from OpenAlex

The emergence of a range of digital media of exchange such as debit cards, credit cards, pre-loaded transport tickets, cafeteria passes and telephone coupons means for the first time that money in the form of paper currency and coins is no longer essential. The scrapping of traditional cash would mean the removal of the means of anonymous exchange with implications for the fiscal deficit. On the one hand, it would mean a loss of seigniorage for national governments, with the size of this loss depending on how the cash is removed from circulation. On the other hand, it would reduce tax evasion, which would increase fiscal revenue of national, state and municipal governments. The absence of an anonymous means of exchange also has favourable fiscal implications from reduced spending on law enforcement, legal proceedings, incarceration, and public health from impeding the drug trade: digital media of exchange provide a trail to follow for illicit transactions, hindering activities of buyers and sellers. This paper calculates the size of the fiscal implications of scrapping cash and finds substantial gains for all levels of a nation’s government, even the national government that loses seigniorage. It takes the view of Canada where virtually every adult has an account at a financial institution.

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)0.001
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 score0.168
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.033
GPT teacher head0.244
Teacher spread0.211 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of payments strategy & systemsSame topicWorking Capital and Financial PerformanceFrench-language works237,207