MétaCan
Menu
Back to cohort
Record W7161945901 · doi:10.82308/37514

Evolution of the payments system and the long-term demand for money in Canada

2005· dissertation· en· W7161945901 on OpenAlexaboutno aff
Weinian Liao

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentCashDemand for moneyCointegrationPayment service providerPayment systemElectronic moneyMobile payment

Abstract

fetched live from OpenAlex

This dissertation starts by examining the evolution of the Canadian payments system from a historical perspective by reviewing the institutional evolution, as well as the development and adoption of some of the newest payment instruments. Two major trends in recent Canadian payment history are revealed, i.e., cash payments are being replaced by non-cash payments and paper-based payment instruments are being replaced by electronic payment instruments. Next, we adopt a model proposed by Snellman et al. (2000) to conduct a Canadian study of the retail cash payment flows. The estimated results imply that the share of cash, as well as cheques, in overall retail payments in Canada has declined quite considerably. We then investigate the cash substitution process, as well as the electronification of payments in Canada using S-shaped growth curve models. Our results indicate that although the card payments will continue to further substitute for cash, cash will still remain the preferred medium of retail payments in Canada. However, approximately 80% of all payments are forecasted to be electronic in just 20 years. This dissertation then extends the existing literature on the long-run money demand relationship in Canada by employing information on the payment technology development as an instrument variable to account for financial innovations that might have caused structural shifts in the money demand equation. The econometric methodology employed is cointegration and error-correction modelling. It is found that our measure of financial innovations removes most of the structural breaks in the money demand equation over the sample period. A unique and significant long-run money demand relationship is detected. The short-run dynamic specifications of the VECM system imply the weak exogeneity of output and interest rates.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.450

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 communication0.0000.001
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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicDigital Platforms and EconomicsFrench-language works237,207