Will the Widespread Use of Cashless Payments Reduce the Frequency of the Use of Cash Payments?
Bibliographic record
Abstract
Will the widespread use of cashless payments reduce the frequency of the use of cash payments? This question is important because the major costs of cash use are fixed costs that would only be reduced if the frequency of cash payments substantially decreased, and thus the extent of the reduction of the cost of cash use depends on the frequency of cash use after the widespread use of cashless payment methods. Using the data from the Financial Literacy Survey 2019 in Japan, this paper shows that the frequency of cash use for those who use both cash and noncash payment methods and that of those who exclusively use cash are about once in 2.3 days and about once in 2 days, respectively, and thus there is only a slight difference. The result did not change even if a regression model for cash usage was used that considers the endogenous choice of payment methods or if counterfactual simulations of the decrease in consumers’ willingness to use cash were conducted. The results suggest that the benefit of reducing the cost of cash use due to the widespread use of cashless payment methods is overestimated because the frequency of the use of cash payments is unlikely to decrease despite the use of cashless payment methods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".