Payment Innovations, the Shadow Economy and Cash Demand of Households in Euro Area Countries
Bibliographic record
Abstract
We analyze for the first time cash holdings of private households in all euro area countries from 2002 to 2019 within a panel cointegration framework. Besides the traditional determinants of cash demand like transactions balances and opportunity costs, we concentrate on cashless payments media as substitutes to cash payments and the role of the shadow economy. Moreover, we take due account of country-specific repercussions of the financial and economic crisis of 2008/09, time series properties and distinguish between small and large countries. We find a significant and positive relationship among households' cash holdings, the volume of transactions and the size of the shadow economy irrespective of country size for all euro area countries over our sample period. Additionally, there is a substitution relationship between the accessibility and availability of cashless payments media and cash demand. And a decreasing number of ATMs reduces cash holdings. These results have important political and financial implications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".