On ‘Rusting’ Money. Silvio Gesell’s Schwundgeld Reconsidered. Part I: The Short Run
Bibliographic record
Abstract
Silvio Gesell hypothesized that money depreciation is economically and socially beneficial, ideas that have often been contended. Here I analyze the spirit of his claims in a Sidrauski model in which households additionally have a ‘love of wealth’-motive. The analysis is presented in two parts, one focusing on the short and the other one on the long run. In the first part of this work these features provide the microfoundations for analyzing Gesell’s claim for the short run. Contrary to some claims it is shown Gesell’s conjectures may indeed be valid in a demand-determined, short-run equilibrium and why money depreciation overcomes the zero lower bound on nominal interest rates. These results are checked against the recent demonetization episode in India and essentially found to be true. Hence, Gesell’s hypotheses can be verified for a plausible, short-run environment and may be relevant for current economic, especially, monetary policies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".