Dynamic Leverage Pricing for Non-Transferable Time Credits: Solving Skill-Mismatch in Volunteer & Public-Good Labor

Problem Classic time-banking systems (Ithaca Hours, LETS, Edgar Cahn’s Time Dollars) use a fixed 1:1 exchange rate: one hour of any labor equals one hour of credit, regardless of skill or scarcity. This has a well-documented failure mode: when a scarce or high-skill task (medical consult, plumbing repair) is priced identically to a low-skill, abundant one (dog walking, data entry), skilled contributors disengage, scarce categories go permanently unfilled, and the system either collapses or quietly reverts to informal favor-trading outside the ledger. The goal here is a mechanism that keeps the core properties of time banking that make it attractive — non-transferable credits, no money, no accumulation into a de facto currency — while fixing the fixed-rate problem, without reintroducing a priced labor market or a central administrator manually setting rates. Mechanism 1. Cold start The system launches with a flat 1:1 baseline: one hour of registered task time equals one unit of standard credit, for every task category. Entry requires only a minimal competency check for skill-gated categories (e.g. basic verification for first-aid or plumbing tasks) — no formal certification bureaucracy. 2. Gap detection A shared ledger tracks, per task category, the ratio of posted task-hours to filled task-hours over a rolling window (e.g. 2–4 weeks). A category is flagged as “in deficit” when unfilled hours exceed a threshold for N consecutive windows. 3. Dynamic rate adjustment When a category is in sustained deficit, its exchange rate is increased algorithmically (e.g. 1:1 → 1:1.5 → 1:2), making it more attractive relative to other categories, without changing what credits can be redeemed for. As supply catches up and the deficit clears, the rate decays back toward the 1:1 baseline over a fixed half-life, rather than snapping back instantly (to avoid oscillation). 4. Multi-signal feedback (beyond raw supply/demand) Two additional signals correct for a failure mode that pure supply/demand tracking misses — a category can look “adequately priced” by the numbers while actually being miserable to do: Exit rate : the fraction of people who accept a task and then abandon it before completion. A high exit rate on a category, even at an already-elevated rate, is treated as a signal that the task itself (not just its price) needs redesign — this is a flag for human review, not just a further rate increase. Repeat rate : the fraction of past participants willing to take the same category again. Sustained low repeat rate at a stable rate suggests the price is masking an underlying quality-of-task problem rather than a scarcity problem. Survey/intent signals : periodic lightweight surveys capture anticipated future gaps before they show up in the hard data (e.g. “would you take on X if it were offered next month”), allowing pre-emptive rather than purely reactive adjustment. 5. Non-transferability and decay Credits cannot be transferred between individuals and decay over time if unused. This is a deliberate design constraint, not an oversight: it prevents credits from being accumulated, traded, or converted into a store of wealth or status, which is the property that distinguishes this from a parallel currency. Prior art Ithaca Hours / LETS : fixed-rate time/labor exchange systems; largely stalled at small scale, with the skill-mismatch problem described above being one of the most commonly cited reasons. Al Roth et al., matching market design : extensive academic literature on allocating scarce resources without prices (kidney exchange, school choice, residency matching). Highly relevant to the allocation problem but generally solved via one-shot matching algorithms rather than a continuously adjusting rate. Uber/Lyft surge pricing : closest real-world analog for the dynamic-rate mechanic itself, but operates with real currency and no decay/non-transferability constraint — the incentive-shaping logic (raise price when supply is short, let it fall as supply recovers) is structurally similar. What doesn’t seem to exist, as far as I’ve found: a non-transferable, decaying credit system with a continuously adjusted rate driven by a multi-signal feedback loop (gap + exit rate + repeat rate + survey), rather than price or gap data alone. Open problems Sybil resistance : nothing here prevents an individual from registering multiple identities to farm high-leverage categories, dodge decay by “resetting” through a fresh identity, or dilute exit-rate/repeat-rate signals with fake activity. This is probably the single largest unsolved issue — without a reliable one-person-one-identity guarantee, none of the anti-accumulation properties actually hold. Decay-gaming : whether small, low-effort recurring transactions could be used purely to reset an individual’s decay clock without meaningful participation, and if so, what the minimum viable anti-gaming rule looks like. Oscillation and reference class size : at what community size does the gap-detection window stop producing noisy, reactive rate swings? This likely needs real deployment data rather than simulation to answer well. Long-horizon, high-specialization tasks : the mechanism assumes tasks are discrete and roughly interchangeable in duration. It has no answer yet for coordinating a small team over a multi-year project where mid-project attrition is catastrophic — that may need a structurally different, contract-like mechanism layered on top rather than a rate adjustment. What I’m looking for Pointers to prior systems that tried something like the multi-signal dynamic-rate approach (rather than fixed-rate time banking or priced surge pricing) and where it broke in practice — especially any that got past small-community scale. Also interested in known Sybil-resistance approaches that don’t require a centralized identity authority, if any credible ones exist. 3 posts - 2 participants Read full topic