Until v5.0 the page ran this engine: each participant converted part of their own BU, and a wage contribution paid for everything. It is kept here, with its settings, presets and charts, so its choices can still be explored and checked; its figures differ from the results on the main page, which come from the release engine. The v4.22 release holds the page exactly as it was.
Cumulative Poverty Exposure how long the average agent spends below each line over the whole run — not just where they end up
Years in Wealth Poverty, per agent ⓘ
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Years in BLEI Poverty, per agent ⓘ
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Wealth Floor Diagnostic how much of the final-year result is a floor artifact, not a policy effect
Pinned at Wealth Floor, final year ⓘ
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Baseline Pinned at Wealth Floor ⓘ
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Poverty by Five Measures who is poor at the start and at the end of the run, measured five ways
Share of people in poverty at year 0 and in the final year, and how Your Settings compares
Lower is better on every measure. ▼ means Your Settings ended lower, ▲ higher. Bars compare the scenarios within each row. Year 0 is the starting population, before any policy year runs; it is the same people in every scenario, so it is a policy-neutral reference.
What each measure asks, and how it is counted
Why five measures. They answer different questions. The stock measures ask whether people have a cushion; the flow measures ask whether this year's income covers this year's needs; extreme poverty asks whether people are homeless. A policy can move one and not another, so each is reported against where people started (year 0) as well as against the Baseline.
Stock: what people own at the end of the run. Wealth poverty counts net wealth below POVERTY_LINE ($25,000). BLEI poverty counts people whose savings, income and BU cover fewer than 30 days of basic living costs. BLEI counts BU and cost relief from the day someone enrols, so its year-0 figure is shown under Baseline rules, with the figure under your settings' rules beneath it.
Flow: what people earn in the final year. Cash income is wage income plus CCO conversion proceeds; PTH appreciation is left out, as a capital gain. Relative income poverty counts cash income below 60% of that scenario's own median, so when most incomes rise together it can stay flat or even rise. Basket poverty compares income with the cost of a living-wage basket (LIVING_WAGE_ANNUAL, adjusted for inflation): "net" uses the prices each person actually pays after CCO, PTF and PTH cost relief; "gross" uses full prices. At year 0 the median person's wage income ($39,945) is below the basket ($49,370), so about two-thirds of people start in basket poverty. That starting gap is what drives the Baseline's decline (Known Limitations; CONTRIBUTING.md v4.17).
Extreme: homeless, with necessities from charity if at all. The engine models no housing, mental illness or vocation, and at the US rate (about 22 per 10,000 people, HUD's 2025 point-in-time count) this is about one person in a 500-agent run. So it is an estimated share built from three pathways, and these rows read per 10,000 people. Economic (73% at year 0) moves with the share of people in housing distress, whose income plus savings cannot cover this year's basket; CCO income and PTF and PTH cost relief lower it. Serious mental illness (25%) does not respond to income, so CCO alone leaves it unchanged; wellness zones, which need both PTH and SZH, lower it by up to half (Housing First trial evidence), scaled by zone coherence. Voluntary (2%) covers ascetics, itinerant monastics and renunciants; it is the same in every scenario, and the share will be updated as data sources become available. This definition differs from the World Bank's, which counts income below $3.00 a day. See Known Limitations and CONTRIBUTING.md v4.18.
Shock Response automatic BU increase in recessions, and what it offsets (v4.19)
How much of a recession's rise in housing distress an automatic BU increase offsets
How this is measured, and what it cannot show
Measure. Housing distress is the v4.18 measure: this year's cash income plus savings cannot cover this year's basket. For each seed the study runs your settings with recessions off and with recessions on under each rule, on the same agents, recession path and random draws. The excess is the difference in recession years, averaged over every recession year of every seed, for CCO participants and non-participants separately. Excess extreme poverty converts the all-agent excess through the v4.18 overlay's economic pathway. Extra BU is the added allocation as a share of the base allocation over the run.
Shock-neutral. The multiplier at which participants' excess distress in recession years is zero, found by false position from ×1 and ×3 (widened to ×4 if needed). At the reference settings it is ×1.36 over 300 seeds (node harness.js stabilizer), shown as ×1.35 on the slider; the scaled rule's equivalent is about +2.8% BU per 1% income loss. These are the sliders' defaults. The Research Hub's ×1.20 offsets about half of the rise. The neutral point is set by a roughly fixed amount of extra relief, about 7% of the basket, so it is the same in every environment at the same BU and 0% inflation, and higher where inflation erodes an unindexed BU: ×1.40 in Adverse Environment and ×1.55 in Stress Test (v4.21).
Why the default is a target, not the peak of a curve. Returns to a larger increase are close to linear, because the engine has no price response to BU issuance and no budget constraint. A larger increase never looks worse, and the model cannot test whether it would be inflationary. The default is the smallest increase that fully offsets a recession for the people it reaches.
How the BU amount reaches a household (v4.19). Through v4.18, CCO's cost relief was a flat 20% of the basket whatever the BU amount, so a larger BU helped only through conversion proceeds, which runYear() credits once a year. The framework describes BU as redeemable for essential goods, so from v4.19 the relief scales with the BU actually issued: 20% at the $1,200 reference, in proportion above and below it, up to a 50% ceiling (a placeholder). Every $1,200 preset is unchanged. Under the v4.18 rule the shock-neutral multiplier was ×2.35.
Reach. A BU increase reaches only CCO participants. Emergency enrollment extends the CCO cost relief to non-participants in triggered years; its 50% take-up default is a placeholder with no source.
Place-based BU premiums (not simulated)
The same lever can target places as well as times. A region that wants to attract residents, such as a cold-climate area with little winter sunlight, could add a BU premium for residents who meet a residency requirement, much as Alaska's Permanent Fund Dividend pays each qualifying resident after a full calendar year of residence. Whether such payments move people is not well established: a 2019 University of Alaska review lists the dividend's effect on in-migration among the questions not yet studied. The closest measured case, Tulsa Remote, pays remote workers $10,000 to relocate; an Upjohn Institute evaluation (Bartik, 2025) estimates that 58–70% of participants would not have moved without it. Remote workers are a different population from households in poverty, and the same evaluation notes that added housing supply is needed to realise the benefits. A payment tied to a place can also be absorbed by higher local rents; Public Trust Housing, whose costs are set outside the private rental market, could limit that. This simulation has no geography, so it reports no result for this use.
Mean ± SD. Use Run 10× or 50× for 95% CI (mean ± t·SD/√n, Student's t) — a stochastic-error range from re-running this simulation with the same parameters, not a full uncertainty interval (excludes calibration, parameter, and structural uncertainty). For formal Sobol/LHC sensitivity, use CSV export with Python/R.
Participant Stratification tests whether CCO benefits participants without harming non-participants
Participant Poverty
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Non-Participant Poverty
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Participant Median BLEI
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Non-Participant BLEI
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One-at-a-Time (OAT) Sensitivity each parameter varied ±20% of its own slider range · computed from actual simulation runs · not Sobol/LHC
Poverty & BLEI response — One-at-a-Time computed estimates
⏳ Running sensitivity scenarios…
Each row = parameter varied ±20% of its own slider range from current settings, 200 agents, 10 years, fixed seed 7777. These are scenario-comparison estimates. Use CSV export for formal Sobol/LHC analysis.
Latin Hypercube Design — Quick Preview
Wealth poverty vs. monthly BU allocation across the sampled design points
In-app sanity check only — darker points sampled a higher participation rate. Each point is a 200-agent/10-year mini-simulation from the exported CSV, seed 7777 (matching OAT's convention). Not a substitute for the CSV + external analysis this export exists for (first-order indices by RBD-FAST or the delta method; see the CSV's note, corrected in v4.20).
Internal Consistency & Behavioral Test Suite
Sanity checks — internal consistency (200–500 agents, 10–20 years each)
⏳ Running checks…
Internal design-target and structural-invariant checks (ODD Level 1–3: code correctness, mathematical invariants, behavioral validation) — not external empirical validation (Level 4–5, not yet performed; see Known Limitations). All six should PASS under well-calibrated parameters. Report failures via CONTRIBUTING.md.
Economic Trajectory
Poverty rate — scenario vs baseline
Dashed = US welfare baseline trajectory (same years; recessions apply to baseline only when your scenario has them enabled — see Cumulative Bug Fixes)
Gini coefficient over time
Wealth distribution — p10 / median / p90
Dashed lines = bottom/top deciles · Filled band = median trajectory · Inequality envelope
Poverty & Wealth Threshold Sensitivity every possible threshold at once, not just this model's own defaults
Wealth poverty rate, by threshold — final year
Computing…
BLEI poverty rate, by threshold — final year
Computing…
Rather than reporting poverty at one fixed dollar or day cutoff, these curves show a full range of thresholds at once — the "poverty dominance" approach used in the poverty-measurement literature (Atkinson 1987; the World Bank's own practice of reporting multiple poverty lines) to avoid resting a claim on any single contested figure. If a scenario's line sits below another's across the whole range shown, it reduces poverty no matter where the "true" line is drawn. "Avg. shortfall" (v4.11) answers a different question the headcount view can't: two scenarios can show identical % curves while differing a lot in how deep the remaining poverty runs — the poverty-gap view shows that depth directly, in the same dollars/days as the axis itself. See the Assumptions panel below for the full rationale, including why LIVING_WAGE_ANNUAL is a separate question from what's shown here. Reading the dominance check (v4.12, caveated v4.13): it is evaluated at the thresholds actually plotted, not continuously, so a crossing narrower than one grid step would not be reported; and it describes this single stochastic run, not a confidence statement — re-run with several seeds (or use Run 10×/50×) before treating a dominance result as a property of the configuration rather than of the draw.
Distribution Trajectories
BLEI tier composition over time
Stacked bars show share of agents in each tier per year — welfare trajectory across the full simulation
BLEI component medians — cashDays · incomeDays · benefitDays
Three-component decomposition: savings buffer · income flow · BU food basket (Johnson & Claude, 2026 §3). cashDays (left axis) typically dominates by 60-100x as wealth compounds — incomeDays and benefitDays (right axis, a much smaller scale) would otherwise be squashed flat against it. benefitDays is close to flat by design: BU is a fixed monthly allocation, so its BLEI contribution barely moves year to year.
Participant vs Non-Participant Analysis tests whether CCO creates net positive welfare without harming non-participants
Poverty rate by participation status
If non-participant poverty does not worsen, CCO generates net welfare gain
Median BLEI by participation status
BLEI gap between participants and non-participants quantifies direct CCO welfare contribution
Policy Milestones
First year each target threshold is crossed
Milestones reflect the animated main run only, not comparison scenarios. "—" indicates threshold not reached in simulation period.
Social Security-Anchored Cohorts
Outcomes for agents whose year-0 wage sits at real-world SSI / SSDI / retirement benefit levels
Reference points only, not a simulated Social Security mechanism — the model has no age/disability/retirement structure. Cohorts are cross-sectional (tagged by initial wage, not tracked over time) from this single run; see CONTRIBUTING.md for the full N=5,000 harness study these figures cross-check against, especially for the small SSI-level cohort.
📊 Illustrative reference run — seed 42 · Full Integration preset · 20 years · Adjust parameters and click ▶ Run Simulation to update with your current settings.
System comparison — final-year results Baseline/CCO-only top tier = Comfortable; CCO+PTF = Flourishing
Top BLEI tier label: 'Comfortable' for baseline/CCO-only (730+ days aspirational without PTF/PTH cost reduction); 'Flourishing' when CCO+PTF active. Both thresholds = 730 days — label reflects realistic attainability. See BLEI paper for full tier definitions.
Configuration
Poverty elim.
Median wealth
Gini
Median BLEI
Avg EDC (design target proxy)
Stability
Run the simulation to see results.
Research Export
v4.0 — full annual time-series (poverty, Gini, wealth p10/p50/p90, BLEI components, participant stratification, baseline) plus cumulative CCO conversion proceeds. JSON export includes complete parameter + results snapshot for replication.
These are documented scenario-comparison estimates from the Replication Framework, not computed Sobol or Latin hypercube indices. For rigorous formal sensitivity analysis, use the CSV export with 50–100 varied runs. See Replication Framework → Sensitivity Analysis for methodology guidance.
BLEI gain attribution — system contribution analysis
⏳ Calculating ablation analysis…
BLEI days lost when each system is removed · 200-agent ablation subsample · Distinct stochastic realisation from main run · Each bar is a compound effect: removing a system also removes its feedback through FBS, octave advancement and wage growth (ODD: Feedback structure), so the bars need not sum to the combined gain (v4.20)
▶ 📋 Assumptions, calibration notes and version history
At the release these moved to the replication page (the full ODD protocol, every assumption and known limitation, the calibration notes and the version history). The short list of limits is at the top of this page.
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📚 References & Citations
click to expand
Autor, D.H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30. [automation risk]
Bass, F.M. (1969). A new product growth model for consumer durables. Management Science, 15(5), 215–227. [PTF diffusion model]
Carroll, C.D. (1997). Buffer-stock saving and the life cycle/permanent income hypothesis. Quarterly Journal of Economics, 112(1), 1–55. [wage diminishing returns]
Champlain Housing Trust. Community Land Trust Program.champlainhousingtrust.org. [PTH liquidity haircut — flat 50% through v4.4; tenure-based schedule from v4.5, see Cumulative Bug Fixes]
Epstein, J.M. & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. MIT Press. [ABM calibrated-unit convention]
Frey, C.B. & Osborne, M.A. (2013). The Future of Employment: How Susceptible Are Jobs to Computerisation? University of Oxford. [automationRisk calibration]
Goering, P., et al. (2014). National At Home/Chez Soi Final Report. Mental Health Commission of Canada. Main messages (PDF). [extreme poverty: wellness-zone effect, EP_WZ_EFFECT, v4.18]
Grimm, V., et al. (2010). The ODD protocol: A review and first update. Ecological Modelling, 221(23), 2760–2768. [ABM documentation standard]
Gutwinski, S., Schreiter, S., Deutscher, K. & Fazel, S. (2021). The prevalence of mental disorders among homeless people in high-income countries: An updated systematic review and meta-regression analysis. PLOS Medicine, 18(8), e1003750. doi:10.1371/journal.pmed.1003750. [extreme poverty: SMI share, EP_SMI_SHARE, v4.18]
Johnson, D. & Claude (Anthropic). (2026). Basic Living Economic Index (BLEI). Better To Best Research Hub. CC BY 4.0. ↗ paper
Johnson, D. & Claude (Anthropic). (2026). Compassionism Framework Simulation. Better To Best Research Hub. Source code: Apache License 2.0 (as of v4.8). ↗ DOI: 10.17605/OSF.IO/QWTE2 — OSF metadata updated (v4.9) to reflect the Apache 2.0/CC BY 4.0 split; see CONTRIBUTING.md's License section. [archived version of this tool]
Jones, D. & Marinescu, I. (2018). The labor market impacts of universal and permanent cash transfers. NBER Working Paper 24312. [Alaska PFD analogue]
Mullainathan, S. & Shafir, E. (2013). Scarcity: Why Having Too Little Means So Much. Times Books. [FBS bandwidth constraint, wage growth]
NBER Business Cycle Dating Committee. U.S. Business Cycle Expansions and Contractions.nber.org. [beta(5,2) recession calibration]
U.S. Bureau of Labor Statistics. (2023). Consumer Expenditure Surveys.bls.gov/cex. [BASE_DAILY_COST $68.33/day]
U.S. Department of Housing and Urban Development. (2026). The 2025 Annual Homelessness Assessment Report (AHAR) to Congress, Part 1: Point-in-Time Estimates of Homelessness.huduser.gov. [extreme poverty: year-0 rate, EP_Y0_RATE, v4.18]