The Abundance Compass

Executive Summary

The world's most consequential number is no longer fit for purpose. Gross Domestic Product was designed in the 1930s to measure industrial output, and it became the global standard because it was simple, comparable, and communicable. That simplicity is now a liability: GDP cannot see energy quality, compute capacity, natural capital depletion, household resilience, or subjective well-being. It measures throughput. It cannot measure direction.

In 2026, the United Nations published Counting What Counts, a report calling for a dashboard of 31 indicators across four areas to complement GDP — explicitly not to replace it. This is the right framing, and it is now politically viable. This white paper proposes the Abundance Compass: a five-layer measurement system that complements GDP without replacing it, designed for country ownership, global comparability, and real-time sensing. It adds a dimension that neither GDP nor the UN framework currently captures: compute capacity — the economic potential of artificial intelligence, and the gap between that potential and realized welfare.

The dashboard displays five layers separately: (1) Foundational Principles — security, rights, institutional trust; (2) Energy, Materials, Compute — physical and computational capacity; (3) Natural Capital — whether prosperity is sustainable; (4) Wellbeing, Equity, Resilience — lived experience and distribution; and (5) a Real-Time Sensor layer — continuous probability distributions over outcomes that matter. It does not aggregate into a single number. Aggregation requires value judgments that destroy information and invite capture; headline distillation is a separate political process, kept deliberately apart from the measurement system itself.

Every data source behind the Abundance Compass already exists. The binding constraint is not technical — it is political. This paper explains how the project navigates that constraint, and what it asks of the countries, institutions, and funders who choose to participate.

Part I — The Measurement Gap

1.1 What GDP Was Built to Do

GDP was designed for a world of physical production. Its architects — Simon Kuznets in the United States, Colin Clark in Britain, and their counterparts elsewhere — built it to answer a specific question: how much output can a wartime economy generate? It answered that question well. It was never designed to measure welfare, sustainability, or resilience.

GDP became the scoreboard of the twentieth century because it served a specific coalition: finance ministries, central banks, bond markets, and multinational corporations. These actors built an entire institutional infrastructure around it — sovereign debt pricing, central bank mandates, IMF surveillance, corporate reporting, political discourse — worth trillions in coordination value. The problem is not that GDP is wrong. It is that GDP is incomplete, and its incompleteness is now consequential.

1.2 What GDP Cannot See

Five domains are now central to prosperity and invisible to GDP.

Energy quality. GDP measures the monetary value of energy transactions. It does not measure the net energy available to society after the energy invested in extraction — the energy return on investment, or EROI. Conventional oil once returned 30 to 40 units of energy per unit invested; global aggregate EROI is now approximately 10:1. A society with declining EROI must spend more of its output simply to secure the energy it needs, a structural headwind GDP cannot see.

Compute capacity. GDP measures spending on software and services. It does not measure the computational capacity available to an economy, nor the gap between that capacity and the welfare it produces. Research by Anton Korinek and Michael McKelvey estimates quality-adjusted AI output growth above 2,000% per year and real AI GDP growth above 2,500% per year in the United States. These are signals of rapidly expanding productive capacity — but capacity is not welfare. A data center full of processors produces potential output; whether that potential becomes realized well-being depends on adoption, integration, and distribution. GDP cannot distinguish a country with vast compute capacity from one that has converted it into broad prosperity.

Natural capital. GDP counts the value of resource extraction as income. It does not deduct the depletion of the stocks from which that income is drawn. Fewer than 1% of publicly reporting companies disclose their biodiversity impacts, while an estimated $1.3 to $3.1 trillion in annual public subsidies flows to nature-destructive activities. A dashboard that ignores this is measuring the liquidation of the biosphere as if it were profit.

Household resilience. GDP measures aggregate output, not the ability of households to absorb a shock and recover. Resilience is a distributional property, not a macro aggregate — a society can have high GDP and low resilience if the gains are concentrated and the buffers are thin. Across Latin America, homicides rose nearly 50% between 2015 and 2023 even as GDP grew 17%. In Eastern Europe, GDP per capita grew faster than in Southern Europe over the past decade, but the share of wealth held by the bottom 99% declined more sharply. And while average GDP per capita in developed economies rose 12% over ten years, women's pay relative to men's improved by only 1 percentage point.

Subjective well-being. GDP assumes more output means better lives; it does not measure whether that assumption holds. The healthspan–lifespan gap — the years people live in poor health — averages 9.5 years globally, ranging from 9 to 12.5 years in the top eight pharmaceutical markets. A study published in Nature found that a slowdown of ageing that increases life expectancy by one year is worth $38 trillion over the lifetime of the current population. GDP sees healthcare spending as output; a well-being metric sees productive years as the real return.

1.3 The Political Opening

The UN's 2026 report is the political centerpiece of the current moment. It proposes 31 indicators across four areas — peace, human rights and the planet; current well-being; equity and inclusion; sustainability and resilience. Fifteen of those indicators are already SDG indicators, meaning many countries have data systems in place, and the framework is designed to be country-owned and adaptable to national priorities. Spain and Guyana are leading the intergovernmental process at the General Assembly.

This is not an academic exercise. It is a live political process with a window that will not stay open indefinitely. But the UN framework has a gap: it does not include a compute layer. In an era when artificial intelligence is becoming the primary driver of productive capacity, a measurement system that cannot see compute cannot see the future. That is the gap the Abundance Compass fills.

Part II — The Five-Layer Framework

2.1 Design Principles

Five principles govern the framework.

• GDP remains on the panel. The Abundance Compass does not replace GDP; it contextualizes it. GDP remains the scoreboard for monetary throughput, and the dashboard becomes the compass for direction.
• Five layers, no single composite. The dashboard displays layers separately. Aggregating into one number requires value judgments that destroy information. The UN framework's decision to present 31 indicators in four groups, rather than one composite, is a deliberate de-escalation of the political conflict over weighting — this paper follows that precedent and extends it.
• Country-owned, globally comparable. Indicators must be measurable with existing or near-term data systems, following the same constraint the UN framework applies by drawing on the SDG indicator set.
• Real-time where possible, annual where necessary. Prediction markets and compute telemetry update continuously; natural capital accounts update annually; well-being surveys update quarterly to annually. The dashboard accommodates heterogeneous update frequencies.
• Distributional decomposition is mandatory. Every aggregate indicator must be decomposable by income decile, gender, region, and generation.

2.2 The Structure

The dashboard is organized as a hierarchy rather than a flat list: Layer 1 is the foundation beneath everything else; Layers 2, 3, and 4 are the three operational domains that sit on top of it; Layer 5 is a continuous, real-time sensor running alongside all four. The figure below is illustrative — the percentages shown are placeholders to demonstrate the display, not live data.

In practice, each layer displays its headline indicator plus a drill-down to the full indicator set below it. The hierarchy communicates intent: foundations at the base, the three operational domains built on top of them, and a continuous real-time signal running across all four.

2.3 Layer 1: Foundational Principles

Purpose: measure whether the institutional and security preconditions for prosperity exist. The UN framework places peace, human rights, and respect for the planet as foundational principles, recognizing that well-being cannot be sustained without security and institutional legitimacy. The abundance scenarios that dominate long-horizon planning — ocean cities, orbital industry, climate repair — all require credible commitment and enforceable contracts. Without this layer, the other four are built on sand.

Headline indicator: number of planetary boundaries exceeded (of nine).

2.4 Layer 2: Energy, Materials, and Compute

Purpose: measure the physical and computational capacity available to society. This is the layer GDP cannot see at all, and it is the layer the UN framework does not yet include.

Headline indicator: aggregate EROI.

Energy indicators

Compute indicators

The Desk Power metric quantifies the economic replacement capacity of an AI server in terms of equivalent office workers — an explicit analogy to James Watt's mechanical horsepower. Concurrent Human-Speed Workflows quantifies how many simultaneous users a system can serve at a given responsiveness threshold. Together they answer the two questions that drive procurement decisions: how many employees can this replace, and how many can it serve at once.

Materials indicators

2.5 Layer 3: Natural Capital and Sustainability

Purpose: measure whether prosperity is being built by liquidating the biosphere or by sustaining it. The SEEA Ecosystem Accounting framework, formally adopted by the UN, organizes natural capital accounts around four interrelated dimensions: extent, condition, services, and assets. This framework follows that structure.

Headline indicator: natural capital stock change (year-over-year).

Extent indicators

Condition indicators

Services and assets indicators

2.6 Layer 4: Wellbeing, Equity, and Resilience

Purpose: measure whether the abundance transition is improving lived experience and broadening access.

Headline indicator: healthspan–lifespan gap.

Subjective well-being indicators

Equity and inclusion indicators

Household resilience indicators

A 2025 academic proposal defines economic resilience as the comparison of economic resource levels observed over a period after a loss, measurable at the individual or household level. This matters because resilience is not a macro aggregate — a society can have high GDP and low resilience if the gains are concentrated and the buffers are thin.

2.7 Layer 5: Real-Time Sensor

Purpose: provide continuous probability distributions over the outcomes that matter.

Headline indicator: recession probability (12-month horizon).

Part III — The Indicator Set

3.1 Full Indicator Table

3.2 Data Architecture

3.3 API Specification

The dashboard is designed to be queried programmatically, not just viewed. Three endpoint shapes cover the core use cases:

GET /api/v1/indicator/{id}?country={iso3}&from={date}&to={date}
→ { value, unit, source, update_frequency, confidence_interval, decomposition }

GET /api/v1/composite/{index}?country={iso3}&weights={json}
→ { score, components, weights, sensitivity }

GET /api/v1/prediction/{market}?platform={kalshi|polymarket}
→ { probability, liquidity, volume_24h, resolution_date, status }

3.4 Composite Indices (Secondary Views Only)

While the dashboard displays layers separately, three composite indices are available as secondary views for those who want them. They are not headline indicators.

Sustainable Prosperity Index (SPI). Based on Jackson and Victor's methodology, a weighted average of seven economic, social, and environmental performance indicators, designed to track whether improved environmental and social outcomes are possible even as growth declines to zero. Illustrative weights: economic 15%, social 35%, environmental 35%, resilience 15% — weights that are politically negotiated, not technically determined.

Abundance Index. A new composite measuring the marginal cost of survival: the cost of food, water, energy, shelter, healthcare, and education as a share of median household income. The index is 100 when costs equal income and 0 when costs are negligible. In a post-scarcity transition, this should approach zero.

Capacity-Realization Ratio. Compute capacity divided by realized welfare output. A ratio above 1 indicates unrealized potential — the key policy variable for the AI transition.

Part IV — What This Is Not

The Abundance Compass is a measurement instrument. It is not a policy program. Clarity about its boundaries is essential to its credibility.

• It is not a ranking. Version 1.0 publishes no country rankings. Rankings produce winners and losers, triggering defensive coalitions that kill measurement reform before it takes root. Countries appear in the dashboard as profiles, not positions.
• It is not a replacement for GDP. GDP remains on the panel. For the first five to ten years, GDP and dashboard indicators are reported in parallel, allowing comparison, learning, and adaptation without forcing a choice.
• It is not a policy prescription. The dashboard measures; it does not advocate. It can reveal that a country's compute capacity is not translating into welfare, but it cannot tell that country what to do about it — those are political decisions that belong to citizens and their representatives.
• It is not a single number. There is no headline composite. The five layers are displayed separately because aggregating them requires value judgments that belong in the political process, not in the methodology.
• It is not a tool for blame. The dashboard is framed as a tool for learning. The “GDP vs. Dashboard” report highlights divergences, not failures. Data is presented; conclusions are left to readers.
• It is not dependent on any single data source. Prediction markets are one sensor among many. If they are restricted or banned in major jurisdictions, the dashboard continues. If a country cannot report a particular indicator, it appears as a partial profile with published justification.
• It is not internationally imposed. Every country owns its dashboard. The core indicator set is non-negotiable, but countries may add modules, adjust presentation, and publish in their own languages. The right to withdraw is preserved with 12 months' notice.

Part V — Adoption Strategy

5.1 The Political Problem

Every measurement system creates winners and losers. GDP has been the world's dominant metric for eighty years because it served a specific coalition. A complementary dashboard does not threaten that coalition directly — it threatens it indirectly, by creating an alternative reference point for evaluating national performance. Once citizens, journalists, and opposition parties can point to a dashboard showing that GDP growth has not translated into well-being, the political monopoly of GDP is broken.

The coalition for adoption is broad but shallow. The coalition against is narrow but deep: finance ministries, central banks, and bond markets have concentrated interests in GDP orthodoxy, while citizens and civil society have diffuse interests in better measurement. Diffuse interests lose to concentrated interests in the absence of organized political entrepreneurship. The adoption strategy below is designed to navigate this asymmetry.

5.2 Incremental Integration, Not Replacement

The dashboard is never framed as a replacement for GDP. It is a complement — a compass alongside the scoreboard. GDP and dashboard indicators are published side by side for at least five years before any consideration of integration.

5.3 Country-Owned Customization

Every country customizes its dashboard — selecting optional indicators, adjusting weights for secondary composites, adding national priorities. This reduces resistance and increases ownership. A core indicator set is non-negotiable; everything else is flexible.

5.4 Statistical Capacity Building as Precondition

No country is asked to report on indicators it cannot measure. Statistical capacity building is a first-class deliverable, not an afterthought: at least 30% of the project budget is dedicated to it, in partnership with the UN Statistical Commission, the World Bank, and regional organizations.

5.5 The Finance Ministry Advisory Group

The binding constraint is finance ministry buy-in. If finance ministries feel ambushed, they kill the project quietly. If they feel consulted, they become co-authors.

A Finance Ministry Advisory Group convenes 10 to 15 senior finance ministry officials, 3 to 4 central bank research directors, 4 to 5 national statistical office heads, 2 multilateral observers, 3 academic methodologists, and 2 civil society observers, with geographic balance across Europe, Asia-Pacific, the Americas, Africa, the Gulf, and small states. The group's mandate is narrow on purpose: review indicators, flag infeasibility, advise on sequencing. It has no authority over methodology or publication — it is an early-warning system and a legitimacy shield, not a decision-making body.

5.6 Pilot Countries

Five countries are recruited for the first implementation cycle. Selection criteria weight existing well-being infrastructure, geographic and income diversity, political stability, statistical capacity, and willingness to publish openly.

This cohort covers four continents, three income levels, two petrostates, one small island state, and one post-conflict state. It produces at least three likely champions and two conditional adopters, and it avoids the U.S.–China trap entirely: the United States and China are invited as observers after version 1.0 launches, since both are too large to be early adopters and too important to be early opponents.

5.7 The Completeness Mechanism

Some pilot countries may suppress rights or subjective well-being indicators. This is not a failure of the project; it is a test of the completeness mechanism. A completeness index is published for every pilot country, showing which indicators are reported and which are omitted with justification. Over time, the gap becomes visible pressure.

5.8 Sequencing

Part VI — Governance and Funding

6.1 Secretariat

A lean team of five to seven full-time equivalents: Executive Director, Research Director, Country Engagement Lead, Data Architect, Communications Lead, Operations Manager, and one to two research analysts.

6.2 Oversight Bodies

6.3 Principles

• Country ownership of data and dashboard customization.
• Open access to all methodology, code, and aggregate data.
• No policy prescriptions — the dashboard measures, it does not advocate.
• Transparent weights for any composite index.
• Right to withdraw for pilot countries with 12 months' notice.

6.4 Funder Protections

• Ring-fenced budget by workstream with quarterly reporting.
• Independent financial audit annually.
• Sunset clause: if version 1.0 is not launched by Q2 2028, remaining funds are returned.
• No single-funder veto over publication or methodology.

6.5 Budget

The ask: $12 million over 18 months from a consortium of three to five foundations plus one multilateral partner. This avoids single-funder capture and keeps the project independent of any single government.

6.6 Methodology Papers

Five peer-reviewed, open-access papers establish technical credibility before political exposure. Without published methodology, the dashboard is vulnerable to the accusation that it is an advocacy instrument with numbers attached.

Each paper follows a standard structure: definition and measurement boundary; data sources, coverage, and imputation; comparability across income levels and governance systems; known failure modes and sensitivity analysis; relationship to GDP and to other layers; implementation cost estimate for a national statistical office; open questions and research agenda. Commissioning begins Q4 2026; lead authors are selected Q1 2027; first drafts are due Q3 2027; peer review runs Q4 2027; revision Q1 2028; publication Q2 2028.

Part VII — The Window

Three windows are open simultaneously. They will not stay open.

The political window. The UN's 2026 report has created intergovernmental momentum. Spain and Guyana are leading the process at the General Assembly, and the SDG indicator framework provides ready-made data infrastructure for 15 of the 31 core indicators. This is the first politically mandated attempt to correct a long-standing flaw in how the world measures progress.

The technical window. Data sources for all five layers now exist. SEEA EA is formally adopted. The Korinek–McKelvey AI GDP framework is published. Prediction market accuracy has been validated by Federal Reserve research. Satellite and mobile data can fill gaps in developing countries.

The institutional window. Costa Rica, Norway, New Zealand, Rwanda, and the UAE are plausible early adopters. The Wellbeing Budget precedent in New Zealand and the Well-being of Future Generations Act in Wales show that legal embedding is possible. The Human Development Index precedent shows that a complementary metric can become a global standard.

The window will close when the UN process concludes, when pilot countries lose political momentum, or when a major geopolitical crisis consumes the political capital needed for measurement reform.

Part VIII — The Ask

$12 million over 18 months from a consortium of three to five foundations plus one multilateral partner. Decision needed by Q1 2027.

What the funding delivers by Q2 2028:

• A public dashboard version 1.0 with five layers and 48 indicators.
• Five pilot countries with signed agreements and baseline reports.
• Five peer-reviewed, open-access methodology papers.
• A founding charter signed by 10 to 15 finance ministries.
• A published “GDP vs. Dashboard” report for 12 to 15 countries.
• A media playbook and launch communications strategy.

What the funding does not deliver: rankings, policy prescriptions, or a replacement for GDP. The dashboard is a compass, not a sword.

The compass is built. The ask is clear. The window is open. What remains is the coalition to navigate it.

Annex A — Indicator Set at a Glance

Annex B — Illustrative Country Profile: Costa Rica

Interpretation. Costa Rica is a high-performing country on Layer 4 relative to its GDP per capita. It has invested in natural capital and avoided the deforestation trajectory of many middle-income countries. Its weaknesses are in Layer 2: it has not developed compute capacity, and its energy system, while clean, is not positioned for the AI transition. This is the kind of insight the dashboard produces — not a ranking, but a profile of strengths and gaps.

References

United Nations (2026). "Counting What Counts." UN General Assembly report on complementary measures of progress.

Kuznets, S. (1934). "National Income, 1929–1932." Report to the U.S. Congress, 73rd Congress, 2nd Session.

Stiglitz, J., Sen, A., Fitoussi, J.-P. (2009). "Report by the Commission on the Measurement of Economic Performance and Social Progress."

Jackson, T., Victor, P. (2016). "Sustainable Prosperity Index" methodology, ecological economics literature.

International Energy Agency (IEA). World Energy Outlook and EROI-related statistics, various years.

Academic EROI literature, aggregate global estimates (various authors).

Korinek, A., McKelvey, M. "Measuring the AI Economy" — Desk Power and Concurrent Human-Speed Workflow framework; AI GDP boundary methodology.

United Nations Environment Programme, International Resource Panel (UNEP IRP). Material footprint statistics.

U.S. Geological Survey (USGS); International Energy Agency. Critical mineral dependency data.

United Nations. System of Environmental-Economic Accounting — Ecosystem Accounting (SEEA EA), formally adopted framework.

Stockholm Resilience Centre. Planetary boundaries framework and nine-boundary assessment.

OECD; UNEP. Nature-destructive subsidy tracking, $1.3–3.1 trillion annual estimate.

World Health Organization (WHO); Global Burden of Disease (GBD) study. Healthspan–lifespan gap data.

Nature (2025). Study on the economic value of a one-year increase in life expectancy via slowed ageing ($38 trillion estimate).

Gallup World Poll; OECD Well-Being Framework. Life evaluation, positive/negative affect indicators.

United Nations Development Programme / Oxford Poverty and Human Development Initiative (UNDP/OPHI). Multidimensional Poverty Index.

World Inequality Database (WID.world). Bottom 50% wealth share data.

International Labour Organization (ILO); OECD. Gender pay gap statistics.

International Telecommunication Union (ITU). Digital access gap by income decile.

Academic literature (2025). Household-level economic resilience methodology.

Federal Reserve research (various, 2025–2026). Kalshi forecast accuracy versus fed funds futures and professional forecasters; CPI and GDP prediction accuracy.

Kalshi, Polymarket, Metaculus. Platform data on prediction market pricing, liquidity, and resolution.

V-Dem Institute; Freedom House; Reporters Without Borders (RSF). Human rights and institutional indices.

World Justice Project. Rule of Law Index.

UN Sustainable Development Goals (SDG) indicator framework, Indicator 16.1.2 and related.

New Zealand Treasury. Wellbeing Budget framework and precedent.

Welsh Government. Well-being of Future Generations (Wales) Act.

United Nations Development Programme (UNDP). Human Development Index methodology and adoption precedent.