GRF · Capital Nexus
Finance and inequality
Finance shapes who can save, borrow, insure and invest, and fiscal choices shape who pays for public capital and who benefits from it. Access gaps, the incidence of taxes and transfers, the cost of debt service and the distribution of losses after crises all carry distributional consequences. This page sets out how finance and inequality interact, how distributional outcomes and access are measured, and which institutions hold the decisions that change them.
How the work runs.
Public investment pipeline
Finance and inequality · Member state A · Budget cycle 2
Pipeline
| Coastal road upgrade | Transport | High risk | Redo | Appraisal |
| District hospital | Health | Medium | Done | Committee |
| Irrigation scheme | Agriculture | Medium | Done | Financing |
| Solar mini-grids | Energy | Low | Done | Procurement |
Committee
- Next meeting
- week 9
- Quorum
- 6 members
- Conflicts
- declared, recorded
- GRF role
- convening and methods
Investment cycle
- Identifyneeds
- Screenclimate and disaster
- Appraisecost-benefit
- Selectcommittee
- Financemix
- Implementmonitor
- Evaluateex post
Fig.Public investment pipeline: example names and illustrative values, not a record or a live system.
Finance and inequality: how the risk develops.
Distributional outcomes and access. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Access is uneven
Households and small firms without accounts, credit histories or collateral pay more for finance or go without. Women, rural populations and informal workers face the widest gaps, which limit their ability to absorb shocks.
Debt service crowds out
When interest payments rise relative to revenue, governments cut or defer spending on health, education and social protection first. The burden falls on those who rely most on public services.
Crises are regressive
Financial crises, inflation and currency collapses erode wages and savings faster than assets. Rescue measures can protect creditors and asset holders while adjustment falls on workers and taxpayers.
Fiscal incidence decides
Who pays taxes, who receives transfers and who uses public services together determine whether public finance narrows or widens inequality. Incidence analysis makes that distribution visible before decisions are taken.
Activity and exposure in Latin America and the Caribbean.
Night lights, population density and flood water over Latin America and the Caribbean, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Activity and exposure, for this page
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and overpass timing leave gaps)
- Source
- VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
- Provider
- NASA LANCE FIRMS
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds and overpass timing leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 500 m grid
- Uncertainty
- Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Activity and exposure, framed on Latin America and the Caribbean.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological Survey · CIESIN/Columbia, NASA SEDAC HBASESources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Context: CIESIN/Columbia, NASA SEDAC HBASE. Center for International Earth Science Information Network (CIESIN), Columbia University, and NASA Socioeconomic Data and Applications Center (SEDAC): Global Human Built-up And Settlement Extent (HBASE) 2010; Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030; Global Urban Heat Island (UHI) Data Set, 2013.
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Adults with an account at a financial institution or mobile money provider | percent of adults, by sex and income group | triennial | Global Findex household survey | OBSERVED |
| Gini index of disposable income | index (0 to 100) | annual where surveyed | Household income and expenditure surveys | ESTIMATED |
| Interest payments relative to revenue | percent of general government revenue | annual | Government finance statistics | Published statistics |
| Change in inequality from taxes and transfers | Gini points (market to final income) | per study | Fiscal incidence analysis | MODELLED |
| Social spending | percent of GDP | annual | Government expenditure by function | Published statistics |
| Small firm credit gap | US dollars | per assessment | Enterprise surveys and financial sector data | ESTIMATED |
| Remittance transfer cost | percent of amount sent | quarterly | Remittance Prices Worldwide | OBSERVED |
Exercise a cascade in finance and inequality with the people who decide.
Assembled from the Nexus Standards area profile Disaster and climate risk finance: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. To model a place of your own choosing, open the full System Builder.
Hazards
- Tropical cyclone
- Earthquake
- Ice-jam flood
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Aftershock sequence (set off downstream)
- Fault surface rupture (set off downstream)
- Soil liquefaction (set off downstream)
- Slope slide (set off downstream)
- Rockfall (set off downstream)
- Tsunami (set off downstream)
- Building collapse (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-F8Parametric and index-based risk transferNRS-F7Disaster risk finance and pre-arranged financeNRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-D1Risk-informed development and project screeningNRS-H28Hazard family: Climate-state shifts (NHS-1 eco.climate-state)
Observation
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- CHIRPS quasi-global gridded precipitation (listed for reference)
- USGS earthquake GeoJSON summary feeds (listed for reference)
- Total public international support for national disaster risk reduction actions (Sendai indicator F-1)
- Direct economic loss attributed to disasters in relation to global GDP
Example geography
- Western Europe: 152 hexagonal cells
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| World Bank Global Findex Database | Account ownership, saving, borrowing and resilience by population group | CC BY 4.0 |
| World Bank Poverty and Inequality Platform | Poverty and inequality estimates from household surveys | CC BY 4.0 |
| IMF Financial Access Survey | Supply-side data on access to and use of financial services | Free, IMF copyright and usage terms |
| Commitment to Equity Institute Data Center | Fiscal incidence studies of taxes, transfers and services | Free, registration and attribution |
| World Inequality Database | Income and wealth distribution series combining surveys, tax and national accounts | Free, attribution |
| World Bank Remittance Prices Worldwide | Cost of sending remittances by corridor | CC BY 4.0 |
| UNCTAD A World of Debt | Public debt and interest burdens set against social spending | Free, UN terms of use |
How finance and inequality is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Development outcomes
The Sustainable Development Goals and targets that outcomes on finance and inequality are reported against.
| Goal | Target | How this subject links |
|---|---|---|
| Goal 1, no poverty | Target 1.5, resilience of the poor and vulnerable | Outcomes reported through the agreed indicator of the target |
| Goal 17, partnerships for the goals | Target 17.4, long-term debt sustainability | Outcomes reported through the agreed indicator of the target |
| Goal 10, reduced inequalities | Target 10.5, regulation and monitoring of financial markets | Outcomes reported through the agreed indicator of the target |
| Goal 16, peace, justice and strong institutions | Target 16.6, effective, accountable and transparent institutions | Outcomes reported through the agreed indicator of the target |
Who decides, and what the evidence serves.
Capital Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Finance ministries | How fiscal adjustment, tax reform and debt service affect different income groups | Fiscal incidence studies, interest burdens and social spending by function |
| Central banks and financial regulators | How to widen access and protect consumers without raising stability risks | Access and usage data by group; supervisory and complaint records |
| Parliaments | Whether budgets protect essential services when debt service rises | Interest relative to revenue, social spending trends and incidence evidence |
| Multilateral boards | Whether programme design includes social spending floors and distributional analysis | Programme documents, social spending floors and post-programme reviews |
Outputs this topic produces
- Distributional briefs on debt service and social spending, with sources labelled
- Dialogue papers on financial inclusion policy and consumer protection
- Notes on fiscal incidence methods and their assumptions
- Question sets for distributional review of adjustment programmes
What experts ask.
- 01
Who has access to finance?
How access to credit, savings, payments and insurance varies by income, gender, location and enterprise size.
- 02
Who bears risk?
How losses from shocks are distributed between households, firms, financial institutions and the state.
- 03
How do crises affect inequality?
How recessions, disasters and financial crises change the distribution of wealth and income.
- 04
What do policies do?
Distributional effects of monetary, fiscal and financial regulation.
What drives the issue.
Households and small firms with little savings and no insurance absorb shocks by selling assets, cutting consumption or borrowing at high cost, which can trap them in poverty. Access to appropriate financial services helps them manage risk.
Credit allocation follows collateral and information. Those without formal titles, credit histories or stable incomes are excluded or pay more, including many women, informal workers and rural households.
Asset price movements redistribute wealth. Policies that raise asset prices benefit those who own assets; inflation and unemployment fall hardest on those without buffers.
Climate and disaster losses are regressive in effect, because poorer households have less protection and recover more slowly. Financial instruments can reduce or deepen this, depending on design.
Digital finance changes access and risk at once. Mobile money and digital credit have widened access in many places, while raising new questions about data use, over-indebtedness and consumer protection.
Why now: the people and places most exposed to shocks often face the highest cost of capital and the least insurance. Capital Nexus convenes dialogue on how public finance decisions distribute risk, with affected constituencies taking part and dissent recorded.
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Household surveys | Access, use and financial health | Infrequent and costly |
| Distributional analysis | Effects of policies on groups | Model assumptions matter |
| Post-shock studies | Recovery paths by group | Hard to follow households over time |
| Administrative data | Credit and insurance coverage | Privacy limits access |
How it is studied, and what the methods cannot say.
- 01Economics and development economicsAppraisal of public investment · Fiscal incidence of policy choices · Indirect costs of shocksApplied here
- 02Policy, institutional and decision scienceMandate and decision-rights mapping · Institutional assessment synthesisApplied here
- 03Financial economics and macro-financeDebt sustainability under stress · The sovereign and bank feedback loopApplied here
Questions and answers.
Why do survey and tax-based inequality estimates differ?
Is financial inclusion always beneficial?
What is fiscal incidence analysis?
Does Capital Nexus advocate particular redistribution policies?
Why include inequality in a capital platform?
Is microfinance the answer to exclusion?
Contribute evidence from this page.
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