GCRI · Economic Development
Inclusive productivity
Productivity, the output produced per worker or per unit of input, drives long-run living standards. In many economies a small group of firms and places pull ahead while most lag, and gains do not reach workers evenly. This page sets out how productivity grows and spreads, why it often stays concentrated, how it is measured, and what evidence serves the ministries and agencies that seek growth whose gains are widely shared.
How the work runs.
Shock propagation model
Inclusive productivity · National economy · Scenario: import price shock
Output impact by channel
Most affected sectors
| Food processing | ▼ 9 | 3288 | Backward |
| Transport | ▼ 5 | 1016 | Forward |
| Construction | ▼ 4 | 1920 | Backward |
| Retail | ▼ 2 | 10,543 | Demand |
Fiscal room
local units, billions, illustrative
Fig.Shock propagation model: example names and illustrative values, not a record or a live system.
Inclusive productivity: how the risk develops.
Productivity, distribution and economic opportunity. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Leaders pull away
Frontier firms adopt technology and management practices quickly, while many small and informal firms lag. The gap between them can widen even as averages rise.
Workers move slowly between sectors
Moving labour from low- to high-productivity activities raises growth, but skills, location and information slow that reallocation.
Misallocation holds output down
Credit, land and regulation often favour connected firms over productive ones, so capital and labour are not used where they produce most.
Gains are shared unevenly
Productivity growth raises wages only where labour markets, bargaining and skills let workers capture some of it.
Activity and hazards in Africa.
Night lights, population density and true-colour imagery over Africa, 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 hazards, for this page
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 hazards, framed on Africa.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 · NASA HLS S30Sources 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
- GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- 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
- 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.
- Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). 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).
- 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).
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (7 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
- Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 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
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
Productivity depends on the domains that sustain workers and firms.
Findings are designed for the Country Systems Risk and Resilience series. Productivity is measured in the national accounts (SNA 2025 now being introduced) with labour and firm surveys.
- Firm survey data.
- Productivity studies with distribution.
Model inclusive productivity as a system. Run the cascade.
Assembled from the Nexus Standards area profile Financial and economic risk standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Sea-level rise
- Dam failure
- Coastal flood (set off downstream)
- Storm surge (set off downstream)
- High-tide flooding (set off downstream)
- Coastal erosion (set off downstream)
- Saltwater intrusion (set off downstream)
- Estuary flood (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Coastal habitat squeeze (set off downstream)
- Wetland loss (set off downstream)
- Mangrove loss (set off downstream)
- Groundwater flood (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
- Climate-driven migration and relocation (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-H59Hazard family: Economic shocks and governance failure (NHS-1 soc.economic)NRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H118Hazard family: Organised crime and illicit economies (NHS-1 soc.crime)NRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-U27Universe platform profile: Sovereign Capital Nexus
Observation
- IMF data services (WEO, IFS, FSI via SDMX) (listed for reference)
- BIS Data Portal (credit, debt service, property prices, banking statistics) (listed for reference)
- World Bank Open Data and World Development Indicators API (listed for reference)
- OECD Data Explorer (SDMX API) (listed for reference)
- Macroeconomic Dashboard
- Debt service as a proportion of exports of goods and services
- Financial Soundness Indicators
Example geography
- Western Europe: 152 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
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 |
|---|---|---|---|---|
| Labour productivity | output per worker or per hour in constant prices | annual | National accounts and labour statistics | Published statistics |
| Total factor productivity | index | annual | Growth accounting databases | ESTIMATED |
| Productivity dispersion across firms | ratio of top to bottom deciles | per census or survey | Firm-level data | ESTIMATED |
| Labour share of income | percent of GDP | annual | National accounts | ESTIMATED |
| Informal employment | percent of employment | annual | Labour force surveys | Published statistics |
| Real wage growth | percent change | annual | Wage statistics | Published statistics |
How inclusive productivity is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Sensitivity analysis
Which inputs move the result for inclusive productivity most, one at a time across their stated ranges.
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 |
|---|---|---|
| Penn World Table (Groningen Growth and Development Centre) | Output, inputs and productivity across countries | Open, CC BY 4.0 |
| ILOSTAT | Employment, informality, labour share and wages | Open, CC BY 4.0 |
| World Bank Enterprise Surveys | Firm performance, constraints and practices | Free with registration, World Bank terms |
| OECD Productivity Statistics | Productivity by country and industry | Public, OECD terms |
| UNU-WIDER and GGDC Economic Transformation Database | Sectoral employment and value added | Open, licence to check |
Who decides, and what the evidence serves.
Economic Development 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 |
|---|---|---|
| Ministries of finance and planning | Which constraints on productivity to address first | Productivity profiles; misallocation evidence |
| Ministries of labour | How to help workers share productivity gains | Wage and labour share evidence |
| Development banks | Where support for firms and skills raises productivity most | Firm-level evidence |
Outputs this topic produces
- Productivity profiles by sector, firm size and region
- Decompositions of growth into within-sector and structural change
- Analyses of how gains reach wages
- Evidence notes for growth strategies
What experts ask about inclusive productivity.
- Why do productivity levels differ so much between firms, sectors and countries?
- How much of productivity growth reaches workers as higher wages?
- What prevents small firms and informal workers from becoming more productive?
- How do shocks affect productivity in the long run, through lost capital and skills?
- Which measures widen access to opportunity without reducing growth?
What drives productivity and its distribution.
Productivity rises through better technology, more and better capital, improved skills and management, and the reallocation of resources from less to more productive uses. In many developing economies, large differences in productivity exist within the same sector, with many small, informal firms alongside a few highly productive ones.
Distribution depends on how gains are shared between capital and labour, between skilled and less skilled workers, and between regions. Market power, labour institutions, access to finance and education all shape this. Productivity growth concentrated in capital-intensive sectors may create few jobs.
Shocks can have lasting effects. Firms that close lose organisational knowledge; workers who are unemployed for long periods lose skills; and cut investment slows technology adoption.
Methods and their limits.
- 01
Productivity accounting
Decomposing output growth into inputs and efficiency. Results depend on how capital and quality are measured.
- 02
Firm-level analysis
Using enterprise surveys and administrative data. Informal firms are often missing.
- 03
Distributional analysis
Household surveys and tax data on income and consumption. Top incomes and informal earnings are under-recorded.
- 04
Impact evaluation
Testing programmes such as training or credit using causal inference. Results may not transfer between settings.
Productivity in services, public sectors and informal activity is particularly hard to measure, and estimates are revised often.
How it is studied, and what the methods cannot say.
- 01Economics and development economicsGrowth diagnostics · Structural transformation analysis · Distributional incidenceApplied here
- 02EconometricsShock transmission models · Panel analysis across countries · Nowcasting with alternative dataApplied here
- 03Causal inference and impact evaluationRandomised evaluations · Evaluating place-based policies · Regression discontinuityApplied here
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
What is labour productivity?
What is structural transformation?
Does productivity growth raise wages?
Does productivity growth always raise wages?
Why focus on small and informal firms?
Does the platform recommend specific programmes?
Is inequality bad for growth?
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