One reference country, up to three others
Countries side by side
A country score only means something against other countries. This page puts a reference country beside up to three others on the same nine axes, then follows every row down to the indicator it was built from.
The first country is the reference: it keeps the filled shape and every other column is read as a distance from it. The selection lives in the address, so /compare/BRA-IDN-ZAF is a comparison you can send to somebody. There is still no composite score and no ranking.
Countries in this comparison
Each shape against the reference
The reference country is drawn as an outline behind every other card, so each card answers the same question: where does this country leave the reference. The nine axes are in the same order on every chart.
- Usable or good evidence
- Thin evidence, hollow point. The dashes open further as confidence falls.
- The point still sits at the score, because confidence never moves it.
0 to 100 is a position inside the frame every country builds together. Zero is the weakest on a dimension and 100 is the strongest. A score of 10 puts a country near the floor of that frame. It does not mean 10 percent of a capability.
Nine capabilities, one row each
Scores run 0 to 100 against all countries in the comparison frame, so a gap of 10 points means the same thing on every row. The number under each score is the distance from the reference.
- weak0 to 25
- below middle25 to 50
- above middle50 to 75
- strong75 and above
| Capability | Brazilreference | Argentina |
|---|---|---|
| Anticipation | 37.3 | 34.4-2.9 |
| Agency | 59.6 | 50.1-9.5 |
| Coordination | 84.4 | 58.1-26.3 |
| Trust | 26.9 | 29.2+2.3 |
| Learning | 43.2 | 54.9+11.7 |
| Experimentation | 30.0 | 21.5-8.5 |
| Adaptability | 56.8 | 50.8-6.0 |
| Building | 25.3 | 26.6+1.3 |
| Shared Purpose | 34.9 | 39.2+4.3 |
Confidence stays a second number
Confidence is coverage times recency times source quality. It never enters the score above, and a country can lead a row on a thinner evidence base than the country beside it.
- very thin0.00 to 0.25
- thin0.25 to 0.45
- usable0.45 to 0.65
- good0.65 and above
- very thin: The score rests on one or two indicators. Do not quote it on its own.
- thin: A minority of indicators, or evidence old enough to have moved. Read with care.
- usable: Enough evidence to compare countries, with known holes.
- good: Most indicators observed, recent, from official or intergovernmental sources.
Where each country is heading
A trend is measured on the indicators observed at both ends of the span, which is a smaller basket than the score. The basket size is printed beside each change, and two countries can be on different baskets in the same row.
Every indicator behind those rows
The chip is the indicator normalized onto the 0 to 100 frame, so higher is better on every row whatever the unit does. The published value and its year sit under it. A row with no dataset is a declared gap and lowers confidence for every country at once.
Anticipation
How capable is the country of identifying and preparing for emerging change?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| R&D expenditure | % of GDP | 18.71.194 (2023) | 9.40.601 (2023) |
| Researchers in R&D | per million people | 9.5903.201 (2014) | 13.81,312.753 (2023) |
| Scientific articles | articles per million people | 10.858,292.04 (2023) | 7.48,589.35 (2023) |
| Statistical performance | index 0-100 | 80.882.308 (2024) | 77.280.391 (2024) |
| Secure internet servers | per million people | 66.66,941.174 (2024) | 64.35,453.434 (2024) |
| Government foresight capacity | index 0-100 | no dataset | no dataset |
| Long-horizon research share | % of R&D | no dataset | no dataset |
Agency
How able are individuals and organizations to turn an intention into action?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| New business density | per 1,000 aged 15-64 | 31.86.667 (2024) | 2.20.525 (2024) |
| Time to start a business | days | 75.116.62 (2019) | 83.511.5 (2019) |
| Procedures to start a business | count | 52.210.61 (2019) | 44.412 (2019) |
| Individuals using the internet | % of population | 80.184.463 (2024) | 86.889.667 (2024) |
| Financial account ownership | % aged 15+ | 82.486.381 (2024) | 76.381.744 (2024) |
| Credit to the private sector | % of GDP | 36.375.103 (2025) | 7.317.598 (2025) |
| Adult digital skills | % of adults | no dataset | no dataset |
| Perceived control over life | mean 1-10 | no dataset | no dataset |
Coordination
How effectively can independent actors organize around shared objectives?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Government effectiveness | z-score -2.5 to 2.5 | retired | retired |
| Regulatory quality | z-score -2.5 to 2.5 | retired | retired |
| Logistics performance | index 1-5 | retired | retired |
| Border compliance time to export | hours | 70.649.043 (2019) | 87.421 (2019) |
| Budget execution fidelity | percentage points from approved budget | 98.2100.828 (2021) | 28.9128.209 (2021) |
| University-industry collaboration | index 0-100 | no dataset | no dataset |
| Civil society strength | index 0-1 | no dataset | no dataset |
| Public-private collaboration | index 0-100 | no dataset | no dataset |
Trust
How much cooperation is possible beyond immediate personal networks?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Rule of law | z-score -2.5 to 2.5 | retired | retired |
| Control of corruption | z-score -2.5 to 2.5 | retired | retired |
| Time to enforce a contract | days | 50.3801.2 (2019) | 35.1995 (2019) |
| Intentional homicide rate | per 100,000 people | retired | retired |
| Generalised interpersonal trust | % agreeing | 3.66.5 (2022) | 23.419.2 (2022) |
| Trust in public institutions | % expressing confidence | no dataset | no dataset |
| Cooperation beyond the in-group | % expressing trust | no dataset | no dataset |
| Court case clearance rate | % of incoming cases | no dataset | no dataset |
Learning
How effectively does the country acquire, distribute, and update knowledge?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Human Capital Index | index 0-1 | 36.80.551 (2020) | 46.60.602 (2020) |
| Tertiary enrolment | % gross | 60.269.732 (2024) | 96.2107.823 (2023) |
| Public education expenditure | % of GDP | 65.35.619 (2022) | 57.75.003 (2023) |
| Vocational share of secondary | % of secondary | 6.94.41 (2018) | 25.316.191 (1998) |
| Firms offering formal training | % of firms | 46.738.519 (2025) | 48.940.196 (2017) |
| Adult learning participation | % of adults | no dataset | no dataset |
| Research citation impact | ratio to world average | no dataset | no dataset |
Experimentation
How easily can new approaches be attempted, tested, abandoned, and improved?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Resident patent applications | per million people | 4.94,666 (2021) | 2.0406 (2021) |
| Resident trademark applications | per million people | 24.8346,752 (2021) | 23.370,131 (2021) |
| Venture capital investment | % of GDP | no dataset | no dataset |
| Early-stage entrepreneurial activity | % aged 18-64 | 50.719.4 (2025) | 60.621.4 (2025) |
| Tolerance of entrepreneurial failure | % not deterred | 39.651.8 (2025) | 0.037.9 (2025) |
| Regulatory sandbox activity | count | no dataset | no dataset |
| University spinouts | per million people | no dataset | no dataset |
| Business share of R&D | % of R&D | no dataset | no dataset |
Adaptability
How effectively can the system respond when circumstances change?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Labour force participation | % aged 15+ | 49.871.049 (2025) | 48.570.691 (2025) |
| Unemployment rate | % of labour force | 72.15.97 (2025) | 65.87.145 (2025) |
| Long-term unemployment share | % of unemployed | no dataset | no dataset |
| Fixed broadband subscriptions | per 100 people | 49.124.079 (2024) | 53.326.098 (2024) |
| Electricity transmission losses | % of output | 56.114.972 (2024) | 35.721.836 (2024) |
| Export diversification | index 0-1 | no dataset | no dataset |
| Disaster preparedness and recovery | index 0-100 | no dataset | no dataset |
| Institutional responsiveness | index 0-100 | no dataset | no dataset |
Building
How capable is the country of turning plans and knowledge into functioning systems?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Manufacturing value added | % of GDP | 34.711.772 (2025) | 40.013.584 (2025) |
| High-technology exports | % of manufactured exports | 17.411.11 (2024) | 5.43.85 (2024) |
| Output per worker | constant 2021 PPP $ | 13.841,840.01 (2025) | 21.561,326.291 (2025) |
| Logistics infrastructure quality | index 1-5 | retired | retired |
| Electricity connection speed | score 0-100 | 41.851.961 (2019) | 61.167.826 (2019) |
| Economic fitness | index | 18.71.757 (2024) | 4.80.455 (2024) |
| Large project delivery | % overrun | no dataset | no dataset |
| Firm scale-up rate | % of firms | no dataset | no dataset |
Shared Purpose
To what extent can people imagine themselves as participants in a common project?
| Indicator | Unit | Brazilreference | Argentina |
|---|---|---|---|
| Voice and accountability | z-score -2.5 to 2.5 | retired | retired |
| Tax revenue | % of GDP | 55.515.41 (2024) | 36.810.429 (2024) |
| Income inequality | Gini 0-100 | 14.250.3 (2024) | 41.542.4 (2024) |
| Sense of national belonging | % expressing belonging | no dataset | no dataset |
| Volunteering | % of adults | no dataset | no dataset |
| Political polarisation | index 0-4 | no dataset | no dataset |
| Civic participation | % of adults | no dataset | no dataset |