Statistical performance indicators (SPI): Pillar 5 data infrastructure in Upper middle income
Upper middle income: Statistical performance indicators (SPI): Pillar 5 data infrastructure was 66.63 scale 0-100 in 2024. ▲ Rising
Statistical performance indicators (SPI): Pillar 5 data infrastructure in Upper middle income, 2016–2024
Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.
Analysis
In 2024, statistical performance indicators (spi): pillar 5 data infrastructure in Upper middle income stood at 66.63 scale 0-100. That is the highest value across all 9 years on record.
Compared with earlier readings it is up 2.5% on the previous year and up 46.5% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 5 data infrastructure in Upper middle income peaked at 66.63 scale 0-100 in 2024 and was at its lowest, 45.49 scale 0-100, in 2016.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 48.03 scale 0-100 | 45.49 scale 0-100 | 51.83 scale 0-100 | 4 |
| 2020s | 61.36 scale 0-100 | 53.37 scale 0-100 | 66.63 scale 0-100 | 5 |
Countries ranked near Upper middle income
- 1 Australia 100 scale 0-100 compare
- 1 New Zealand 100 scale 0-100 compare
- 1 Norway 100 scale 0-100 compare
- 1 Russia 100 scale 0-100 compare
- 1 Turkey 100 scale 0-100 compare
- 6 Albania 95 scale 0-100 compare
- 6 Chile 95 scale 0-100 compare
- 6 Costa Rica 95 scale 0-100 compare
- 6 Israel 95 scale 0-100 compare
- 6 Japan 95 scale 0-100 compare
- 6 South Korea 95 scale 0-100 compare
- 6 North Macedonia 95 scale 0-100 compare
More public sector data for Upper middle income
- Arms imports 8.06 billion SIPRI trend indicator values (2024)
- Tax revenue 10.4% (2024)
- Taxes on income, profits and capital gains 25.4% (2024)
- Taxes on goods and services 33.6% (2024)
- Interest payments 10.4% (2024)
- Grants and other revenue 16.4% (2024)
- Interest payments 8.8% (2023)
- Other taxes 0.9% (2024)
- Compensation of employees 20.9% (2023)
- Goods and services expense 13.9% (2023)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 5 data infrastructure in Upper middle income?
- Statistical performance indicators (spi): pillar 5 data infrastructure in Upper middle income was 66.63 scale 0-100 in 2024, according to Statistical Performance Indicators, World Bank (WB).
- What is the highest statistical performance indicators (spi): pillar 5 data infrastructure recorded in Upper middle income?
- The highest recorded value was 66.63 scale 0-100 in 2024.
- What is the lowest statistical performance indicators (spi): pillar 5 data infrastructure recorded in Upper middle income?
- The lowest recorded value was 45.49 scale 0-100 in 2016.
- How does Upper middle income rank for statistical performance indicators (spi): pillar 5 data infrastructure?
- Upper middle income ranks 3rd out of 5 groups with data for 2024.
- Is statistical performance indicators (spi): pillar 5 data infrastructure rising or falling in Upper middle income?
- Over the last ten years it is up 46.5%. The long-run trend across the full record is rising.
- Where does this Upper middle income data come from?
- The figures come from Statistical Performance Indicators, World Bank (WB), published as part of Statistical performance indicators (SPI): Pillar 5 data infrastructure score (scale 0-100). Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 9 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
About this data
The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.