Statistical performance indicators (SPI): Pillar 4 data sources score in Paraguay

Paraguay: Statistical performance indicators (SPI): Pillar 4 data sources score was 62.7 scale 0-100 in 2024. ▲ Rising

Latest (2024)
62.7 scale 0-100
Change on year
up 2.4%
World rank
85th
of 182 countries
All-time high
62.7 scale 0-100
in 2024
All-time low
32.4 scale 0-100
in 2019
Years of data
10
2015–2024

Statistical performance indicators (SPI): Pillar 4 data sources score in Paraguay, 2015–2024

02040602015201920242015: 39.6 scale 0-1002016: 38.4 scale 0-1002017: 37.7 scale 0-1002018: 38.3 scale 0-1002019: 32.4 scale 0-1002020: 49.2 scale 0-1002021: 55.9 scale 0-1002022: 59.6 scale 0-1002023: 61.2 scale 0-1002024: 62.7 scale 0-100

Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.

Analysis

Paraguay recorded 62.7 scale 0-100 for statistical performance indicators (spi): pillar 4 data sources score in 2024. That is the highest value across all 10 years on record.

Compared with earlier readings it is up 2.4% on the previous year and up 58.4% over ten years.

Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Paraguay peaked at 62.7 scale 0-100 in 2024 and was at its lowest, 32.4 scale 0-100, in 2019.

Paraguay ranks 85th of 182 countries on this measure, in the middle of the range.

Averages by decade

DecadeAverage LowestHighest Years
2010s 37.28 scale 0-100 32.4 scale 0-100 39.59 scale 0-100 5
2020s 57.74 scale 0-100 49.25 scale 0-100 62.7 scale 0-100 5

Countries ranked near Paraguay

  1. 82 Oman 63.66 scale 0-100 compare
  2. 83 Peru 63.26 scale 0-100 compare
  3. 84 Tunisia 63.21 scale 0-100 compare
  4. 86 Maldives 62.37 scale 0-100 compare
  5. 87 Kuwait 62.32 scale 0-100 compare
  6. 88 Morocco 61.87 scale 0-100 compare

See the full ranking of 186 places →

More public sector data for Paraguay

All data for Paraguay →

Frequently asked questions

What is statistical performance indicators (spi): pillar 4 data sources score in Paraguay?
Statistical performance indicators (spi): pillar 4 data sources score in Paraguay was 62.7 scale 0-100 in 2024, according to Statistical Performance Indicators, World Bank (WB).
What is the highest statistical performance indicators (spi): pillar 4 data sources score recorded in Paraguay?
The highest recorded value was 62.7 scale 0-100 in 2024.
What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Paraguay?
The lowest recorded value was 32.4 scale 0-100 in 2019.
How does Paraguay rank for statistical performance indicators (spi): pillar 4 data sources score?
Paraguay ranks 85th out of 182 countries with data for 2024.
Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Paraguay?
Over the last ten years it is up 58.4%. The long-run trend across the full record is rising.
Where does this Paraguay data come from?
The figures come from Statistical Performance Indicators, World Bank (WB), published as part of Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100). Statizoid updates them automatically from the source API.

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About this data

Indicator
Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100)
Unit
scale 0-100
Source
Statistical Performance Indicators, World Bank (WB)
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
186 places, 1,766 data points, 2015–2024
Last refreshed

The data sources overall score is a composite measure of whether countries have data available from the following sources: Censuses and surveys, administrative data, geospatial data, and private sector/citizen generated data. The data sources (input) pillar is segmented by four types of sources generated by (i) the statistical office (censuses and surveys), and sources accessed from elsewhere such as (ii) administrative data, (iii) geospatial data, and (iv) private sector data and citizen generated data. The appropriate balance between these source types will vary depending on a country's institutional setting and the maturity of its statistical system. High scores should reflect the extent to which the sources being utilized enable the necessary statistical indicators to be generated. For example, a low score on environment statistics (in the data production pillar) may reflect a lack of use of (and low score for) geospatial data (in the data sources pillar). This type of linkage is inherent in the data cycle approach and can help highlight areas for investment required if country needs are to be met.