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

Peru: Statistical performance indicators (SPI): Pillar 4 data sources score was 63.26 scale 0-100 in 2024. ▲ Rising

Latest (2024)
63.26 scale 0-100
Change on year
up 3.0%
World rank
83rd
of 182 countries
All-time high
66.72 scale 0-100
in 2021
All-time low
45.89 scale 0-100
in 2020
Years of data
10
2015–2024

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

02040602015201920242015: 48.3 scale 0-1002016: 47.7 scale 0-1002017: 46.4 scale 0-1002018: 47 scale 0-1002019: 47 scale 0-1002020: 45.9 scale 0-1002021: 66.7 scale 0-1002022: 65.6 scale 0-1002023: 61.4 scale 0-1002024: 63.3 scale 0-100

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

Analysis

The most recent figure for statistical performance indicators (spi): pillar 4 data sources score in Peru is 63.26 scale 0-100, measured in 2024.

That represents a change of up 3.0% on the previous year and up 31.0% over ten years.

Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Peru peaked at 66.72 scale 0-100 in 2021 and was at its lowest, 45.89 scale 0-100, in 2020.

That places Peru 83rd out of 182 countries with data for 2024, putting it in the middle of the range.

Averages by decade

DecadeAverage LowestHighest Years
2010s 47.27 scale 0-100 46.42 scale 0-100 48.29 scale 0-100 5
2020s 60.58 scale 0-100 45.89 scale 0-100 66.72 scale 0-100 5

Countries ranked near Peru

  1. 80 Sri Lanka 64.07 scale 0-100 compare
  2. 81 Bahrain 63.94 scale 0-100 compare
  3. 82 Oman 63.66 scale 0-100 compare
  4. 84 Tunisia 63.21 scale 0-100 compare
  5. 85 Paraguay 62.7 scale 0-100 compare
  6. 86 Maldives 62.37 scale 0-100 compare

See the full ranking of 186 places →

More public sector data for Peru

All data for Peru →

Frequently asked questions

What is statistical performance indicators (spi): pillar 4 data sources score in Peru?
Statistical performance indicators (spi): pillar 4 data sources score in Peru was 63.26 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 Peru?
The highest recorded value was 66.72 scale 0-100 in 2021.
What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Peru?
The lowest recorded value was 45.89 scale 0-100 in 2020.
How does Peru rank for statistical performance indicators (spi): pillar 4 data sources score?
Peru ranks 83rd out of 182 countries with data for 2024.
Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Peru?
Over the last ten years it is up 31.0%. The long-run trend across the full record is rising.
Where does this Peru 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.