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

Mauritius: Statistical performance indicators (SPI): Pillar 4 data sources score was 67.33 scale 0-100 in 2024. ▲ Rising

Latest (2024)
67.33 scale 0-100
Change on year
up 4.6%
World rank
75th
of 182 countries
All-time high
68.12 scale 0-100
in 2021
All-time low
59.64 scale 0-100
in 2019
Years of data
10
2015–2024

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

02040602015201920242015: 64.1 scale 0-1002016: 62.2 scale 0-1002017: 61 scale 0-1002018: 61.3 scale 0-1002019: 59.6 scale 0-1002020: 59.8 scale 0-1002021: 68.1 scale 0-1002022: 62.7 scale 0-1002023: 64.3 scale 0-1002024: 67.3 scale 0-100

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

Analysis

In 2024, statistical performance indicators (spi): pillar 4 data sources score in Mauritius stood at 67.33 scale 0-100.

The figure is up 4.6% on the previous year and up 5.0% over ten years.

Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Mauritius peaked at 68.12 scale 0-100 in 2021 and was at its lowest, 59.64 scale 0-100, in 2019.

Mauritius ranks 75th of 182 countries on this measure, in the middle of the range.

Averages by decade

DecadeAverage LowestHighest Years
2010s 61.67 scale 0-100 59.64 scale 0-100 64.14 scale 0-100 5
2020s 64.46 scale 0-100 59.79 scale 0-100 68.12 scale 0-100 5

Countries ranked near Mauritius

  1. 72 Moldova 67.91 scale 0-100 compare
  2. 73 Cape Verde 67.9 scale 0-100 compare
  3. 74 Thailand 67.53 scale 0-100 compare
  4. 76 Botswana 67.25 scale 0-100 compare
  5. 77 Bangladesh 66.67 scale 0-100 compare
  6. 78 Azerbaijan 66.33 scale 0-100 compare

See the full ranking of 186 places →

More public sector data for Mauritius

All data for Mauritius →

Frequently asked questions

What is statistical performance indicators (spi): pillar 4 data sources score in Mauritius?
Statistical performance indicators (spi): pillar 4 data sources score in Mauritius was 67.33 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 Mauritius?
The highest recorded value was 68.12 scale 0-100 in 2021.
What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Mauritius?
The lowest recorded value was 59.64 scale 0-100 in 2019.
How does Mauritius rank for statistical performance indicators (spi): pillar 4 data sources score?
Mauritius ranks 75th out of 182 countries with data for 2024.
Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Mauritius?
Over the last ten years it is up 5.0%. The long-run trend across the full record is rising.
Where does this Mauritius 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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CSV · JSON — 10 observations, free to reuse under CC BY 4.0 (World Bank Open Data).

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.