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

Luxembourg: Statistical performance indicators (SPI): Pillar 4 data sources score was 74.22 scale 0-100 in 2024. ▲ Rising

Latest (2024)
74.22 scale 0-100
Change on year
up 6.0%
World rank
53rd
of 182 countries
All-time high
74.22 scale 0-100
in 2024
All-time low
59.42 scale 0-100
in 2017
Years of data
9
2016–2024

Statistical performance indicators (SPI): Pillar 4 data sources score in Luxembourg, 2016–2024

0204060802016202020242016: 60.8 scale 0-1002017: 59.4 scale 0-1002018: 59.9 scale 0-1002019: 61.6 scale 0-1002020: 64.3 scale 0-1002021: 72.6 scale 0-1002022: 70 scale 0-1002023: 70 scale 0-1002024: 74.2 scale 0-100

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

Analysis

Luxembourg recorded 74.22 scale 0-100 for statistical performance indicators (spi): pillar 4 data sources score in 2024. That is the highest value across all 9 years on record.

The figure is up 6.0% on the previous year and up 22.1% over ten years.

Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Luxembourg peaked at 74.22 scale 0-100 in 2024 and was at its lowest, 59.42 scale 0-100, in 2017.

Luxembourg ranks 53rd of 182 countries on this measure, in the middle of the range.

Averages by decade

DecadeAverage LowestHighest Years
2010s 60.44 scale 0-100 59.42 scale 0-100 61.64 scale 0-100 4
2020s 70.23 scale 0-100 64.29 scale 0-100 74.22 scale 0-100 5

Countries ranked near Luxembourg

  1. 50 Cyprus 74.75 scale 0-100 compare
  2. 51 Albania 74.6 scale 0-100 compare
  3. 52 Panama 74.48 scale 0-100 compare
  4. 54 India 74.18 scale 0-100 compare
  5. 55 Egypt 73.33 scale 0-100 compare
  6. 56 Palestine 73.2 scale 0-100 compare

See the full ranking of 186 places →

More public sector data for Luxembourg

All data for Luxembourg →

Frequently asked questions

What is statistical performance indicators (spi): pillar 4 data sources score in Luxembourg?
Statistical performance indicators (spi): pillar 4 data sources score in Luxembourg was 74.22 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 Luxembourg?
The highest recorded value was 74.22 scale 0-100 in 2024.
What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Luxembourg?
The lowest recorded value was 59.42 scale 0-100 in 2017.
How does Luxembourg rank for statistical performance indicators (spi): pillar 4 data sources score?
Luxembourg ranks 53rd out of 182 countries with data for 2024.
Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Luxembourg?
Over the last ten years it is up 22.1%. The long-run trend across the full record is rising.
Where does this Luxembourg 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.