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

Croatia: Statistical performance indicators (SPI): Pillar 4 data sources score was 75.95 scale 0-100 in 2024. ▲ Rising

Latest (2024)
75.95 scale 0-100
Change on year
down 1.1%
World rank
49th
of 182 countries
All-time high
76.83 scale 0-100
in 2022
All-time low
63.87 scale 0-100
in 2017
Years of data
9
2016–2024

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

0204060802016202020242016: 67.3 scale 0-1002017: 63.9 scale 0-1002018: 64.2 scale 0-1002019: 65.9 scale 0-1002020: 67.6 scale 0-1002021: 76 scale 0-1002022: 76.8 scale 0-1002023: 76.8 scale 0-1002024: 76 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 Croatia is 75.95 scale 0-100, measured in 2024.

The figure is down 1.1% on the previous year and up 12.8% over ten years.

Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Croatia peaked at 76.83 scale 0-100 in 2022 and was at its lowest, 63.87 scale 0-100, in 2017.

That places Croatia 49th out of 182 countries with data for 2024, putting it in the middle of the range.

Averages by decade

DecadeAverage LowestHighest Years
2010s 65.33 scale 0-100 63.87 scale 0-100 67.32 scale 0-100 4
2020s 74.63 scale 0-100 67.62 scale 0-100 76.83 scale 0-100 5

Countries ranked near Croatia

  1. 46 United Kingdom 77.62 scale 0-100 compare
  2. 47 Belarus 77.1 scale 0-100 compare
  3. 48 Latvia 76.8 scale 0-100 compare
  4. 50 Cyprus 74.75 scale 0-100 compare
  5. 51 Albania 74.6 scale 0-100 compare
  6. 52 Panama 74.48 scale 0-100 compare

See the full ranking of 186 places →

More public sector data for Croatia

All data for Croatia →

Frequently asked questions

What is statistical performance indicators (spi): pillar 4 data sources score in Croatia?
Statistical performance indicators (spi): pillar 4 data sources score in Croatia was 75.95 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 Croatia?
The highest recorded value was 76.83 scale 0-100 in 2022.
What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Croatia?
The lowest recorded value was 63.87 scale 0-100 in 2017.
How does Croatia rank for statistical performance indicators (spi): pillar 4 data sources score?
Croatia ranks 49th out of 182 countries with data for 2024.
Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Croatia?
Over the last ten years it is up 12.8%. The long-run trend across the full record is rising.
Where does this Croatia 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.