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

Philippines: Statistical performance indicators (SPI): Pillar 4 data sources score was 71.98 scale 0-100 in 2024. ▼ Falling

Latest (2024)
71.98 scale 0-100
Change on year
up 1.9%
World rank
59th
of 182 countries
All-time high
85.3 scale 0-100
in 2015
All-time low
70.61 scale 0-100
in 2023
Years of data
10
2015–2024

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

0204060802015201920242015: 85.3 scale 0-1002016: 83 scale 0-1002017: 80.2 scale 0-1002018: 80.2 scale 0-1002019: 78.5 scale 0-1002020: 83.5 scale 0-1002021: 71 scale 0-1002022: 74.8 scale 0-1002023: 70.6 scale 0-1002024: 72 scale 0-100

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

Analysis

Philippines recorded 71.98 scale 0-100 for statistical performance indicators (spi): pillar 4 data sources score in 2024.

Compared with earlier readings it is up 1.9% on the previous year and down 15.6% over ten years.

Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Philippines peaked at 85.3 scale 0-100 in 2015 and was at its lowest, 70.61 scale 0-100, in 2023.

Philippines ranks 59th of 182 countries on this measure, in the middle of the range.

Averages by decade

DecadeAverage LowestHighest Years
2010s 81.42 scale 0-100 78.53 scale 0-100 85.3 scale 0-100 5
2020s 74.38 scale 0-100 70.61 scale 0-100 83.53 scale 0-100 5

Countries ranked near Philippines

  1. 56 Palestine 73.2 scale 0-100 compare
  2. 57 Argentina 72.92 scale 0-100 compare
  3. 58 Turkey 71.99 scale 0-100 compare
  4. 60 Armenia 71.93 scale 0-100 compare
  5. 61 Jordan 71.7 scale 0-100 compare
  6. 62 South Africa 71.25 scale 0-100 compare

See the full ranking of 186 places →

More public sector data for Philippines

All data for Philippines →

Frequently asked questions

What is statistical performance indicators (spi): pillar 4 data sources score in Philippines?
Statistical performance indicators (spi): pillar 4 data sources score in Philippines was 71.98 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 Philippines?
The highest recorded value was 85.3 scale 0-100 in 2015.
What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Philippines?
The lowest recorded value was 70.61 scale 0-100 in 2023.
How does Philippines rank for statistical performance indicators (spi): pillar 4 data sources score?
Philippines ranks 59th out of 182 countries with data for 2024.
Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Philippines?
Over the last ten years it is down 15.6%. The long-run trend across the full record is falling.
Where does this Philippines 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.