Pakistan: Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100)

Key figures

Over five years it is up 23.9% from 40.77 in 2019 (4.38% a year on average, compounded). Since 2015 it is up 30.18% from 38.8 in 2015 (2.97% a year on average, compounded).

What the numbers say

In 2024, Pakistan's statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100) fell 0.9 on 2023 (from 51.41 to 50.51).

Across the 8 yearly changes before that (2016 to 2023), the average change was +1.58 and a typical year strayed about 2.31 from that (the standard deviation). This year's change was 1.1 standard deviations below that average, so it was larger than a typical year, though not out of the range seen before.

On record, the biggest yearly rise was 5.82 in 2021 and the biggest yearly fall was 0.9 in 2024. The numbers show how large and when, not why; for the cause, look at what happened in that country in those years.

From 2015 to 2024 the straight-line trend is upward, about 1.5 a year. A straight line explains 81% of the movement over 10 observed years.

Worked out from the yearly values above. How the checks work: standard deviation, z-scores and straight-line trends.

How it compares

In 2024, Pakistan had the 63rd highest value of the 123 economies reporting that year. Higher is not always better: for some indicators the lowest value is the one to aim for. See the full ranking.

Closest to Pakistan in the 2024 ranking

• Bosnia and Herzegovina — 60th of 123: 53.43
• Tanzania — 61st of 123: 52.95
• Samoa — 62nd of 123: 50.64
• Malawi — 64th of 123: 49.38
• Benin — 65th of 123: 49.31
• Burkina Faso — 66th of 123: 49.23

What this measures

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.

Limitations: In the data sources pillar, more information is needed in the areas of administrative data, geospatial data, and private and citizen generated data. On administrative data, the picture is incomplete with no measures of whether countries have administrative data systems in place to measure health, education, labor, and social protection program statistics. For the geospatial indicator, there is a proxy measure of whether the country is able to produce indicators at the sub-national level, but as yet, no understanding of how countries are using geospatial information in other ways, for instance using satellite data.

Regional and income-group figures are computed by the World Bank as a weighted average.

All 10 values

Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100) in nearby economies

• Afghanistan — 20.68 (2024)
• Algeria — 44.3 (2024)
• Djibouti — 16.57 (2024)
• Egypt, Arab Rep. — 73.33 (2024)
• Iran, Islamic Rep. — 69.9 (2024)
• Jordan — 71.7 (2024)
• Lebanon — 48.13 (2024)
• Morocco — 61.87 (2024)

More public sector data for Pakistan

• Arms imports (SIPRI trend indicator values) — 706 million (2025)
• Military expenditure (current USD) — 11.87 billion (2025)
• Military expenditure (current LCU) — 3.34 trillion (2025)
• Military expenditure (% of GDP) — 2.91% (2025)
• Battle-related deaths (number of people) — 1,534 (2024)
• Armed forces personnel, total — 943,000 (2020)
• Military expenditure (% of general government expenditure) — 13.83% (2025)
• Armed forces personnel (% of total labor force) — 1.25% (2020)
• Intentional homicides (per 100,000 people) — 4.33 (2023)
• Arms exports (SIPRI trend indicator values)

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Questions people ask

What is Pakistan's statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100)?

50.51 in 2024, according to the World Bank (World Development Indicators).

How has it changed since 2015?

It is up 30.18% from 38.8 in 2015 (2.97% a year on average, compounded). The highest value was 51.41 in 2022 and the lowest 38.8 in 2015.

How does Pakistan rank?

63rd highest of 123 economies with data for 2024.

Is the latest change in statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100) unusual for Pakistan?

In 2024, Pakistan's statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100) fell 0.9 on 2023 (from 51.41 to 50.51). Across the 8 yearly changes before that (2016 to 2023), the average change was +1.58 and a typical year strayed about 2.31 from that (the standard deviation). This year's change was 1.1 standard deviations below that average, so it was larger than a typical year, though not out of the range seen before.

Source

World Bank, World Development Indicators, indicator IQ.SPI.PIL4, licensed CC BY 4.0. Original source: Statistical Performance Indicators, World Bank (WB), uri: https://datacatalog.worldbank.org/dataset/statistical-performance-indicators Figures are fetched from the World Bank API and refreshed monthly; see the series on data.worldbank.org. The full definition and method are in the World Bank's metadata glossary. Comparisons use the same World Bank release.

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