San Marino vs Palestine: Statistical performance indicators (SPI): Pillar 1 data use score

San Marino
70 scale 0-100
in 2024
Palestine
70 scale 0-100
in 2024
San Marino rank
126th
Palestine rank
126th

Statistical performance indicators (SPI): Pillar 1 data use score over time

  • San Marino
  • Palestine
020406080200420142024

How they compare

San Marino currently reports 70 scale 0-100 against 70 scale 0-100 in Palestine, a difference of 0 scale 0-100.

Across all 21 years both countries report, Palestine has been ahead every year.

San Marino ranks 126th and Palestine ranks 126th of 216 countries.

Palestine has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade San Marino Palestine Difference Ahead
2000s 0 scale 0-100 36.67 scale 0-100 36.67 scale 0-100 Palestine
2010s 23 scale 0-100 53 scale 0-100 30 scale 0-100 Palestine
2020s 54 scale 0-100 68 scale 0-100 14 scale 0-100 Palestine

Averages of every year both report within each decade.

Frequently asked questions

Which has higher statistical performance indicators (spi): pillar 1 data use score, San Marino or Palestine?
San Marino, at 70 scale 0-100 against 70 scale 0-100 in Palestine as of 2024.
What is the difference in statistical performance indicators (spi): pillar 1 data use score between San Marino and Palestine?
0 scale 0-100, with San Marino ahead.
How many years of comparable data are there for San Marino and Palestine?
21 years are reported by both, from 2004 to 2024.
How do San Marino and Palestine rank globally for statistical performance indicators (spi): pillar 1 data use score?
San Marino ranks 126th and Palestine ranks 126th of 216 countries.
Where does this data come from?
Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 1 data use score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

San Marino vs Palestine: Statistical performance indicators (SPI): Pillar 1 data use score. Statizoid, drawing on Statistical Performance Indicators, World Bank (WB). Retrieved 02 September 2026, from https://public-sector.statizoid.com/compare/statistical-performance-indicators-spi-pillar-1-data-use-score-scale-0-100/san-marino/west-bank-and-gaza/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY 4.0 (World Bank Open Data); please keep the attribution.

<a href="https://public-sector.statizoid.com/compare/statistical-performance-indicators-spi-pillar-1-data-use-score-scale-0-100/san-marino/west-bank-and-gaza/">San Marino vs Palestine: Statistical performance indicators (SPI): Pillar 1 data use score</a> — Statizoid

About this data

Indicator
Statistical performance indicators (SPI): Pillar 1 data use 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
221 places, 4,593 data points, 2004–2024
Last refreshed

The data use overall score is a composite score measuring the demand side of the statistical system. The data use pillar is segmented by five types of users: (i) the legislature, (ii) the executive branch, (iii) civil society (including sub-national actors), (iv) academia and (v) international bodies. Each dimension would have associated indicators to measure performance. A mature system would score well across all dimensions whereas a less mature one would have weaker scores along certain dimensions. The gaps would give insights into prioritization among user groups and help answer questions as to why the existing services are not resulting in higher use of national statistics in a particular segment. Currently, the SPI only features indicators for one of the five dimensions of data use, which is data use by international organizations. Indicators on whether statistical systems are providing useful data to their national governments (legislature and executive branches), to civil society, and to academia are absent. Thus the dashboard does not yet assess if national statistical systems are meeting the data needs of a large swathe of users.