World Bank · Public Sector

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

95.88ordinal scale (0-100) · 2024

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. Annual figures for Singapore from 2016 to 2024.

20162024

Every year

YearValue (ordinal scale (0-100))Note
202495.875
202394.175
202294.175
202186.542
202078.208
201973.383
201871.683
201767.083
201662.408

Source

Published by World Bank, produced by World Bank. Licence: CC BY 4.0. Retrieved 2026-11-07.

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World Bank (2026). Statistical performance indicators (SPI): Pillar 4 data sources score. Interva. https://interva.co/dataset/worldbank-statistical-performance-indicators-spi-pillar-4-data-sources (accessed 2026-11-08). catalog snapshot 2026-11-07.

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Singapore: Statistical performance indicators (SPI): Pillar 4 data sources score (2016–2024) · Interva