Guinea-Bissau vs Micronesia (country): Statistical performance indicators (SPI): Pillar 4 data sources score

Guinea-Bissau
19.92 scale 0-100
in 2024
Micronesia (country)
22.1 scale 0-100
in 2024
Guinea-Bissau rank
172nd
Micronesia (country) rank
169th

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

  • Guinea-Bissau
  • Micronesia (country)
0102030201520192024

How they compare

Micronesia (country) currently reports 22.1 scale 0-100 against 19.92 scale 0-100 in Guinea-Bissau, a difference of 2.18 scale 0-100.

That makes Micronesia (country)'s figure about 1.1 times Guinea-Bissau's.

Across all 10 years both countries report, Micronesia (country) has been ahead every year.

Globally, Guinea-Bissau ranks 172nd and Micronesia (country) ranks 169th of 182 countries.

Individual pages

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.