Lower middle income vs Poland: Statistical performance indicators (SPI): Pillar 4 data sources score
Statistical performance indicators (SPI): Pillar 4 data sources score over time
- Lower middle income
- Poland
How they compare
Poland currently reports 94.33 scale 0-100 against 49.13 scale 0-100 in Lower middle income, a difference of 45.2 scale 0-100.
That makes Poland's figure about 1.9 times Lower middle income's.
Across all 9 years both countries report, Poland has been ahead every year.
Lower middle income ranks 3rd and Poland ranks 2nd of 4 groups.
Poland has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Lower middle income | Poland | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 43.34 scale 0-100 | 79.68 scale 0-100 | 36.34 scale 0-100 | Poland |
| 2020s | 47.9 scale 0-100 | 89.7 scale 0-100 | 41.8 scale 0-100 | Poland |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 4 data sources score, Lower middle income or Poland?
- Poland, at 94.33 scale 0-100 against 49.13 scale 0-100 in Lower middle income as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 4 data sources score between Lower middle income and Poland?
- 45.2 scale 0-100, with Poland ahead.
- How many years of comparable data are there for Lower middle income and Poland?
- 9 years are reported by both, from 2016 to 2024.
- How do Lower middle income and Poland rank globally for statistical performance indicators (spi): pillar 4 data sources score?
- Lower middle income ranks 3rd and Poland ranks 2nd of 4 groups.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
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About this data
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.