Statistical performance indicators (SPI): Pillar 4 data sources score in Nepal
Nepal: Statistical performance indicators (SPI): Pillar 4 data sources score was 46.5 scale 0-100 in 2024. ▼ Falling
Statistical performance indicators (SPI): Pillar 4 data sources score in Nepal, 2015–2024
Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.
Analysis
The most recent figure for statistical performance indicators (spi): pillar 4 data sources score in Nepal is 46.5 scale 0-100, measured in 2024.
That represents a change of up 1.5% on the previous year and down 11.0% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Nepal peaked at 52.23 scale 0-100 in 2015 and was at its lowest, 44.1 scale 0-100, in 2022.
That places Nepal 125th out of 182 countries with data for 2024, putting it in the middle of the range.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 47.09 scale 0-100 | 44.23 scale 0-100 | 52.23 scale 0-100 | 5 |
| 2020s | 45.34 scale 0-100 | 44.1 scale 0-100 | 46.5 scale 0-100 | 5 |
Countries ranked near Nepal
- 122 Lebanon 48.12 scale 0-100 compare
- 123 Bhutan 47.75 scale 0-100 compare
- 124 Cambodia 46.58 scale 0-100 compare
- 126 Dominican Republic 46.17 scale 0-100 compare
- 128 Mozambique 45.78 scale 0-100 compare
More public sector data for Nepal
- Arms imports 0 SIPRI trend indicator values (2021)
- Tax revenue 13.9% (2023)
- Taxes on income, profits and capital gains 26.7% (2023)
- Taxes on goods and services 38.0% (2023)
- Net investment in nonfinancial assets 4.4% (2023)
- Net lending (+) / net borrowing (-) -5.9% (2023)
- Interest payments 8.0% (2023)
- Grants and other revenue 17.8% (2023)
- Interest payments 4.1% (2021)
- Other taxes 1.0% (2023)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 4 data sources score in Nepal?
- Statistical performance indicators (spi): pillar 4 data sources score in Nepal was 46.5 scale 0-100 in 2024, according to Statistical Performance Indicators, World Bank (WB).
- What is the highest statistical performance indicators (spi): pillar 4 data sources score recorded in Nepal?
- The highest recorded value was 52.23 scale 0-100 in 2015.
- What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Nepal?
- The lowest recorded value was 44.1 scale 0-100 in 2022.
- How does Nepal rank for statistical performance indicators (spi): pillar 4 data sources score?
- Nepal ranks 125th out of 182 countries with data for 2024.
- Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Nepal?
- Over the last ten years it is down 11.0%. The long-run trend across the full record is falling.
- Where does this Nepal data come from?
- The figures come from Statistical Performance Indicators, World Bank (WB), published as part of Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100). Statizoid updates them automatically from the source API.
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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.