Use of interpolation and extrapolation on original Gini coefficient data in India
India: Use of interpolation and extrapolation on original Gini coefficient data was 6,449 in 2017. ◆ Volatile
Use of interpolation and extrapolation on original Gini coefficient data in India, 1820–2017
Source: Various sources (2020) – processed by Our World in Data.
Analysis
In 2017, use of interpolation and extrapolation on original gini coefficient data in India stood at 6,449. That is the highest value across all 15 years on record.
That represents a change of up 89.8% over ten years.
Over the whole period, use of interpolation and extrapolation on original gini coefficient data in India peaked at 6,449 in 2017 and was at its lowest, 850, in 1870.
That places India 107th out of 160 countries with data for 2017, putting it in the middle of the range.
The series is highly variable year to year, so single readings are best treated with caution.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1820s | 935.34 | 935.34 | 935.34 | 1 |
| 1850s | 947 | 947 | 947 | 1 |
| 1870s | 850 | 850 | 850 | 1 |
| 1890s | 931 | 931 | 931 | 1 |
| 1910s | 1,111 | 1,111 | 1,111 | 1 |
| 1920s | 1,160 | 1,160 | 1,160 | 1 |
| 1950s | 987 | 987 | 987 | 1 |
| 1960s | 1,200 | 1,200 | 1,200 | 1 |
| 1970s | 1,384 | 1,384 | 1,384 | 1 |
| 1980s | 1,495 | 1,495 | 1,495 | 1 |
| 1990s | 2,087 | 2,087 | 2,087 | 1 |
| 2000s | 3,075 | 2,753 | 3,397 | 2 |
| 2010s | 5,488 | 4,526 | 6,449 | 2 |
Countries ranked near India
More poverty & inequality data for India
- Number of income/consumption surveys in the past decade available via the World Bank 1 surveys (2025)
- Fertility rate vs. share living in extreme poverty 1.98 live births per woman (2023)
- Cereal yield vs. share in extreme poverty 3,632 kg per hectare (2024)
- Tax revenue as share of GDP vs. income inequality 17.3% (2023)
- Gender Inequality Index 0.403 (2023)
- Share of government consumption in GDP vs. share of population living in extreme poverty 7.4% (2023)
- Lifespan inequality: Gini coefficient in women 0.1281 (2023)
- Lifespan inequality: Gini coefficient by sex 0.1281 (2023)
- Lifespan inequality: Gini coefficient in men 0.1407 (2023)
- Income inequality: Atkinson index 0.3736 (2023)
Frequently asked questions
- What is use of interpolation and extrapolation on original gini coefficient data in India?
- Use of interpolation and extrapolation on original gini coefficient data in India was 6,449 in 2017, according to Various sources (2020) – processed by Our World in Data.
- What is the highest use of interpolation and extrapolation on original gini coefficient data recorded in India?
- The highest recorded value was 6,449 in 2017.
- What is the lowest use of interpolation and extrapolation on original gini coefficient data recorded in India?
- The lowest recorded value was 850 in 1870.
- How does India rank for use of interpolation and extrapolation on original gini coefficient data?
- India ranks 107th out of 160 countries with data for 2017.
- Is use of interpolation and extrapolation on original gini coefficient data rising or falling in India?
- Over the last ten years it is up 89.8%. The long-run trend across the full record is volatile.
- Where does this India data come from?
- The figures come from Various sources (2020) – processed by Our World in Data, published as part of Use of interpolation and extrapolation on original Gini coefficient data. Statizoid updates them automatically from the source API.
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CSV · JSON — 15 observations, free to reuse under CC BY 4.0 (Our World in Data).
About this data
In order to produce global estimates of historical poverty trends we have interpolated or extrapolated inequality data for missing observations. Green indicates observations of the Gini coefficient available in the original source.