Malta vs Spain: Use of interpolation and extrapolation on original Gini coefficient data

Malta
30,902
in 2017
Spain
30,908
in 2017
Malta rank
32nd
Spain rank
31st

Use of interpolation and extrapolation on original Gini coefficient data over time

  • Malta
  • Spain
010.0k20.0k30.0k182019182017

How they compare

Spain currently reports 30,908 against 30,902 in Malta, a difference of 6.

Across all 15 years both countries report, Spain has been ahead every year.

Malta ranks 32nd and Spain ranks 31st of 160 countries.

Spain has averaged higher in every one of the 13 decades both report.

Head to head by decade

Decade Malta Spain Difference Ahead
1820s 472.88 1,600 1,127 Spain
1850s 564.89 1,706 1,141 Spain
1870s 694.38 1,809 1,115 Spain
1890s 925.84 2,463 1,537 Spain
1910s 1,150 2,823 1,673 Spain
1920s 1,336 4,173 2,837 Spain
1950s 1,573 3,464 1,891 Spain
1960s 2,383 5,037 2,654 Spain
1970s 3,889 9,511 5,622 Spain
1980s 8,920 14,008 5,088 Spain
1990s 13,259 19,215 5,956 Spain
2000s 21,170 28,940 7,770 Spain
2010s 27,268 31,347 4,080 Spain

Averages of every year both report within each decade.

Frequently asked questions

Which has higher use of interpolation and extrapolation on original gini coefficient data, Malta or Spain?
Spain, at 30,908 against 30,902 in Malta as of 2017.
What is the difference in use of interpolation and extrapolation on original gini coefficient data between Malta and Spain?
6, with Spain ahead.
How many years of comparable data are there for Malta and Spain?
15 years are reported by both, from 1820 to 2017.
How do Malta and Spain rank globally for use of interpolation and extrapolation on original gini coefficient data?
Malta ranks 32nd and Spain ranks 31st of 160 countries.
Where does this data come from?
Various sources (2020) – processed by Our World in Data, published as Use of interpolation and extrapolation on original Gini coefficient data. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

About this data

Indicator
Use of interpolation and extrapolation on original Gini coefficient data
Source
Various sources (2020) – processed by Our World in Data
Licence
CC BY 4.0 (Our World in Data)
Coverage
160 places, 2,400 data points, 1820–2017
Last refreshed

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.