Chad vs Rwanda: Use of interpolation and extrapolation on original Gini coefficient data

Chad
2,066
in 2017
Rwanda
1,819
in 2017
Chad rank
137th
Rwanda rank
140th

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

  • Chad
  • Rwanda
5001.0k1.5k2.0k182019182017

How they compare

Chad currently reports 2,066 against 1,819 in Rwanda, a difference of 247.

That makes Chad's figure about 1.1 times Rwanda's.

The two have swapped places 2 times across 15 shared years of data; in 1820 it was Chad ahead.

Chad ranks 137th and Rwanda ranks 140th of 160 countries.

Across the 13 decades both report, Chad averaged higher in 5 and Rwanda in 8.

Head to head by decade

Decade Chad Rwanda Difference Ahead
1820s 598.96 554.49 44.46 Chad
1850s 525.35 486.35 39 Chad
1870s 648.36 600.23 48.13 Chad
1890s 635.46 600.23 35.23 Chad
1910s 650.51 1,075 424.46 Rwanda
1920s 614.41 1,251 636.27 Rwanda
1950s 815 1,020 205 Rwanda
1960s 974 1,224 250 Rwanda
1970s 880 1,337 457 Rwanda
1980s 583 1,672 1,089 Rwanda
1990s 692 1,398 706 Rwanda
2000s 991 1,118 126.5 Rwanda
2010s 1,893 1,618 275.5 Chad

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, Chad or Rwanda?
Chad, at 2,066 against 1,819 in Rwanda as of 2017.
What is the difference in use of interpolation and extrapolation on original gini coefficient data between Chad and Rwanda?
247, with Chad ahead.
How many years of comparable data are there for Chad and Rwanda?
15 years are reported by both, from 1820 to 2017.
How do Chad and Rwanda rank globally for use of interpolation and extrapolation on original gini coefficient data?
Chad ranks 137th and Rwanda ranks 140th 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.