Congo vs Myanmar: Use of interpolation and extrapolation on original Gini coefficient data

Congo
5,747
in 2017
Myanmar
5,536
in 2017
Congo rank
111th
Myanmar rank
112th

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

  • Congo
  • Myanmar
02.0k4.0k6.0k182019182017

How they compare

Congo currently reports 5,747 against 5,536 in Myanmar, a difference of 211.

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

Congo ranks 111th and Myanmar ranks 112th of 160 countries.

Across the 13 decades both report, Congo averaged higher in 12 and Myanmar in 1.

Head to head by decade

Decade Congo Myanmar Difference Ahead
1820s 1,152 803 349.38 Congo
1850s 1,011 803 207.76 Congo
1870s 1,247 803 444.44 Congo
1890s 1,210 991.83 218.47 Congo
1910s 1,250 954.42 295.31 Congo
1920s 1,158 1,380 222.18 Myanmar
1950s 1,693 631 1,062 Congo
1960s 1,999 899 1,100 Congo
1970s 2,396 1,023 1,373 Congo
1980s 3,075 1,320 1,755 Congo
1990s 3,794 1,253 2,541 Congo
2000s 4,490 2,395 2,095 Congo
2010s 5,742 4,654 1,088 Congo

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, Congo or Myanmar?
Congo, at 5,747 against 5,536 in Myanmar as of 2017.
What is the difference in use of interpolation and extrapolation on original gini coefficient data between Congo and Myanmar?
211, with Congo ahead.
How many years of comparable data are there for Congo and Myanmar?
15 years are reported by both, from 1820 to 2017.
How do Congo and Myanmar rank globally for use of interpolation and extrapolation on original gini coefficient data?
Congo ranks 111th and Myanmar ranks 112th 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.