Lithuania vs Peru: Decile ratios of gross earnings — Interdecile ratio of gross earnings
Lithuania
1.7 Factor of decile 1
in 2024
Peru
1.98 Factor of decile 1
in 2022
Lithuania rank
3rd
Peru rank
3rd
Decile ratios of gross earnings — Interdecile ratio of gross earnings over time
- Lithuania
- Peru
How they compare
Peru currently reports 1.98 Factor of decile 1 against 1.7 Factor of decile 1 in Lithuania, a difference of 0.28 Factor of decile 1.
That makes Peru's figure about 1.2 times Lithuania's.
Across all 6 years both countries report, Peru has been ahead every year.
Lithuania ranks 3rd and Peru ranks 3rd of 8 countries.
Peru has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Lithuania | Peru | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 1.84 Factor of decile 1 | 2.35 Factor of decile 1 | 0.5096 Factor of decile 1 | Peru |
| 2020s | 1.75 Factor of decile 1 | 2.26 Factor of decile 1 | 0.5139 Factor of decile 1 | Peru |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher decile ratios of gross earnings — interdecile ratio of gross earnings, Lithuania or Peru?
- Peru, at 1.98 Factor of decile 1 against 1.7 Factor of decile 1 in Lithuania as of 2022.
- What is the difference in decile ratios of gross earnings — interdecile ratio of gross earnings between Lithuania and Peru?
- 0.28 Factor of decile 1, with Peru ahead.
- How many years of comparable data are there for Lithuania and Peru?
- 6 years are reported by both, from 2010 to 2022.
- How do Lithuania and Peru rank globally for decile ratios of gross earnings — interdecile ratio of gross earnings?
- Lithuania ranks 3rd and Peru ranks 3rd of 8 countries.
- Where does this data come from?
- Organisation for Economic Co-operation and Development, published as Decile ratios of gross earnings — Interdecile ratio of gross earnings. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
This dataset contains three earnings-dispersion measures - ratio of 9th-to-1st, 9th-to-5th and 5th-to-1st - where 9th, 5th (median) and 1st deciles are upper-earnings decile limits, unless otherwise indicated, of gross earnings of full-time dependent employees.