Lithuania vs South Sudan: Paying taxes: Postfiling index (0-100) (DB17-20 methodology) - Score

Lithuania
97.52
in 2019
South Sudan
95.87
in 2019
Lithuania rank
11th
South Sudan rank
14th

Paying taxes: Postfiling index (0-100) (DB17-20 methodology) - Score over time

  • Lithuania
  • South Sudan
020406080100201520172019

How they compare

Lithuania currently reports 97.52 against 95.87 in South Sudan, a difference of 1.65.

Across all 5 years both countries report, Lithuania has been ahead every year.

Lithuania ranks 11th and South Sudan ranks 14th of 180 countries.

Lithuania has averaged higher in every one of the 1 decades both report.

Frequently asked questions

Which has higher paying taxes: postfiling index (0-100) (db17-20 methodology) - score, Lithuania or South Sudan?
Lithuania, at 97.52 against 95.87 in South Sudan as of 2019.
What is the difference in paying taxes: postfiling index (0-100) (db17-20 methodology) - score between Lithuania and South Sudan?
1.65, with Lithuania ahead.
How many years of comparable data are there for Lithuania and South Sudan?
5 years are reported by both, from 2015 to 2019.
How do Lithuania and South Sudan rank globally for paying taxes: postfiling index (0-100) (db17-20 methodology) - score?
Lithuania ranks 11th and South Sudan ranks 14th of 180 countries.
Where does this data come from?
The World Bank, published as Paying taxes: Postfiling index (0-100) (DB17-20 methodology) - Score. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

About this data

Indicator
Paying taxes: Postfiling index (0-100) (DB17-20 methodology) - Score
Source
World Bank
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
182 places, 910 data points, 2015–2019
Last refreshed

The score for postfiling index benchmarks economies with respect to the regulatory best practice on the indicator. The score is indicated on a scale from 0 to 100, where 0 represents the worst regulatory performance and 100 the best regulatory performance, and is computed based on the methodology in the DB17-20 studies.