Equatorial Guinea vs Georgia: Trading across borders: Cost to import (US$ per container)(DB06-15 met
Equatorial Guinea
78.13
in 2014
Georgia
78.22
in 2014
Equatorial Guinea rank
115th
Georgia rank
114th
Trading across borders: Cost to import (US$ per container)(DB06-15 met over time
- Equatorial Guinea
- Georgia
How they compare
Georgia currently reports 78.22 against 78.13 in Equatorial Guinea, a difference of 0.09.
The two have swapped places 2 times across 10 shared years of data; in 2005 it was Georgia ahead.
Equatorial Guinea ranks 115th and Georgia ranks 114th of 181 countries.
Georgia has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Equatorial Guinea | Georgia | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 57.36 | 72.33 | 14.97 | Georgia |
| 2010s | 71.88 | 77.23 | 5.35 | Georgia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher trading across borders: cost to import (us$ per container)(db06-15 met, Equatorial Guinea or Georgia?
- Georgia, at 78.22 against 78.13 in Equatorial Guinea as of 2014.
- What is the difference in trading across borders: cost to import (us$ per container)(db06-15 met between Equatorial Guinea and Georgia?
- 0.09, with Georgia ahead.
- How many years of comparable data are there for Equatorial Guinea and Georgia?
- 10 years are reported by both, from 2005 to 2014.
- How do Equatorial Guinea and Georgia rank globally for trading across borders: cost to import (us$ per container)(db06-15 met?
- Equatorial Guinea ranks 115th and Georgia ranks 114th of 181 countries.
- Where does this data come from?
- The World Bank, published as Trading across borders: Cost to import (US$ per container)(DB06-15 methodology) - Score. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The score for the cost to import benchmarks economies with respect to the regulatory best practice on the indicator. The score ranges 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 DB06-15 studies.