Angola vs Equatorial Guinea: Trading across borders: Time to import (days) (DB06-15 methodology)
Angola
37.1
in 2014
Equatorial Guinea
35.48
in 2014
Angola rank
160th
Equatorial Guinea rank
162nd
Trading across borders: Time to import (days) (DB06-15 methodology) over time
- Angola
- Equatorial Guinea
How they compare
Angola currently reports 37.1 against 35.48 in Equatorial Guinea, a difference of 1.62.
The two have swapped places 1 time across 10 shared years of data; in 2005 it was Equatorial Guinea ahead.
Angola ranks 160th and Equatorial Guinea ranks 162nd of 181 countries.
Equatorial Guinea has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Angola | Equatorial Guinea | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 11.29 | 36.77 | 25.48 | Equatorial Guinea |
| 2010s | 33.87 | 35.48 | 1.61 | Equatorial Guinea |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher trading across borders: time to import (days) (db06-15 methodology), Angola or Equatorial Guinea?
- Angola, at 37.1 against 35.48 in Equatorial Guinea as of 2014.
- What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Angola and Equatorial Guinea?
- 1.62, with Angola ahead.
- How many years of comparable data are there for Angola and Equatorial Guinea?
- 10 years are reported by both, from 2005 to 2014.
- How do Angola and Equatorial Guinea rank globally for trading across borders: time to import (days) (db06-15 methodology)?
- Angola ranks 160th and Equatorial Guinea ranks 162nd of 181 countries.
- Where does this data come from?
- The World Bank, published as Trading across borders: Time to import (days) (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 time 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.