Angola vs Nepal: Trading across borders: Time to import (days) (DB06-15 methodology)

Angola
37.1
in 2014
Nepal
43.55
in 2014
Angola rank
160th
Nepal rank
157th

Trading across borders: Time to import (days) (DB06-15 methodology) over time

  • Angola
  • Nepal
1020304050200520092014

How they compare

Nepal currently reports 43.55 against 37.1 in Angola, a difference of 6.45.

That makes Nepal's figure about 1.2 times Angola's.

Across all 10 years both countries report, Nepal has been ahead every year.

Angola ranks 160th and Nepal ranks 157th of 181 countries.

Nepal has averaged higher in every one of the 2 decades both report.

Head to head by decade

Decade Angola Nepal Difference Ahead
2000s 11.29 50 38.71 Nepal
2010s 33.87 46.45 12.58 Nepal

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 Nepal?
Nepal, at 43.55 against 37.1 in Angola as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Angola and Nepal?
6.45, with Nepal ahead.
How many years of comparable data are there for Angola and Nepal?
10 years are reported by both, from 2005 to 2014.
How do Angola and Nepal rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Angola ranks 160th and Nepal ranks 157th 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

Indicator
Trading across borders: Time to import (days) (DB06-15 methodology) - Score
Source
World Bank
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
183 places, 1,813 data points, 2005–2014
Last refreshed

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.