Angola vs Nepal: Trading across borders: Cost to import (US$ per container)(DB06-15 met

Angola
58.15
in 2014
Nepal
59.49
in 2014
Angola rank
156th
Nepal rank
155th

Trading across borders: Cost to import (US$ per container)(DB06-15 met over time

  • Angola
  • Nepal
0204060200520092014

How they compare

Nepal currently reports 59.49 against 58.15 in Angola, a difference of 1.34.

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

Angola ranks 156th and Nepal ranks 155th 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 20.13 45.99 25.87 Nepal
2010s 46 59.48 13.47 Nepal

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, Angola or Nepal?
Nepal, at 59.49 against 58.15 in Angola as of 2014.
What is the difference in trading across borders: cost to import (us$ per container)(db06-15 met between Angola and Nepal?
1.34, 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: cost to import (us$ per container)(db06-15 met?
Angola ranks 156th and Nepal ranks 155th 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

Indicator
Trading across borders: Cost to import (US$ per container)(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 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.