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

Congo
0
in 2014
Rwanda
17.93
in 2014
Congo rank
174th
Rwanda rank
171st

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

  • Congo
  • Rwanda
0204060200520092014

How they compare

Rwanda currently reports 17.93 against 0 in Congo, a difference of 17.93.

The two have swapped places 1 time across 10 shared years of data; in 2005 it was Congo ahead.

Congo ranks 174th and Rwanda ranks 171st of 181 countries.

Across the 2 decades both report, Congo averaged higher in 1 and Rwanda in 1.

Head to head by decade

Decade Congo Rwanda Difference Ahead
2000s 46.42 17.02 29.4 Congo
2010s 0 34.71 34.71 Rwanda

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, Congo or Rwanda?
Rwanda, at 17.93 against 0 in Congo as of 2014.
What is the difference in trading across borders: cost to import (us$ per container)(db06-15 met between Congo and Rwanda?
17.93, with Rwanda ahead.
How many years of comparable data are there for Congo and Rwanda?
10 years are reported by both, from 2005 to 2014.
How do Congo and Rwanda rank globally for trading across borders: cost to import (us$ per container)(db06-15 met?
Congo ranks 174th and Rwanda ranks 171st 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.