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

Japan
88.41
in 2014
Peru
88.61
in 2014
Japan rank
52nd
Peru rank
50th

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

  • Japan
  • Peru
020406080100200520092014

How they compare

Peru currently reports 88.61 against 88.41 in Japan, a difference of 0.2.

The two have swapped places 4 times across 10 shared years of data; in 2005 it was Peru ahead.

Japan ranks 52nd and Peru ranks 50th of 181 countries.

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

Head to head by decade

Decade Japan Peru Difference Ahead
2000s 88.66 89.59 0.9219 Peru
2010s 87.91 89.04 1.12 Peru

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, Japan or Peru?
Peru, at 88.61 against 88.41 in Japan as of 2014.
What is the difference in trading across borders: cost to import (us$ per container)(db06-15 met between Japan and Peru?
0.2, with Peru ahead.
How many years of comparable data are there for Japan and Peru?
10 years are reported by both, from 2005 to 2014.
How do Japan and Peru rank globally for trading across borders: cost to import (us$ per container)(db06-15 met?
Japan ranks 52nd and Peru ranks 50th 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.