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

Cyprus
88.61
in 2014
Peru
88.61
in 2014
Cyprus rank
50th
Peru rank
50th

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

  • Cyprus
  • Peru
020406080100200520092014

How they compare

Cyprus currently reports 88.61 against 88.61 in Peru, a difference of 0.

The two have swapped places 3 times across 7 shared years of data; in 2008 it was Cyprus ahead.

Cyprus ranks 50th and Peru ranks 50th of 181 countries.

Across the 2 decades both report, Cyprus averaged higher in 1 and Peru in 1.

Head to head by decade

Decade Cyprus Peru Difference Ahead
2000s 88.4 87.67 0.7311 Cyprus
2010s 88.66 89.04 0.3807 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, Cyprus or Peru?
Cyprus, at 88.61 against 88.61 in Peru as of 2014.
What is the difference in trading across borders: cost to import (us$ per container)(db06-15 met between Cyprus and Peru?
0, with Cyprus ahead.
How many years of comparable data are there for Cyprus and Peru?
7 years are reported by both, from 2008 to 2014.
How do Cyprus and Peru rank globally for trading across borders: cost to import (us$ per container)(db06-15 met?
Cyprus ranks 50th 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.