Comoros vs Syria: Trading across borders: Time to import (days) (DB06-15 methodology)

Comoros
67.74
in 2014
Syria
67.74
in 2014
Comoros rank
109th
Syria rank
109th

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

  • Comoros
  • Syria
020406080200520092014

How they compare

Comoros currently reports 67.74 against 67.74 in Syria, a difference of 0.

The two have swapped places 2 times across 10 shared years of data; in 2005 it was Syria ahead.

Comoros ranks 109th and Syria ranks 109th of 181 countries.

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

Head to head by decade

Decade Comoros Syria Difference Ahead
2000s 67.74 70.32 2.58 Syria
2010s 67.74 70 2.26 Syria

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), Comoros or Syria?
Comoros, at 67.74 against 67.74 in Syria as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Comoros and Syria?
0, with Comoros ahead.
How many years of comparable data are there for Comoros and Syria?
10 years are reported by both, from 2005 to 2014.
How do Comoros and Syria rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Comoros ranks 109th and Syria ranks 109th 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.