Namibia vs Solomon Islands: Trading across borders: Time to import (days) (DB06-15 methodology)

Namibia
74.19
in 2014
Solomon Islands
74.19
in 2014
Namibia rank
91st
Solomon Islands rank
91st

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

  • Namibia
  • Solomon Islands
020406080200520092014

How they compare

Namibia currently reports 74.19 against 74.19 in Solomon Islands, a difference of 0.

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

Namibia ranks 91st and Solomon Islands ranks 91st of 181 countries.

Head to head by decade

Decade Namibia Solomon Islands Difference Ahead
2000s 74.19 74.19 0
2010s 74.19 74.19 0

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), Namibia or Solomon Islands?
Namibia, at 74.19 against 74.19 in Solomon Islands as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Namibia and Solomon Islands?
0, with Namibia ahead.
How many years of comparable data are there for Namibia and Solomon Islands?
10 years are reported by both, from 2005 to 2014.
How do Namibia and Solomon Islands rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Namibia ranks 91st and Solomon Islands ranks 91st 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.