Moldova vs Rwanda: Trading across borders: Time to import (days) (DB06-15 methodology)

Moldova
62.9
in 2014
Rwanda
62.9
in 2014
Moldova rank
128th
Rwanda rank
128th

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

  • Moldova
  • Rwanda
0204060200520092014

How they compare

Moldova currently reports 62.9 against 62.9 in Rwanda, a difference of 0.

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

Moldova ranks 128th and Rwanda ranks 128th of 181 countries.

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

Head to head by decade

Decade Moldova Rwanda Difference Ahead
2000s 57.74 17.74 40 Moldova
2010s 60.32 57.1 3.23 Moldova

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), Moldova or Rwanda?
Moldova, at 62.9 against 62.9 in Rwanda as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Moldova and Rwanda?
0, with Moldova ahead.
How many years of comparable data are there for Moldova and Rwanda?
10 years are reported by both, from 2005 to 2014.
How do Moldova and Rwanda rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Moldova ranks 128th and Rwanda ranks 128th 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.