Congo vs Zambia: Trading across borders: Time to import (days) (DB06-15 methodology)

Congo
19.35
in 2014
Zambia
20.97
in 2014
Congo rank
168th
Zambia rank
167th

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

  • Congo
  • Zambia
5101520200520092014

How they compare

Zambia currently reports 20.97 against 19.35 in Congo, a difference of 1.62.

That makes Zambia's figure about 1.1 times Congo's.

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

Congo ranks 168th and Zambia ranks 167th of 181 countries.

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

Head to head by decade

Decade Congo Zambia Difference Ahead
2000s 6.45 11.29 4.84 Zambia
2010s 11.61 19.03 7.42 Zambia

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), Congo or Zambia?
Zambia, at 20.97 against 19.35 in Congo as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Congo and Zambia?
1.62, with Zambia ahead.
How many years of comparable data are there for Congo and Zambia?
10 years are reported by both, from 2005 to 2014.
How do Congo and Zambia rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Congo ranks 168th and Zambia ranks 167th 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.