Jordan vs Serbia: Trading across borders: Time to import (days) (DB06-15 methodology)

Jordan
82.26
in 2014
Serbia
82.26
in 2014
Jordan rank
64th
Serbia rank
64th

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

  • Jordan
  • Serbia
020406080200520092014

How they compare

Jordan currently reports 82.26 against 82.26 in Serbia, a difference of 0.

The two have swapped places 3 times across 10 shared years of data; in 2005 it was Jordan ahead.

Jordan ranks 64th and Serbia ranks 64th of 181 countries.

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

Head to head by decade

Decade Jordan Serbia Difference Ahead
2000s 70 70.97 0.9678 Serbia
2010s 81.29 81.29 0 Serbia

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), Jordan or Serbia?
Jordan, at 82.26 against 82.26 in Serbia as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Jordan and Serbia?
0, with Jordan ahead.
How many years of comparable data are there for Jordan and Serbia?
10 years are reported by both, from 2005 to 2014.
How do Jordan and Serbia rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Jordan ranks 64th and Serbia ranks 64th 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.