Georgia vs Taiwan: Trading across borders: Time to import (days) (DB06-15 methodology)

Georgia
90.32
in 2014
Taiwan
90.32
in 2014
Georgia rank
30th
Taiwan rank
30th

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

  • Georgia
  • Taiwan
20406080100200520092014

How they compare

Georgia currently reports 90.32 against 90.32 in Taiwan, a difference of 0.

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

Georgia ranks 30th and Taiwan ranks 30th of 181 countries.

Across the 2 decades both report, Georgia averaged higher in 1 and Taiwan in 1.

Head to head by decade

Decade Georgia Taiwan Difference Ahead
2000s 72.58 87.1 14.52 Taiwan
2010s 89.68 89.03 0.6452 Georgia

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), Georgia or Taiwan?
Georgia, at 90.32 against 90.32 in Taiwan as of 2014.
What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Georgia and Taiwan?
0, with Georgia ahead.
How many years of comparable data are there for Georgia and Taiwan?
10 years are reported by both, from 2005 to 2014.
How do Georgia and Taiwan rank globally for trading across borders: time to import (days) (db06-15 methodology)?
Georgia ranks 30th and Taiwan ranks 30th 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.