Austria vs Italy: Trading across borders: Cost to export (US$ per container) (DB06-15 me

Austria
83.88
in 2014
Italy
82.9
in 2014
Austria rank
84th
Italy rank
87th

Trading across borders: Cost to export (US$ per container) (DB06-15 me over time

  • Austria
  • Italy
020406080200520092014

How they compare

Austria currently reports 83.88 against 82.9 in Italy, a difference of 0.98.

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

Austria ranks 84th and Italy ranks 87th of 181 countries.

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

Head to head by decade

Decade Austria Italy Difference Ahead
2000s 84.57 77.9 6.67 Austria
2010s 83.26 81.28 1.99 Austria

Averages of every year both report within each decade.

Frequently asked questions

Which has higher trading across borders: cost to export (us$ per container) (db06-15 me, Austria or Italy?
Austria, at 83.88 against 82.9 in Italy as of 2014.
What is the difference in trading across borders: cost to export (us$ per container) (db06-15 me between Austria and Italy?
0.98, with Austria ahead.
How many years of comparable data are there for Austria and Italy?
10 years are reported by both, from 2005 to 2014.
How do Austria and Italy rank globally for trading across borders: cost to export (us$ per container) (db06-15 me?
Austria ranks 84th and Italy ranks 87th of 181 countries.
Where does this data come from?
The World Bank, published as Trading across borders: Cost to export (US$ per container) (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: Cost to export (US$ per container) (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 cost to export 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.