Argentina vs Papua New Guinea: Trading across borders: Time to import (days) (DB06-15 methodology)
Argentina
58.06
in 2014
Papua New Guinea
58.06
in 2014
Argentina rank
140th
Papua New Guinea rank
140th
Trading across borders: Time to import (days) (DB06-15 methodology) over time
- Argentina
- Papua New Guinea
How they compare
Argentina currently reports 58.06 against 58.06 in Papua New Guinea, a difference of 0.
The two have swapped places 1 time across 10 shared years of data; in 2005 it was Argentina ahead.
Argentina ranks 140th and Papua New Guinea ranks 140th of 183 countries.
Argentina has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Argentina | Papua New Guinea | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 76.13 | 59.68 | 16.45 | Argentina |
| 2010s | 67.1 | 57.42 | 9.68 | Argentina |
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), Argentina or Papua New Guinea?
- Argentina, at 58.06 against 58.06 in Papua New Guinea as of 2014.
- What is the difference in trading across borders: time to import (days) (db06-15 methodology) between Argentina and Papua New Guinea?
- 0, with Argentina ahead.
- How many years of comparable data are there for Argentina and Papua New Guinea?
- 10 years are reported by both, from 2005 to 2014.
- How do Argentina and Papua New Guinea rank globally for trading across borders: time to import (days) (db06-15 methodology)?
- Argentina ranks 140th and Papua New Guinea ranks 140th of 183 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
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.