Trading across borders: Time to import (days) (DB06-15 methodology) in Marshall Islands
Marshall Islands: Trading across borders: Time to import (days) (DB06-15 methodology) was 66.13 in 2014. ▬ Flat
Trading across borders: Time to import (days) (DB06-15 methodology) in Marshall Islands, 2005–2014
Source: World Bank.
Analysis
The most recent figure for trading across borders: time to import (days) (db06-15 methodology) in Marshall Islands is 66.13, measured in 2014. That is the highest value across all 10 years on record.
The figure is unchanged over ten years.
Over the whole period, trading across borders: time to import (days) (db06-15 methodology) in Marshall Islands peaked at 66.13 in 2005 and was at its lowest, 66.13, in 2005.
Marshall Islands ranks 118th of 184 countries on this measure, in the middle of the range.
Trading across borders: Time to import (days) (DB06-15 methodology) in Marshall Islands, year by year
| Year | Value | Change |
|---|---|---|
| 2005 | 66.13 | — |
| 2006 | 66.13 | +0.0% |
| 2007 | 66.13 | +0.0% |
| 2008 | 66.13 | +0.0% |
| 2009 | 66.13 | +0.0% |
| 2010 | 66.13 | +0.0% |
| 2011 | 66.13 | +0.0% |
| 2012 | 66.13 | +0.0% |
| 2013 | 66.13 | +0.0% |
| 2014 | 66.13 | +0.0% |
Marshall Islands compared with similar countries
- Marshall Islands's 66.13 is below the median for upper middle income countries, which is 75.81, 87% of the median. (55 countries reporting)
- Marshall Islands's 66.13 is below the median for East Asia & Pacific, which is 70.97, 93% of the median. (27 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2000s | 66.13 | 66.13 | 66.13 | 5 |
| 2010s | 66.13 | 66.13 | 66.13 | 5 |
Countries ranked near Marshall Islands
- 118 Azerbaijan 66.13 compare
- 118 Benin 66.13 compare
- 118 Cameroon 66.13 compare
- 118 Mozambique 66.13 compare
- 118 Tonga 66.13 compare
More reference data data for Marshall Islands
- Emission Totals - Emissions (CH4) - IPCC Agriculture 0 (2019)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 0 (2019)
- Emission Totals - Emissions (CO2eq) (AR5) - IPCC Agriculture 0 (2019)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture 0 (2019)
- Emission Totals - Emissions (CO2eq) from CH4 (AR5) - IPCC Agriculture 0 (2019)
- Political opposition, annual growth rate 0 % change on previous year (2025)
- Elected parliament and government, annual growth rate 0 % change on previous year (2025)
- Global number of reported disasters by size, gaps filled 0 events (2024)
- Free country 2 (2025)
- Civil liberties rating 1 (2025)
Frequently asked questions
- What is trading across borders: time to import (days) (db06-15 methodology) in Marshall Islands?
- Trading across borders: time to import (days) (db06-15 methodology) in Marshall Islands was 66.13 in 2014, according to the World Bank.
- What is the highest trading across borders: time to import (days) (db06-15 methodology) recorded in Marshall Islands?
- The highest recorded value was 66.13 in 2005.
- What is the lowest trading across borders: time to import (days) (db06-15 methodology) recorded in Marshall Islands?
- The lowest recorded value was 66.13 in 2005.
- How does Marshall Islands rank for trading across borders: time to import (days) (db06-15 methodology)?
- Marshall Islands ranks 118th out of 184 countries with data for 2014.
- Is trading across borders: time to import (days) (db06-15 methodology) rising or falling in Marshall Islands?
- Over the last ten years it is unchanged. The long-run trend across the full record is flat.
- Where does this Marshall Islands data come from?
- The figures come from the World Bank, published as part of Trading across borders: Time to import (days) (DB06-15 methodology) - Score. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 10 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
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.