Is trading across borders: cost to import: border compliance (usd) (db16 rising or falling in Fiji?

Over the last ten years it is unchanged. The long-run trend across the full record is flat.

Where does this Fiji data come from?

The figures come from the World Bank, published as part of Trading across borders: Cost to import: Border compliance (USD) (DB16-20 methodology) - Score. Statizoid updates them automatically from the source API.

Trading across borders: Cost to import: Border compliance (USD) (DB16 in Fiji

Name: Trading across borders: Cost to import: Border compliance (USD) (DB16 in Fiji
Creator: World Bank
License: CC BY 4.0 (World Bank Open Data)

Fiji: Trading across borders: Cost to import: Border compliance (USD) (DB16 was 73.35 in 2019. ▬ Flat

Latest (2019)

73.35

Change on year

unchanged

World rank

83rd

of 188 countries

All-time high

73.35

in 2014

All-time low

73.35

in 2014

Years of data

2014–2019

Trading across borders: Cost to import: Border compliance (USD) (DB16 in Fiji, 2014–2019

Source: World Bank.

Analysis

Fiji recorded 73.35 for trading across borders: cost to import: border compliance (usd) (db16 in 2019. That is the highest value across all 6 years on record.

The figure is unchanged over ten years.

Fiji ranks 83rd of 188 countries on this measure, in the middle of the range.

Countries ranked near Fiji

80 South Korea 73.78 compare
81 Japan 73.76 compare
82 Bolivia 73.75 compare
84 Gambia 72.86 compare
85 Tonga 72.5 compare
86 Cyprus 72.08 compare

See the full ranking of 190 places →

More reference data data for Fiji

Emission Totals - Indirect emissions (N2O) - Agricultural Soils 0.307 (2050)
Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.0683 (2050)
Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 0.1992 (2050)
Emission Totals - Indirect emissions (N2O) - Crop Residues 0.0009 (2050)
Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 0.307 (2050)
Emission Totals - Emissions (CO2eq) (AR5) - Agricultural Soils 382.55 (2050)
Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure applied to 60.73 (2050)
Emission Totals - Emissions (CH4) - IPCC Agriculture 38.02 (2050)
Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture 428.11 (2050)
Emission Totals - Direct emissions (N2O) - Manure left on Pasture 0.8534 (2050)

All data for Fiji →

Frequently asked questions

What is trading across borders: cost to import: border compliance (usd) (db16 in Fiji?: Trading across borders: cost to import: border compliance (usd) (db16 in Fiji was 73.35 in 2019, according to the World Bank.
What is the highest trading across borders: cost to import: border compliance (usd) (db16 recorded in Fiji?: The highest recorded value was 73.35 in 2014.
What is the lowest trading across borders: cost to import: border compliance (usd) (db16 recorded in Fiji?: The lowest recorded value was 73.35 in 2014.
How does Fiji rank for trading across borders: cost to import: border compliance (usd) (db16?: Fiji ranks 83rd out of 188 countries with data for 2019.
Is trading across borders: cost to import: border compliance (usd) (db16 rising or falling in Fiji?: Over the last ten years it is unchanged. The long-run trend across the full record is flat.
Where does this Fiji data come from?: The figures come from the World Bank, published as part of Trading across borders: Cost to import: Border compliance (USD) (DB16-20 methodology) - Score. Statizoid updates them automatically from the source API.

Download this data

CSV · JSON — 6 observations, free to reuse under CC BY 4.0 (World Bank Open Data).

About this data

Indicator: Trading across borders: Cost to import: Border compliance (USD) (DB16-20 methodology) - Score
Source: World Bank
Licence: CC BY 4.0 (World Bank Open Data)
Coverage: 190 places, 1,139 data points, 2014–2019
Last refreshed: 10 August 2026

The score for the cost for border compliance 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 DB16-20 studies.