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

Over the last ten years it is up 118.1%. The long-run trend across the full record is rising.

Where does this Brazil 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 Brazil

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

Brazil: Trading across borders: Cost to import: Border compliance (USD) (DB16 was 68.75 in 2019. ▲ Rising

Latest (2019)

68.75

Change on year

unchanged

World rank

93rd

of 188 countries

All-time high

68.75

in 2018

All-time low

31.52

in 2014

Years of data

2014–2019

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

Source: World Bank.

Analysis

Brazil recorded 68.75 for trading across borders: cost to import: border compliance (usd) (db16 in 2019. That is the highest value across all 6 years on record.

That represents a change of up 118.1% over ten years.

Brazil ranks 93rd of 188 countries on this measure, in the middle of the range.

Countries ranked near Brazil

90 New Zealand 69.46 compare
91 Mauritius 68.99 compare
92 Vietnam 68.92 compare
94 Zambia 68.33 compare
95 Indonesia 68.12 compare
96 Puerto Rico 67.86 compare

See the full ranking of 190 places →

More reference data data for Brazil

Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 13.82 (2050)
Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 72.83 (2050)
Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 139.27 (2050)
Emission Totals - Indirect emissions (N2O) - Crop Residues 9.01 (2050)
Emission Totals - Indirect emissions (N2O) - Agricultural Soils 139.27 (2050)
Emission Totals - Emissions (N2O) - Manure applied to Soils 46.34 (2050)
Emission Totals - Emissions (N2O) - Manure Management 18.99 (2050)
Emission Totals - Emissions (N2O) - Manure left on Pasture 405.35 (2050)
Emission Totals - Emissions (N2O) - IPCC Agriculture 699.19 (2050)
Emission Totals - Emissions (N2O) - Crop Residues 49.04 (2050)

All data for Brazil →

Frequently asked questions

What is trading across borders: cost to import: border compliance (usd) (db16 in Brazil?: Trading across borders: cost to import: border compliance (usd) (db16 in Brazil was 68.75 in 2019, according to the World Bank.
What is the highest trading across borders: cost to import: border compliance (usd) (db16 recorded in Brazil?: The highest recorded value was 68.75 in 2018.
What is the lowest trading across borders: cost to import: border compliance (usd) (db16 recorded in Brazil?: The lowest recorded value was 31.52 in 2014.
How does Brazil rank for trading across borders: cost to import: border compliance (usd) (db16?: Brazil ranks 93rd out of 188 countries with data for 2019.
Is trading across borders: cost to import: border compliance (usd) (db16 rising or falling in Brazil?: Over the last ten years it is up 118.1%. The long-run trend across the full record is rising.
Where does this Brazil 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.