Is trading across borders: time to import: border compliance (hours) (db1 rising or falling in Malta?

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

Where does this Malta data come from?

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

Trading across borders: Time to import: Border compliance (hours) (DB1 in Malta

Name: Trading across borders: Time to import: Border compliance (hours) (DB1 in Malta
Creator: World Bank
License: CC BY 4.0 (World Bank Open Data)

Malta: Trading across borders: Time to import: Border compliance (hours) (DB1 was 99.8 in 2019. ▬ Flat

Latest (2019)

99.8

Change on year

unchanged

World rank

27th

of 188 countries

All-time high

99.8

in 2014

All-time low

99.8

in 2014

Years of data

2014–2019

Trading across borders: Time to import: Border compliance (hours) (DB1 in Malta, 2014–2019

Source: World Bank.

Analysis

The most recent figure for trading across borders: time to import: border compliance (hours) (db1 in Malta is 99.8, measured in 2019. That is the highest value across all 6 years on record.

That represents a change of unchanged over ten years.

Malta ranks 27th of 188 countries on this measure, in the top quarter.

Countries ranked near Malta

26 United States 99.82 compare
28 Canada 99.64 compare
28 Finland 99.64 compare
28 Kazakhstan 99.64 compare
28 Norway 99.64 compare

See the full ranking of 190 places →

More reference data data for Malta

Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.0121 (2050)
Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 0.0042 (2050)
Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 0.0205 (2050)
Emission Totals - Indirect emissions (N2O) - Crop Residues 0.0008 (2050)
Emission Totals - Indirect emissions (N2O) - Agricultural Soils 0.0205 (2050)
Emission Totals - Emissions (N2O) - Manure applied to Soils 0.0404 (2050)
Emission Totals - Emissions (N2O) - Manure Management 0.0227 (2050)
Emission Totals - Emissions (N2O) - Manure left on Pasture 0.0192 (2050)
Emission Totals - Emissions (N2O) - IPCC Agriculture 0.1009 (2050)
Emission Totals - Emissions (N2O) - Crop Residues 0.0043 (2050)

All data for Malta →

Frequently asked questions

What is trading across borders: time to import: border compliance (hours) (db1 in Malta?: Trading across borders: time to import: border compliance (hours) (db1 in Malta was 99.8 in 2019, according to the World Bank.
What is the highest trading across borders: time to import: border compliance (hours) (db1 recorded in Malta?: The highest recorded value was 99.8 in 2014.
What is the lowest trading across borders: time to import: border compliance (hours) (db1 recorded in Malta?: The lowest recorded value was 99.8 in 2014.
How does Malta rank for trading across borders: time to import: border compliance (hours) (db1?: Malta ranks 27th out of 188 countries with data for 2019.
Is trading across borders: time to import: border compliance (hours) (db1 rising or falling in Malta?: Over the last ten years it is unchanged. The long-run trend across the full record is flat.
Where does this Malta data come from?: The figures come from the World Bank, published as part of Trading across borders: Time to import: Border compliance (hours) (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: Time to import: Border compliance (hours) (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 time 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.