East Timor vs Zimbabwe: Trading across borders: Time to export: Border compliance (hours) (DB1

East Timor
40.25
in 2019
Zimbabwe
45.07
in 2019
East Timor rank
150th
Zimbabwe rank
148th

Trading across borders: Time to export: Border compliance (hours) (DB1 over time

  • East Timor
  • Zimbabwe
01020304050201420162019

How they compare

Zimbabwe currently reports 45.07 against 40.25 in East Timor, a difference of 4.82.

That makes Zimbabwe's figure about 1.1 times East Timor's.

Across all 6 years both countries report, Zimbabwe has been ahead every year.

East Timor ranks 150th and Zimbabwe ranks 148th of 188 countries.

Zimbabwe has averaged higher in every one of the 1 decades both report.

Frequently asked questions

Which has higher trading across borders: time to export: border compliance (hours) (db1, East Timor or Zimbabwe?
Zimbabwe, at 45.07 against 40.25 in East Timor as of 2019.
What is the difference in trading across borders: time to export: border compliance (hours) (db1 between East Timor and Zimbabwe?
4.82, with Zimbabwe ahead.
How many years of comparable data are there for East Timor and Zimbabwe?
6 years are reported by both, from 2014 to 2019.
How do East Timor and Zimbabwe rank globally for trading across borders: time to export: border compliance (hours) (db1?
East Timor ranks 150th and Zimbabwe ranks 148th of 188 countries.
Where does this data come from?
The World Bank, published as Trading across borders: Time to export: Border compliance (hours) (DB16-20 methodology) - Score. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

About this data

Indicator
Trading across borders: Time to export: 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

The score for the time for border compliance to export 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.