Anguilla vs Montserrat: Share of population living in rural areas
Anguilla
100.0%
in 2020
Montserrat
100.0%
in 2020
Anguilla rank
1st
Montserrat rank
1st
Share of population living in rural areas over time
- Anguilla
- Montserrat
How they compare
Anguilla currently reports 100.0% against 100.0% in Montserrat, a difference of 0.0%.
The two have swapped places 1 time across 15 shared years of data; in 1950 it was Anguilla ahead.
Anguilla ranks 1st and Montserrat ranks 1st of 236 countries.
Anguilla has averaged higher in every one of the 8 decades both report.
Head to head by decade
| Decade | Anguilla | Montserrat | Difference | Ahead |
|---|---|---|---|---|
| 1950s | 100.0% | 4.5% | 95.5% | Anguilla |
| 1960s | 100.0% | 6.7% | 93.3% | Anguilla |
| 1970s | 100.0% | 9.6% | 90.4% | Anguilla |
| 1980s | 100.0% | 8.1% | 91.9% | Anguilla |
| 1990s | 100.0% | 13.0% | 87.0% | Anguilla |
| 2000s | 100.0% | 100.0% | 0.0% | — |
| 2010s | 100.0% | 100.0% | 0.0% | — |
| 2020s | 100.0% | 100.0% | 0.0% | — |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher share of population living in rural areas, Anguilla or Montserrat?
- Anguilla, at 100.0% against 100.0% in Montserrat as of 2020.
- What is the difference in share of population living in rural areas between Anguilla and Montserrat?
- 0.0%, with Anguilla ahead.
- How many years of comparable data are there for Anguilla and Montserrat?
- 15 years are reported by both, from 1950 to 2020.
- How do Anguilla and Montserrat rank globally for share of population living in rural areas?
- Anguilla ranks 1st and Montserrat ranks 1st of 236 countries.
- Where does this data come from?
- European Commission, Joint Research Centre (JRC) (2025) – with major processing by Our World in Data, published as Share of population living in rural areas. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
Estimated share of the population living in rural areas. Rural areas are identified using satellite imagery and population data, applying the same definitions across countries.