Urbanization and Development : Is Latin America and the Caribbean Different from the Rest of the World?
Two long-established stylized facts in the urban and development economics literatures are that: (a) a country's level of economic development is strongly positively correlated with its level of urbanization; and (b) a country's level of...
| Main Authors: | , , , |
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| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2017
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/164251490903580662/Urbanization-and-development-is-Latin-America-and-the-Caribbean-different-from-the-rest-of-the-world http://hdl.handle.net/10986/26363 |
| Summary: | Two long-established stylized facts in
the urban and development economics literatures are that:
(a) a country's level of economic development is
strongly positively correlated with its level of
urbanization; and (b) a country's level of urbanization
is strongly negatively correlated with the size of its
agricultural sector. However, countries in the Latin America
and Caribbean region appear to depart significantly from the
rest of the world in these two basic relationships. Although
Latin American countries appear to be significantly more
urbanized than predicted based on these global
relationships, Caribbean countries appear significantly less
urbanized. However, analyses involving cross-country
comparisons of urbanization levels are undermined by
systematic measurement errors arising from differences in
how countries define their urban areas. This paper
reexamines whether Latin America and Caribbean countries
differ from the rest of the world in the basic stylized
facts of urbanization, development, and structural
transformation. The analysis makes use of two alternative
methodologies for the consistent definition of urban areas
across countries: the Agglomeration Index methodology and a
methodology based on the identification of dense spatially
contiguous clusters of population. Both methodologies rely
on globally gridded population data sets as input. There
exist several such data sets, and so the paper also assesses
the robustness of the findings to the choice of input
population layer. |
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