rural-urban dynamics_report.pdf - Khazar University

94 RURAL-URBAN DISPARITIES AND DYNAMICS GLOBAL MONITORING REPORT 2013
FIGURE 2.5
Literacy rates in rural areas and smaller towns are worse than in large cities
Percent
100
90
80
70
60
50
40
30
20
10
0
Niger Guinea Côte
d’Ivoire
Mali
Central
African
Republic
Sierra
Leone
Mauritania Senegal Togo Malawi Gabon Swaziland
XXS XS S M L XXL Rural XL
Source: Coulombe and Lanjouw 2013.
rates in Latin America, Europe and Central
Asia, and 10–16 percentage points in the
Middle East and North Africa, South Asia,
and Sub-Saharan Africa. East Asia has the
highest differential, at 21 percentage points.
Individual country differences are more
informative (figure 2.6).
A study of 40 Sub-Saharan African countries
based on DHS data indicates that the
infant mortality rate is 65 (per 1,000 live
births) in urban areas and 80 in rural areas.
The percentage of deliveries in health
facilities in urban areas is about 78 percent
on average across the countries, compared
with 43 percent in rural areas, in a sample of
28 Sub-Saharan Africa countries. The largest
rural-urban differences are in some of the
poorest countries (Wodon 2013b). Similar
patterns are observed for measures of child
malnutrition. Countries with the worst indicators
for infant and child mortality also
have the largest absolute differences between
rural and urban areas. The average share of
stunting in children is 42 percent in rural
areas compared to 30 percent in urban areas
(Wodon 2013b).
It is sometimes argued that other dimensions
of poverty—health outcomes, for
example—tend to be better in large cities.
Analysis of anthropometric health outcomes
for children across cities of different sizes
in Mexico (based on small-area estimation
methods) suggests that the prevalence of
child stunting in Mexico tends to be higher
in small towns than in the largest cities
(Ferre, Ferreira, and Lanjouw 2012). This
corresponds with findings regarding poverty,
which is more pronounced in smaller cities
than in larger cities.
Understanding the broader economic
consequences of closing health gaps in
low-income countries
Most countries are lagging behind in all three
health-related MDGs. It is therefore useful to
quantitatively evaluate the broader economic
consequences of closing health gaps in lowincome
countries. In a simulation exercise
conducted for this report, the broader economic
consequences of closing health gaps
in low-income countries were explored by
adapting maquette for MDG simulations
(MAMS), a computable general equilibrium
(CGE) model for country strategy analysis,
to address the rural-urban aspects of MDG
achievement (Lofgren 2013). The database
used was designed to capture characteristics
typical of low-income countries, including
their MDG outcomes, sectoral shares in
value-added of agriculture, manufacturing
and services, degree of urbanization, and
population growth. Annex 2A.1 presents
the results of this exercise. The main results