1. Development Economics Web Guide, Unit 5B 4
Indicators of development Compare and contrast GDP per Understand the limitations of
in developing countries in capita and other measures of national income statistics as
sub-Saharan Africa, Asia economic and social development, indicators of development.
and Latin America e.g. life expectancy, literacy rates, Explain the inter-relationships
the proportion of population between these indicators.
Absolute and relative employed in agriculture. Understand
poverty. the distinction between these terms.
Differences between Compare how the record of Understand how there are
developing countries. economic development differs in differences in countries both
sub-Saharan Africa, Asia and Latin between and within the three
America and explain reasons for continents and a consideration
these differences. of these differences.
Indicators of Economic Development
Introduction
The specification refers to two categories of country, ‘developed’ and ‘developing’. A
variety of economic and social indicators can be used to classify countries in this way.
However, some of these are more reliable than others.
Further classifications are possible between countries within the ‘developing’
category – for example, strong differences by region emerge: Africa, South Asia, East
Asia and Latin America have rather different sets of characteristics. However, it is
also true that countries within each of these regions differ widely.
Some Important Indicators
A very wide variety of indicators can be used to characterise the difference between
developed and developing countries. Only a small selection is considered here. The
data reported below comes from the United Nations Human Development Report for
2001.
1 GDP per capita
GDP per capita is the total value of (final i.e. not intermediate) goods and services
produced within a country divided by the total population. The bar chart below shows
the extraordinary difference between countries in terms of GDP per head. It also
illustrates the relative difference between countries categorised as ‘developing’:
Ghana had $1881 per capita in 1999, Zambia only $756. It is worth pausing to
consider the figures for Zambia: on average, people there live on no more than about
$2 a day. As a measure of development this seems to be the most important indicator:
if people want to be in a position to buy commodities and enjoy high standards of
health and education then they will need the income to match.
Issue 1 – May 2003
Authorised by Peter Goff

2. Development Economics Web Guide, Unit 5B 5
GDP per capita, PPP US $, 1999
25000
20000
15000
10000
5000
0
UK Ghana Zambia
There are some issues concerning the reliability of this indicator. One problem is
measuring GDP in countries where much economic activity is unofficial. The data
itself may be collected by governments who use different and more or less efficient
methods of measurement. The measurement of inflation is also problematic: if
inflation is under-estimated then real output will be over-estimated. Government
officials may have an incentive to over-value output (particularly the unsold output of
nationalised industries). Another major problem is the high level of subsistence
farming in developing countries: non-marketed output may never get measured.
To enable cross-country comparisons the data needs to be standardised to a particular
currency. Using current exchange rates is unlikely to be appropriate for this – they are
only based on traded goods and are greatly affected by speculative capital flows. The
alternative, finding a purchasing power parity (PPP) rate with which to do the
conversion, is non trivial in a world where goods and services differ so widely
between countries.
There are some other problems. First, it may be more informative to see patterns of
GDP per capita growth over time, rather than just a snapshot of a particular year.
Second, there is no sense in which this indicator can tell the whole story of a
country’s economic or social situation – for example, there can be widely varying
standards of health and education for countries with similar levels of GDP per head.
The distribution of GDP may also vary, in some countries being much more uneven
than in others. Third, increasing GDP per capita may bring with it costs as well as
benefits, particularly if it is brought about in a non-sustainable way: the level of
negative externalities needs to be considered.
The rate of growth of GDP is also crucial. Over the last ten years real GDP per head
in the UK has grown by 2.1% per year. Over the same period, the figure for Ghana
was 1.6% and for Zambia minus 2.4%.
Issue 1 – May 2003
Authorised by Peter Goff

3. Development Economics Web Guide, Unit 5B 6
2. Life Expectancy
In 1999, Ghana had a life expectancy at birth of 56.6 years, contrasting with Zambia’s
41.0 years and the UK’s 77.7 years. A variety of factors may contribute to these
differences – the stability of food supplies, the extent to which an area is contested by
war, and the incidence of disease are all important.
It is therefore possible for countries with similar levels of GDP per head to have very
different life expectancies: for example, Vietnam currently has an almost identical
income per head to Ghana, but a considerably higher life expectancy of 67.8 years.
According to World Bank figures, over the past 40 years, life expectancy at birth in
developing countries as a whole increased by 20 years. The figures above suggest that
this was not evenly distributed. In many countries in sub-Saharan Africa life
expectancy is now falling due to the AIDS epidemic.
3. Literacy Rates
The UN Development Report defines adult literacy rates as the percentage of those
aged 15 and above who are able to read and write a short, simple, statement on their
everyday life. This is a very narrow definition of literacy.
Interestingly, on this measure Zambia has a literacy rate of 77.2%, compared to
Ghana’s 70.3%, and better than that of Saudi Arabia which has fourteen times higher
GDP per head. However, and once again, a single indicator cannot tell the whole story
– an important part of development economics consists in trying to understand the
origins of such differences.
More extensive definitions of literacy are available, for example ‘functional literacy’
based on the International Adult Literacy Survey. This survey tests people’s ability to
understand printed text, to interpret documents adequately and perform basic
arithmetic. One problem with such indicators is the care needed to ensure that the
survey is appropriate to the local culture – you cannot ask people to interpret texts that
refer to areas outside of their experience. ‘Literacy’ is likely to be considerably
determined within a culture rather than across cultures. The wider the definition of
literacy the greater this problem will be.
Another problem is the distribution of literacy: a number of countries have a
considerable gender divide, denying women access to the same levels of education as
men.
Issue 1 – May 2003
Authorised by Peter Goff

4. Development Economics Web Guide, Unit 5B 7
4 Measures of Poverty
It is important to understand the difference between absolute and relative poverty.
Absolute poverty refers to the inability to acquire goods necessary to satisfy basic
needs e.g. the means to obtain the minimum level of nutrition necessary to sustain an
active life. Basic needs also tend to include clothing and shelter. Put simply, absolute
poverty is having ‘just enough to survive’ but no more. However, it is well worth
considering whether what counts as ‘absolute’ poverty is, to some extent, relative to
the culture concerned: the concept is by no means uncontroversial.
Relative poverty refers to the differential of income and wealth between people or
countries. That is, it involves some comparison across economies.
One indicator of absolute poverty is the percentage of the population receiving less
than the equivalent of $1 a day income. This stood at 38.8% for Ghana and 63.7% for
Zambia in 1999. For most developed countries there is no absolute poverty according
to this measure because of social security benefits. The World Bank estimates that
1.2bn people live off less than $1 a day, with a further 1.6bn existing on less than $2 a
day.
The figures for absolute poverty have to be treated with some caution for reasons
similar to those discussed for GDP per capita. The concept is itself rather loose, and a
$x a day measure is somewhat arbitrary: especially as local costs of living vary
enormously and there are wide variations across countries of, for example, climate.
There is also something of a preconceived idea involved in defining poverty in terms
of income levels – it may be that for some people there are other more pressing
objectives e.g. having shoes to wear or establishing a separation of living quarters for
people and animals. These other objectives may be improving even when income is
falling. Many commentators therefore prefer to see ‘poverty’ as a multidimensional
concept. This is important because the way poverty is conceptualised will influence
the policy measures adopted to deal with it. For example, a definition based
exclusively on income will tend to see growth in GDP per head as the only solution to
poverty.
Other dimensions of absolute poverty might include access to ‘essential’ drugs
(Ghana 44%, Zambia 66%, UK 100%) and the proportion of the population using
regulated water supplies (only 64% in both Ghana and Zambia).
To shed light on relative poverty it is possible to compare GDP per capita between
countries or to look at income distributions within a particular country. The
inequalities of income in developing countries can be very pronounced. In 1999 the
richest 10% of the population in the UK had a 27.3% share of income. For Ghana the
figure was 29.5%, for Zambia it was as high as 41%.
Note that relative poverty is an issue even at a local scale of description. For example,
within households there can be widely varying distributions of resources e.g. on the
basis of age or gender.
Issue 1 – May 2003
Authorised by Peter Goff

5. Development Economics Web Guide, Unit 5B 8
5 Demographic Indicators
The table below contrasts Ghana and Zambia through a variety of further possible
demographic (to do with population) indicators of development:
Indicator UK Ghana Zambia
Annual
Population 0.1% 2.1% 2.3%
Growth Rate
Urban Population
– percentage of 89.4% 37.9% 39.5%
total
Percentage of the
Population Under 19.1% 41.4% 46.5%
the age of 15
Infant Mortality
Rate per 1,000
live births, 1999 6 (18) 63 (111) 112 (109)
figures,
(1970 figures in
brackets)
6 Disease Indicators
Disease is endemic in many developing countries due to low levels of health care,
expensive drugs, contaminated water supplies, and poor health education. The figures
in the table below speak for themselves.
Indicator UK Ghana Zambia
% of adult
population with 0.11% 3.6% 19.95%
HIV/AIDS
Malaria cases
(per 100,000 0 11,941 37,458
people)
Tuberculosis cases
(per 100,000 10 53 482
people)
Issue 1 – May 2003
Authorised by Peter Goff

6. Development Economics Web Guide, Unit 5B 9
Aggregate Indices of Development
To minimise the problems with individual indicators discussed above it is possible to
combine a selection of indicators to form an index of development. Several of these
are published by various organisations. The UN Development Report, for example,
ranks countries by their “Human development index” which includes the major
indices of life expectancy, adult literacy, and GDP per capita. This then creates a
league table of development with the UK, at 14th, ranked as a country with “high
human development”, Ghana at 119th classified as having “medium human
development” and Zambia, at 143rd in the category “low human development”.
As with any index, weights have to be used to construct the overall figure. These are
to some extent arbitrary. However, it is interesting to see that some countries e.g.
Pakistan, have relatively high GDP per capita but are much lower than this might
suggest in the overall development index. This may suggest failures of government
policy.
Africa, Asia, Latin America
Development indicators suggest pronounced regional differences. The countries of
Latin America tend to be high up in the category “medium human development”.
The countries of Asia also tend to be in the medium development classification, but
lower down the ranking than countries in Latin America.
The category of “low human development” is almost entirely made up of countries
from sub-Saharan Africa.
GDP per capita, 1999 US $
8000
7000
6000
5000
$ 4000
3000
2000
1000
0
Latin East Asia South Asia Sub-Saharan
America Africa
Issue 1 – May 2003
Authorised by Peter Goff

7. Development Economics Web Guide, Unit 5B 10
However, growth within these regions has been by no means uniform:
· Chile and Uruguay have grown so fast in the past few decades that they are
now in the UN’s “high human development” group. Meanwhile, GDP in many
Latin American countries was falling in the 1980s – as it is again during the
current debt crisis.
· Countries in East Asia, including most recently China, have grown far more
rapidly than those in South Asia e.g. India. Thus, according to the World
Bank, the number of people living in absolute poverty (less than $1 a day) fell
by 139.2 million in East Asia and the Pacific between 1987 and 1998 whilst in
South Asia the number increased by 47.6 million.
However, the economic performance of countries in sub-Saharan Africa was not only
poor but much less diverse – it appears to be very difficult for the very poorest
countries to escape their poverty. According to the World Bank “sub-Saharan Africa
as a region saw no increase in its per-capita incomes between 1965 and 1999, even
with some improvement in the 1990s.”
Inter-Relationships Between Indicators
An important question is the extent to which the indicators outlined above are inter-
related. This is a complex issue and only a few points are made here.
There is a strong positive correlation between GDP per capita and life expectancy.
However the graph below shows that this is non-linear – for the obvious reason that a
small increase in wealth can enable basic standards of health and education to be
established and thus dramatically improved increases in life span, whereas
expenditure on advanced medical care in developed countries only brings marginal
increases in longevity.
Issue 1 – May 2003
Authorised by Peter Goff

8. Development Economics Web Guide, Unit 5B 11
Low and Medium Development Countries
80
75
70
Life expectancy, years
65
60
55
50
45 South Africa
40
Zimbabwe
35
30
0 5000 10000 15000
GDP per capita, $ 1999 PPP
In the aggregate the correlation between these variables is striking. However, a
number of countries seem to be separate from the overall pattern, from Zimbabwe,
through Angola and Namibia to South Africa marked on the graph.
The dramatic difference that levels of GDP per capita seem to be able to make to life
expectancy in most countries is shown on the following scatter diagram for the
poorest group:
Countries of Low Human Development
65
60
Life expectancy, years
55
50
45
40
35
30
0 1000 2000 3000 4000
GDP per capita, 1999 PPP $
Issue 1 – May 2003
Authorised by Peter Goff

9. Development Economics Web Guide, Unit 5B 12
The relationship between GDP per head and adult literacy, whilst positively
correlated when all countries are included, is much less clear for the poorest countries.
The graph below shows the relation between Adult literacy and GDP per capita for
countries of low human development:
Countries of Low Human Development
90
80
70
Adult Literacy
60
50
40
30
20
10
0
0 1000 2000 3000 4000
GDP per capital, $ 1999 PPP
This data is, in fact, slightly negatively correlated suggesting that in no sense are
education programmes a sufficient condition for development.
Resources for Pupils
www.worldbank.org/data/countrydata/countrydata.html
A very useful set of key economic indicators, some presented in graphical form, for
each country.
www.worldbank.org/poverty
Includes data and further links on poverty.
Suggested Activity
Scroll down the page on the first link above to “Countries at a glance”. Print out the
‘at a glance’ pages for Brazil, Argentina, Ghana, Zambia, India and China. You
should use these – or others of your choice - as case study countries. If you you’re
your own choice make sure that you include countries from each of the three main
regions mentioned in the specification: Latin America, Sub-Saharan Africa, and Asia.
Also be sure to include two countries from each region so as to be able to draw out the
Issue 1 – May 2003
Authorised by Peter Goff

10. Development Economics Web Guide, Unit 5B 13
differences within the region. You will need information on specific countries to help
answer the ‘Questions for Discussion’ at the end of each section.
Using the World Bank resource listed above, prepare for a class presentation a
comparison of either Brazil and Argentina (Latin America) or Ghana and Zambia
(Sub-Saharan Africa) or India and China (Asia). You should also try to get hold a
recent issue of the United Nations Development Report to retrieve the Human
Development Indices (HDI) for your chosen countries.
Begin to collect newspaper reports and articles from The Economist about the selected
countries.
Questions for Discussion
1 After the class presentations, draw up a list of differences between Latin
America, Sub-Saharan Africa and Asia.
2 Is ‘Asia’ too large an area to be treated as a single region?
3 Is the concept of ‘literacy’ of any interest in a discussion of economic
development?
4 Examine the factors which might explain differences in infant mortality
rates between developing countries.
5 How clear cut is the concept of ‘poverty’? Does it matter?
6 What factors might explain why some countries are rising and some
countries falling in rank orders of human development?
7 “‘GDP per head’ is a very poor indicator of development.” Discuss.
8 Why is there so much discussion about what to call developing countries?
9 What is the significance of a negative figure for a GDP minus HDI
ranking?
10 Examine the implications of the statement (page 10) that “a small increase
in wealth can enable basic standards of health and education to be
established.”
Issue 1 – May 2003
Authorised by Peter Goff