SlideShare a Scribd company logo
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
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
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
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
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
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
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
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
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
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

More Related Content

PDF
Income inequality in South Africa report
PPTX
Gini coefficient and gdp
PDF
The Disenchantment of Latin America: What to expect from the region in 2020?
 
PDF
劉遵義 Income inequality under economic globalisation(final) 20150414
PPT
Factors Influencing Development
PDF
Economic sustainability
PDF
April 2009
PDF
February 2009
Income inequality in South Africa report
Gini coefficient and gdp
The Disenchantment of Latin America: What to expect from the region in 2020?
 
劉遵義 Income inequality under economic globalisation(final) 20150414
Factors Influencing Development
Economic sustainability
April 2009
February 2009

What's hot (19)

PDF
Social trendsgeorgegrayfinal 1
PDF
Measuring a country's progress
PPTX
Economic inequality
PPTX
What is poverty
PDF
Wdr 1984 'step to reduce fertility' confirms that the un and the who are im...
PPTX
Rethinking Inequality in Arab States
PPTX
Income Inequality presentation
PDF
D0142635
DOCX
Lifting the small boats
PPT
Development gap lesson 1
PDF
ChoicesArticle_3Q2016
PPT
Unit 3 contested_planet_bridging_the_development_gap
PPTX
Income inequality
DOC
Bridging the development gap file organiser
PPTX
HUMANITY DIVIDED: Confronting inequality in Developing Countries
PDF
UNCTAD - The Least Developed Countries Report 2011 - Overview
PPTX
Income inequality
PDF
DS Keynote Menu 2017
PDF
June 2009
Social trendsgeorgegrayfinal 1
Measuring a country's progress
Economic inequality
What is poverty
Wdr 1984 'step to reduce fertility' confirms that the un and the who are im...
Rethinking Inequality in Arab States
Income Inequality presentation
D0142635
Lifting the small boats
Development gap lesson 1
ChoicesArticle_3Q2016
Unit 3 contested_planet_bridging_the_development_gap
Income inequality
Bridging the development gap file organiser
HUMANITY DIVIDED: Confronting inequality in Developing Countries
UNCTAD - The Least Developed Countries Report 2011 - Overview
Income inequality
DS Keynote Menu 2017
June 2009
Ad

Similar to Indicators Of Economic Development (20)

DOCX
Economic Conditions in Developing Countries An economics lec.docx
PPT
Economic problems of development
PPTX
Chapter-2 Characterstics of UDs.pptx
PDF
Rural Development
PPT
TOPIC4A_COMMON CHARACTERISTICS OF DEVELOPING COUNTRIES.ppt
PPT
Honors geo. ch 21 p.p.
DOCX
Act Local Please respond to the following in 2-3 paragraphsBased .docx
PDF
PPT
A2development2112
PPT
Population Populationdevelopment
PPT
A2development
PPTX
[SARMIENTO] Development and Wealth POERPOINT PRESENTATION.pptx
PDF
Module 3 unit 2 geography
DOC
Rural finance in an indian economy
PDF
Localization And Globalization
PDF
#TimeToCare (India Supplement) | Oxfam India
PPTX
Poverty as challenge
PDF
Notes Global Poverty Presentation 15 May 08
PDF
Inequality matters: BRICS inequalities fact sheet
Economic Conditions in Developing Countries An economics lec.docx
Economic problems of development
Chapter-2 Characterstics of UDs.pptx
Rural Development
TOPIC4A_COMMON CHARACTERISTICS OF DEVELOPING COUNTRIES.ppt
Honors geo. ch 21 p.p.
Act Local Please respond to the following in 2-3 paragraphsBased .docx
A2development2112
Population Populationdevelopment
A2development
[SARMIENTO] Development and Wealth POERPOINT PRESENTATION.pptx
Module 3 unit 2 geography
Rural finance in an indian economy
Localization And Globalization
#TimeToCare (India Supplement) | Oxfam India
Poverty as challenge
Notes Global Poverty Presentation 15 May 08
Inequality matters: BRICS inequalities fact sheet
Ad

Recently uploaded (20)

PDF
HVAC Specification 2024 according to central public works department
PPTX
Onco Emergencies - Spinal cord compression Superior vena cava syndrome Febr...
PPTX
History, Philosophy and sociology of education (1).pptx
PPTX
Chinmaya Tiranga Azadi Quiz (Class 7-8 )
PPTX
B.Sc. DS Unit 2 Software Engineering.pptx
PDF
CISA (Certified Information Systems Auditor) Domain-Wise Summary.pdf
PPTX
ELIAS-SEZIURE AND EPilepsy semmioan session.pptx
PPTX
CHAPTER IV. MAN AND BIOSPHERE AND ITS TOTALITY.pptx
PDF
Black Hat USA 2025 - Micro ICS Summit - ICS/OT Threat Landscape
PDF
Chinmaya Tiranga quiz Grand Finale.pdf
PDF
Paper A Mock Exam 9_ Attempt review.pdf.
PDF
Indian roads congress 037 - 2012 Flexible pavement
PPTX
Virtual and Augmented Reality in Current Scenario
PDF
1.3 FINAL REVISED K-10 PE and Health CG 2023 Grades 4-10 (1).pdf
PDF
AI-driven educational solutions for real-life interventions in the Philippine...
PDF
Weekly quiz Compilation Jan -July 25.pdf
PDF
FOISHS ANNUAL IMPLEMENTATION PLAN 2025.pdf
PDF
BP 704 T. NOVEL DRUG DELIVERY SYSTEMS (UNIT 1)
PDF
1_English_Language_Set_2.pdf probationary
PPTX
A powerpoint presentation on the Revised K-10 Science Shaping Paper
HVAC Specification 2024 according to central public works department
Onco Emergencies - Spinal cord compression Superior vena cava syndrome Febr...
History, Philosophy and sociology of education (1).pptx
Chinmaya Tiranga Azadi Quiz (Class 7-8 )
B.Sc. DS Unit 2 Software Engineering.pptx
CISA (Certified Information Systems Auditor) Domain-Wise Summary.pdf
ELIAS-SEZIURE AND EPilepsy semmioan session.pptx
CHAPTER IV. MAN AND BIOSPHERE AND ITS TOTALITY.pptx
Black Hat USA 2025 - Micro ICS Summit - ICS/OT Threat Landscape
Chinmaya Tiranga quiz Grand Finale.pdf
Paper A Mock Exam 9_ Attempt review.pdf.
Indian roads congress 037 - 2012 Flexible pavement
Virtual and Augmented Reality in Current Scenario
1.3 FINAL REVISED K-10 PE and Health CG 2023 Grades 4-10 (1).pdf
AI-driven educational solutions for real-life interventions in the Philippine...
Weekly quiz Compilation Jan -July 25.pdf
FOISHS ANNUAL IMPLEMENTATION PLAN 2025.pdf
BP 704 T. NOVEL DRUG DELIVERY SYSTEMS (UNIT 1)
1_English_Language_Set_2.pdf probationary
A powerpoint presentation on the Revised K-10 Science Shaping Paper

Indicators Of Economic Development

  • 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