DEPARTMENT OF ECONOMICS

Uppsala University

Thesis C

Author: Johanna Ekhagen

Supervisor: Karin Edmark

Term and year: Spring 2009

HIV/AIDS in economic growth models

– how does HIV/AIDS influence the Solow Growth Model and what are the implications of

the pandemic for the fight against poverty for countries in Sub-Saharan Africa?

2

Abstract This thesis studies the impact from HIV/AIDS on economic growth in sub-Saharan Africa.

This is an important region for investigation since HIV/AIDS is more common in poor

countries where economic growth levels are initially low.

The theoretical framework for the analysis is the Solow Growth Model. The analysis also

considers the impact on changes to human capital and adds this factor to the Solow equation.

The analysis concludes that the HIV/AIDS epidemic has negative effects on per capita GDP

growth through the parameters of the Solow Growth Model, including human capital. The

thesis also deduces that the pandemic enhances income and gender inequality.

Keywords: Economic growth, HIV/AIDS, poverty

3

Table of Contents

1. Introduction .......................................................................................................................... 4

1.1 Aim and research question ............................................................................................... 5

1.2 Theoretical delimitation ................................................................................................... 6

1.3 Previous and current research .......................................................................................... 6

1.4 Method ............................................................................................................................. 9

1.5 Material ............................................................................................................................ 9

2. Theory ................................................................................................................................. 11

2.1 The Solow Growth Model.............................................................................................. 11

3. Empiricism.......................................................................................................................... 16

3.1 The impact of HIV/AIDS on saving and investment in physical capital ....................... 16

3.2 The impact of HIV/AIDS on the population.................................................................. 16

3.3 The impact of HIV/AIDS on human capital .................................................................. 17

4. Analysis ............................................................................................................................... 18

4.1. The impact of the factors in the Solow Growth Model................................................. 18

4.1.1 Saving and investment in physical capital .............................................................. 18

4.1.2 Population................................................................................................................ 19

4.1.3 Human capital ......................................................................................................... 20

4.2 HIV and its impact on economic growth; descriptive analysis ...................................... 22

4.3 Gender, HIV/AIDS and economic growth..................................................................... 25

5. Discussion............................................................................................................................ 26

6. Conclusion........................................................................................................................... 28

7. Summary ............................................................................................................................. 30

List of references .................................................................................................................... 32

4

1. Introduction

According to the executive director of the Joint United Nations Programme on HIV/AIDS

(UNAIDS) together with some advisors, AIDS is often said to be the core of a “vicious

circle” since the impacts of AIDS increase poverty and social deprivation while these factors

in turn increase vulnerability to HIV infection (Piot et al., 2007).

In 2007, over 33 million people worldwide were living with HIV1 and sub-Saharan Africa

was the most heavily affected region, accounting for almost 68 percent of all individuals

living with HIV and for 72 percent of all AIDS2 deaths in 2007 (UNAIDS, 2008, p. 3). In

addition to being a severely affected region, the spread of infections between men and women

is uneven in the region where women account for nearly 60 percent of those living with HIV

(UNAIDS, 2008, p. 8). This is higher than the world average where women account for about

50 percent of those infected (UNAIDS/WHO, 2007, p. 1). According to UNAIDS, HIV can

slow down economic growth, widen economic inequality and cause severe strains on affected

households. The epidemic has harsh effects on women who are more vulnerable for the

pandemic and has a 1.2 percent greater chance of being infected with the virus (USAID,

Health and Family Planning). UNAIDS argues that this means that there is a need to

implement scaled-up measures to increase women’s independent income-generating potential

(UNAIDS, 2008, p. 23).

In addition to being the most harshly damaged region by HIV/AIDS, sub-Saharan Africa is

also the poorest region in the world, accounting for only two percent of world Gross Domestic

Product (GDP) in 2005. The region is in spite of this home to twelve percent of the world’s

population (The World Bank, 2008 World Development Indicators, p. 3). This results in more

than 50 percent of the population living in poverty on less than $1.25 a day (The World Bank,

2008, Poverty data, p. 10). Furthermore, the region has the most unequal income distribution

in the world, where the richest 20 percent of the population get a 64.5 percentage share whilst

the poorest 20 percent get only 3.6 percent of income (The World Bank, 2008 World

Development Indicators, p. 5).

1 Human Immunodeficiency Virus 2 Acquired Immune Deficiency Syndrome, the disease caused by HIV

5

The annual growth rate of GDP per capita in sub-Saharan Africa was -0.5 percent between

1975 and 2005 and 0.5 percent from 1990 to 2005. This is the lowest growth rate in the world.

However, the region is projected to have the highest population growth rate between 2005 and

2015 with a mean of 2.3 percent (The World Bank, Human Development Report 2007/2008,

p. 280, 246).

Furthermore, AIDS undermines several important foundations for development which

include, economic growth, good governance, development of human capital, the investment

climate, and labour productivity (Ahwireng-Obeng – Akussah, 2003, p. 11).

Thus, since sub-Saharan Africa is both the poorest region in the world as well as the one most

severely affected by HIV/AIDS, how can the region expect the epidemic to influence

economic growth and poverty?

1.1 Aim and research question

The aim of this thesis is to analyse how HIV/AIDS influences the economic growth process in

countries severely affected by the HIV/AIDS pandemic. First, the thesis will analyse how

HIV/AIDS affects the components of the Solow Growth Model. Thereafter, it will discuss

how economic growth is affected by the epidemic. Hence, the analysis hopes to provide a

framework of how the epidemic influences macroeconomic models and theories by

investigating how the disease and its consequences affect the macro factors; acquisition of

human capital, employment levels, saving and investment patterns and population growth.

These effects can be implemented into the neoclassical Solow Growth Model and the effects

of the disease on economic growth can then be analysed. Since both poverty and the

HIV/AIDS epidemic have affected women more severely than men in sub-Saharan Africa, the

analysis also anticipates to bring forward how the epidemic affects economic growth and

poverty reduction differently between the two sexes.

Thus by investigating how the different factors of the Solow Growth Model are affected by

the HIV/AIDS epidemic, the thesis seeks to answer the research question; how does

HIV/AIDS affect the economic growth process in sub-Saharan Africa according to the Solow

Growth Model?

6

1.2 Theoretical delimitation

Since the world is big and all regions and countries have different prerequisites and

conditions, all parts of the world cannot be investigated in this thesis. This thesis will hence

only analyse the implications on economic growth from HIV/AIDS in sub-Saharan Africa.

The reason for this demarcation is that Africa and particularly the part south of Sahara, is the

poorest region in the world as well as the region most relentlessly affected by HIV/AIDS

(UNAIDS/WHO, 2007, p. 3). This makes the region sub-Saharan Africa an interesting region

for an analysis of these two areas of research and their interplay. I have moreover previously

written two essays in the sociology of religion concerning Christian values in relation to

HIV/AIDS, poverty and aid, which makes this a natural area for future research to deepen my

knowledge.

1.3 Previous and current research

Although there is much research being done on the subject of HIV/AIDS and economic

growth and development at the moment, the subject is fairly new. World Bank economist

Rene Bonnel estimated in HIV/AIDS: Does it Increase or Decrease Growth in Africa?

presented in 2000, that per capita economic growth in Africa was reduced by 0.7 percent per

year in the 1990s as a result of HIV/AIDS (Bonnela, 2000, p. 1). He also found that for

countries with a low prevalence rate of HIV/AIDS, the impact on growth was small.

However, for countries such as those in sub-Saharan Africa where the prevalence rate is high,

Bonnel estimated that a prevalence level of 20 percent would reduce the growth of GDP by

2.6 percentage points each year (Bonnela, 2000, p. 17). This is according to Bonnel the sum

of the reduction in growth per capita (1.2 per cent) and the shortfall in population growth (1.4

percent) (Bonnelb, 2000 p. 377). According to UNAIDS’ 2008 Report on the Global AIDS

Epidemic, the best available evidence suggests that HIV can reduce economic growth in high-

prevalence countries by 0.5 percent to 1.5 percent over a period of 10 to 20 years (UNAIDS,

2008, p. 23). Moreover, health economists Simon Dixon, Scott McDonald and Jennifer

Roberts, claim that the pandemic already has reduced average national economic growth rates

across Africa by two to four percent (Dixon et al, 2002).

Alan Whiteside, professor of Health Economics and HIV/AIDS at the University of

KwaZulu-Natal, South Africa and an elected member of the Governing Council of the

7

International AIDS Society, discusses the results found by Bonnel. However, he points out,

that AIDS does not appear to have held back economic growth in Uganda, Botswana or South

Africa (Whiteside, 2008, p. 68).

According to Whiteside, there is a distinct relationship between poverty and communicable

disease epidemics, which are diseases that can be passed on to other people. The causal chain

runs from different macro-factors and result in poverty through the individual, the household

and the community. Moreover, the immune system’s capacity is decreased which further the

effects (Whiteside, 2002, p. 316). Whiteside argues that the greatest impact comes to

individuals and households whereas the macroeconomic impacts take longer to evolve.

Additionally, the magnitude of these will depend on the scale and location of the micro-level

effects. Besides, the impact to households is concluded to be long term (Whiteside, 2002, p.

320).

A recent publication from the Nordic African Institute by Professor Arne Bigsten and

Lecturer Dick Durevall, both working at Gothenburg University, School of Business,

Economics and Law, provides facts concerning the links between economic growth and

HIV/AIDS and states that there is still not a consensus on how the pandemic affects income

per capita (Bigsten – Durevall, 2008, p. 9). They also bring forward recent research indicating

that even where HIV/AIDS does not reduce per capita income it does increase poverty. They

conclude that the size of the increase depends on how many people live near the poverty line

and the prevalence rate of HIV/AIDS among them. Additionally, the epidemic also worsens

income distribution (Bigsten – Durevall, 2008, p. 10).

Furthermore, Channing Arndt and Jeffrey D. Lewis argue that the AIDS epidemic is expected

to reduce the overall size of the economy. In an economy with fewer factors of production

together with reduced investment and a lower productivity as a consequence of AIDS, the size

of the economy is according to the authors bound to be small. However, not only the size of

the economy is reduced, the population is also condensed. Based on this finding, Arndt and

Lewis conclude that this may result in an increase in GDP per capita (Arndt – Lewis, 2000, p.

12).

HIV/AIDS affects all ‘classes’ and all are vulnerable to HIV, but the poor have suffered the

most economically. Equally important, AIDS obstruct efforts to reduce poverty as it deprives

8

the poor of the two most important assets they can utilise to bring themselves out of poverty,

namely health and education (Ahwireng-Obeng – Akussah, 2003, p. 11).

This theory gets support in the article Squaring the Circle AIDS, Poverty, and Human

Development presented in 2007 by Peter Piot, Robert Greener, and Sarah Russell, all

employees of UNAIDS. They present a distinct relationship between the HIV prevalence rate

and income inequality. This is illustrated in the Figure 1 below that shows the regression

between HIV prevalence and the Gini coefficient for countries in Africa.

Figure 1: HIV and income inequality

Source: Piot et al. (2007) Squaring the Circle AIDS, Poverty, and Human Development.

On the same note, International Monetary Fund (IMF) economists Gonzalo Salinas and

Markus Haacker investigated in 2006 the impact of HIV/AIDS on poverty and inequality in

sub-Saharan Africa by focusing on four countries in the region. Salinas and Haacker argue

that HIV/AIDS economically affects a household in two ways; it increases its expenditures

and it reduces its income as a result of morbidity and mortality. Their investigation and

calculations leads to the conclusion that the fall in average income as a result of HIV/AIDS is

significant in countries with high prevalence rates of the disease, while countries with lower

prevalence rates only will experience a reduction in income by one percent over a ten year

period. Additionally, their survey indicates that there is a correspondence between prevalence

rates of HIV/AIDS and increases in the poverty gap. They denote nevertheless that the effects

9

of HIV/AIDS on average income and poverty are not perfectly correlated which demonstrates

that there are distributional factors of bearing the impacts of the disease (Salinas – Haacker,

2006).

Lastly, according to Ibrahim A. Elbadawi and Benno J. Ndulu, analyses concerning the

economic growth process in sub-Saharan Africa have provided broad conclusions stating that

the region could not catch-up with other developing regions even tough they have low initial

income levels, as a result of the regions low standards of human capital and low levels of

saving (Elbadawi – Ndulu, 2001, p. 47).

1.4 Method

This thesis is a literature study as well as a theoretical investigation. This indicates that it will

be based upon economic theories and facts which will be presented graphically in order to be

compared to other economist’s research on the subject. In order to answer the research

question, different theoretical facts about areas important in the Solow Growth Model and

factors being affected by HIV/AIDS will be presented.

In order to answer the research question, this thesis aims to look into what other economists

have found about the relationship between HIV/AIDS and the parameters of the Solow

Growth Model. By looking at what these investigations have found about the effect of

HIV/AIDS on the factors in the Solow Growth Model, the aim is to see how HIV/AIDS

influence the outcome of the model’s predictions for economic growth. In addition, the

analysis will look at income inequality and gender differences in order to investigate whether

the higher prevalence rate for women in the region is correlated to the female level of poverty

in sub-Saharan Africa.

1.5 Material

The material in this thesis will partly be built upon sources from organizations such as the

Joint United Nations Programme on HIV/AIDS (UNAIDS) and from the World Bank’s

reports World Development Indicators as well as the Human Development Report. This

material has been collected and calculated for the dissemination of information, which gives it

10

a high level of objectivity. The fact that they are also generated in multicultural forums

provides impartiality which is important for the calculations and conclusions in this analysis.

The starting point when it comes to HIV/AIDS in relation to economic growth and human

development comes foremost from IMF economist Markus Haacker’s research. Haacker has

been Senior Economist at the United Nations Economics Commission for Africa (UNECA)

and has published several works concerning the macroeconomic implications of HIV/AIDS.

The research booklet The African economy and its role in the world economy published in

2008 by the Nordic African Institute, written by Arne Bigsten and Dick Durevall both

working at Gothenburg University, School of Business, Economics and Law will also be

used. This booklet focuses on factors affecting the development process in Africa and

provides an outline of the impact that HIV/AIDS has on these economies.

For the presentation of the Solow Growth Model, two books used as course literature in

Economics at Uppsala University, will be used. These are the Economics of Development,

sixth edition from 2006 by Dwight H. Perkins, Steven Radelet, and David L. Lindauer, and

Macroeconomics, the European edition from 2008 by N. Gregory Mankiw and Mark P.

Taylor. These books are very informative and simple which are useful for presenting the

theoretical framework of this thesis and its analysis.

The analysis will additionally be based on several articles, where World Bank economist

Rene Bonnel’s HIV/AIDS: Does it Increase of Decrease Growth in Africa? from 2000 is one

of them. This article has been important for the research concerning HIV/AIDS and economic

growth and several other sources reference to this article. Additionally, Alan Whiteside’s

article Poverty and HIV/AIDS in Africa published in 2002 will be used. Whiteside is Professor

of Health Economics and HIV/AIDS at the University of KwaZulu-Natal, South Africa and

an elected member of the Governing Council of the International AIDS Society.

The critical aspects of using this material is primarily that some researchers likely choose to

give emphasis to certain results in order to further their own agenda. However, since most of

the material is written based on economic theories or medical facts, there is little need to

suspect that the articles have been written with any political motif. However, it is important

that a critical perspective is held when the conclusions from the material is analysed and

discussed.

11

2. Theory

2.1 The Solow Growth Model

The Solow (neoclassical) Growth Model was introduced in 1956 by MIT-economist Robert

Solow. The new framework in this theory compared to earlier growth models, such as the

Harrod-Domar model, was that Solow dropped the fixed-coefficient production function and

allowed for substitution between the factors of production. Thus in the Solow model, the

capital-output and the capital-labour ratios are not fixed but vary depending on the

endowments of the economy and the production process (Perkins et al., 2006, p. 117). The

Solow Growth Model also assumes constant returns to scale (Perkins et al., 2006, p. 118).

The starting equation in order to demonstrate the Solow Growth Model structure is an

aggregate production function. Y represent total output and hence total income. K, is the

capital stock and L is the labour supply (Perkins et al., 2006, p. 105). Hence, under these

assumptions, the production function takes it starting point at;

Y=F(K,L)

Under the assumption of constant returns to scale, the production function of the Solow model

can be written as:

Y/L=F(K/L,1)

which shows that output per worker is a function of physical capital per worker. By

reordering the terms in output per worker, y=Y/L and capital per worker, k=K/L, the first

equation of the Solow Growth Model can be written as:

y=f(k)

This equation illustrates that physical capital per worker is elementary to the growth process

(Perkins et al., 2006, p. 119).

The capital-labour ratio is a key determinant of an economy’s output, can change over time

and can lead to economic growth. There are two important factors influencing the capital

stock; the depreciation of capital and investment (Mankiw – Taylor, 2008, p. 206).

The second equation of the Solow framework demonstrates the determinants of changes in

capital per worker and shows that capital accumulation depends on the growth rate of the

labour force, depreciation and on saving:

Δk=sky – (n+δk)k

12

The equation states that the change in physical capital per worker, Δk, is determined on three

constraints. The capital per worker is positively related to saving per worker since when the

saving per worker increases so does investment per worker, which in turn increases the capital

stock of each worker. However, capital per worker is negatively related to population growth.

When there is growth in the population and the labour force, this increase is shown by nL in

the equation. When there are nL new workers together with no additional investment, the

capital per worker decrease by –nk. In addition to this decrease, the depreciation erodes the

capital stock each year by the amount of –δkk (Perkins et al., 2006, p. 120, 121). The higher

the capital stock, the greater amounts of investment and of output. However, a high capital

stock also means a greater depreciation, which causes the capital stock to fall (Mankiw –

Taylor, 2008, p. 206, 207).

Furthermore, the Solow framework shows that saving is important for the steady-state capital

stock. If the saving rate is high, there is a large capital stock and a high level of output and

vice versa (Mankiw – Taylor, 2008, p. 212). However, saving alone cannot generate persistent

economic growth (Mankiw – Taylor, 2008, p. 229). Besides, the second equation illustrating

the change in the capital stock per worker shows, that population growth reduces the

accumulation of capital per worker through a similar pathway as depreciation does. However,

whilst depreciation erodes the capital stock, k, the population growth reduces the capital stock

because it has to be spread more stringently among a larger population (Mankiw – Taylor,

2008, p. 223). Hence, the Solow framework shows that saving levels and the rate of

population growth are important aspects of the growth process.

The two equations of the Solow Growth Model state that output per worker which is

equivalent to income per capita, is dependent on the amount of capital per worker and that

changes in capital per worker depends on saving, the population growth rate and on the

depreciation of physical capital (Perkins et al., 2006, p. 122).

The Solow Growth Model is illustrated in a diagram consisting of three curves, each

illustrating a step in the equation. The first curve is the production function y=f(k), the second

is the saving function, sky which shows saving per capita, and the third curve is the line

(n+δk)k, that illustrates the amount of new capital needed to keep capital per worker constant

when there are changes in the labour force and changes because of depreciation (Perkins et

al., 2006, p. 122). The Solow Growth Model reaches a steady state when the amount of new

13

saving is equal to the amount of new capital needed because of changes in the population and

because of depreciation. This is referred to as the steady state of the Solow Growth Model, at

which physical capital per worker, k, is constant. It is illustrated as point E in Figure 2 below.

It is important to note however that at this point, even tough capital and saving per worker

remain constant, total capital and total saving continues to grow (Perkins et al., 2006, p. 123).

Figure 2 The Solow Growth Model

Source: Perkins et al. (2006) Economics of Developement and Mankiw – Taylor (2008) Macroeconomics

The steady state of the Solow Growth Model is significant for several reasons. Foremost, the

steady state is the long-run equilibrium of the economy which indicates that an economy at

the steady state will remain there just as an economy not at the steady state will go there

(Mankiw – Taylor, 2008, p. 208). Additionally, at the long-run steady-state of the economy,

the positive effects on the capital stock per worker from investment exactly balances the

negative effects caused by population growth and the depreciation of capital. This equilibrium

is illustrated in the Solow Growth Model equations as; sky =(n+δk)k. At this stage, investment

has two purposes. The part, δkk replaces the depreciated capital while nk provides the new

workers form the population growth with the steady-state level of capital. When the economy

reaches its steady-state level, the level of output per worker is at its optimum, y=f(k) (Mankiw

– Taylor, 2008, p. 223, 224).

14

Furthermore, the Solow Growth Model is altered by population growth in three ways. In the

steady state with population growth, both capital and output per worker are constant.

However, since the number of workers is growing at rate n, so must total capital and total

output. Thus, population growth can help shed light to the sustained growth in total output.

Population growth also explains why some countries are richer than others and the theory

predicts that countries with higher population growth will have lower levels of GDP per

capita (Mankiw – Taylor, 2008, p. 223, 224).

From the previous research presented above, we have learnt that the factors being affected by

HIV/AIDS are the saving rate and the incentives to invest. We have also learnt that the size of

the population is affected as the disease affect people in their most productive years.

Moreover, many studies conducted in economics today emphasise human capital and how

important this factor is for increased total output and hence total income. Since these are

outcomes of the Solow model, it is possible to assume that human capital is a supplementary

factor being affected by HIV/AIDS that also affects per capita output or income. Hence, the

Solow Growth Model has to be modified to include human capital since this factor is not part

of the original model. Through this addition, it is possible to get a clear picture of how the

epidemic alters the economic growth of economies.

In order to take into account human capital, I include human capital as an additional factor in

the production function and assume that it has the same properties as physical capital. This is

done in order to obtain a model framework that can illustrate the partial effects of changes in

investments in human capital on economic growth in a simple way. The first aggregate

production function thus takes the form:

Y=F(K,L,H)

where Y is total output (and total income), K is still the capital stock and L is the labour force.

H represents the human capital that has been incorporated into the production function of the

economy. By reordering the terms as output per worker, y=Y/L, physical capital per worker;

k=K/L, and human capital per worker, h=H/L, the first equation of the Solow Growth Model

can be written as:

y=f(k,h)

where y is output per worker or capital per worker, k represents physical capital and h

represents the added human capital. This equation now illustrates that physical capital per

15

worker and human capital per worker are two factors influencing the economic growth

process.

Thus, the new Solow Growth Model illustrates that the determinants of changes in human

capital are saving per worker, investment, population growth and depreciation. We assume

that these factors respond to changes in the same way as for physical capital. In the equation

sh represents saving and investment in human capital, and δh is the depreciation rate for

human capital. This can be written as:

Δh=shy – (n+δh)h

As a result of this adjustment, we now have a theory stating that economic growth is altered

by saving rates, investments, population growth, depreciation and human capital. This is

illustrated in two equations:

Δk=sky – (n+δk)k

which shows the effect on physical capital per worker and:

Δh=shy – (n+δh)h

which illustrates how human capital is influenced.

Since the Solow Growth Model is a theoretical model, it has both strengths and weaknesses

when trying to understand the economic growth process. One important weakness of the

model is that even tough the model provides focus on fundamental influences of the growth

rate and the steady state, it does not provide a full understanding on the pathways through

which these factors influence economic growth and output. Additionally, the model does only

provide insight in one sector, it does not consider the fact that various sectors may have

different allocations of resources, which could influence productivity (Perkins et al., 2006, p.

131).

We have now learnt that according to the Solow Growth Model, saving rates, investments,

population growth and depreciation are the determinants for changes in physical capital per

worker. We have also added the implications of changes to investments in and the

composition of human capital into the production function. We shall now see how each of

these factors are expected to influence economic growth.

16

3. Empiricism

The theories presented above have shown that the parameters of the Solow Growth Model;

saving, investment, population growth, depreciation and additionally human capital, are all

factors influencing economic growth. In order to investigate how HIV/AIDS affect the

economic growth process of economies, we must look deeper into how HIV/AIDS affects the

parameters that are important for economic growth. After this analysis, we can see how these

impact the Solow Growth Model.

3.1 The impact of HIV/AIDS on saving and investment in physical capital

Arne Bigsten and Dick Durevall discuss how HIV/AIDS impact peoples prospects about the

future. They refer to a theory presented both by Lorentz et al in 2005 as well as by Kalemli

and Ozcan in 2006, which states that the severest impact from HIV/AIDS is through adult

mortality. Since adult mortality affects the time horizon people have for the future, people

will become more myopic and reduce investment in both physical capital and education as

mortality increases (Bigsten – Durevall, 2008, p. 38).

According to Channing Arndt and Jeffrey D. Lewis in The Macro Implications of HIV/AIDS

in South Africa: A Preliminary Assessment, saving rates are likely to be affected by

HIV/AIDS. Moreover, they argue that AIDS affected households are unlikely to have high

saving rates (Arndt – Lewis, 2000, p. 3).

This hypothesis is supported by Alan Whiteside who argues that HIV/AIDS is assumed to

affect economic growth through both reduced saving levels as well as lower levels of

investment (Whiteside, 2008, p. 68-69).

3.2 The impact of HIV/AIDS on the population

HIV/AIDS affects the population in several ways; it increases the morbidity of people in their

most reproductive years and it reduces fertility rates. Moreover, the epidemic may alter the

structure of the population and slow the rate of population growth (Ahwireng-Obeng –

Akussah, 2003, p. 8).

17

IMF economist Markus Haacker investigates how the supply of labour is affected by the

HIV/AIDS epidemic. He argues that the overall size of the labour force declines and that the

age structure of the workforce changes as a result of changes in mortality and birth rates

(Haacker, 2002, p. 19). He claims that the disruptions in the production process caused by

sickness and death of employees have an impact on the productivity of firms and that the

decline in the growth rate of the labour force results in declines in the growth of GDP

(Haacker, 2002, p. 24).

In addition, Arndt and Lewis predict that the HIV/AIDS pandemic will slow population

growth and have a differential impact on growth in the labour supply, similar to what Haacker

believes (Arndt – Lewis, 2000, p. 9).

3.3 The impact of HIV/AIDS on human capital

Rene Bonnel concludes in HIV/AIDS: Does it Increase or Decrease Growth in Africa? that

“the initial effect of HIV/AIDS is to destroy human capital.” (Bonnela, 2000, p. 5).

Fred Ahwireng-Obeng, professor of Economics and Dr George Akussha, principal Medical

Officer both at the Wits Business School, Johannesburg, South Africa, proclaim that

HIV/AIDS undermines the acquisition of human capital and its usage through two combined

effects. These are the loss of skilled and educated people and through the loss of education

opportunities for the children of families affected by the epidemic – which foremost are the

poorest (Ahwireng-Obeng – Akussah, 2003, p. 17).

Markus Haacker contends that the HIV/AIDS epidemic affects the educational sector in

various ways. The number of teachers decreases as a result of increased mortality and the

number of pupils also decline as a result of declining birth rates and increased child mortality

(Haacker, 2002, p. 13). Additional to these factors, there may also be a risk of deterioration in

the access to education. Haacker emphasise that while a decline in enrollment rates may ease

the burden of the epidemic on the education sector, it would also mean a descent in accessing

education and as most of the orphans who drop out come from poorer households, the income

inequality within the country could increase (Haacker, 2002, p. 16).

18

In addition Haacker remonstrates that the skill composition of the labour supply changes and

that the labour turnover rates increase as a result of the pandemic. Haacker sees that these

changes in the size of the supply of labour is a close match to the changes in the demographic

structure of the population in South Africa, where he did his investigation (Haacker, 2002, p.

19). Accordingly, Haacker argues that the rising mortality rates due to HIV/AIDS directly

affect personnel costs for companies which may reduce the incentives of companies to invest

in training for their employees (Haacker, 2002, p. 22).

These theories get support from Whiteside who concludes that HIV/AIDS is assumed to

affect economic growth since it reduces the size of the labour force, which lowers efficiency

and productivity (Whiteside, 2008, p. 68 f).

Thus, we have now learnt that the effects of HIV/AIDS on human capital are negative and are

displayed in lower productivity and lower saving and/or investment levels. However, the

epidemic may have positive impacts on the population not affected by the disease.

4. Analysis

4.1. The impact of the factors in the Solow Growth Model

We have now seen that other economists have found proof for or agree with the prediction

that human capital besides savings, investment, population growth and the depreciation of

capital alters the per capita economic growth of economies. We have additionally learnt that

the pandemic affects human capital in both the educational and the health sector as well as in

the labour market where the epidemic results in fewer workers and fewer incentives to invest

in on-the-job training. The pandemic also effects the composition and the size of the

population as well as saving and investment in physical capital. Hence, there are several

channels through which HIV/AIDS can affect GDP per capita.

4.1.1 Saving and investment in physical capital

As a result of the Solow Growth Model’s construction, it describes a positive relationship

between saving and per capita income. This denotes that high saving rates are associated with

a large capital stock and a high level of output. The impact of HIV/AIDS on saving however,

19

is theoretically believed to be negative where the disease lowers the saving rate of the

individual and/or the household. Therefore, the impact of HIV/AIDS on saving can be

expected to decrease the saving rate which would ultimately have an impact on the capital and

output per worker. The effect of a decreased saving rate in the Solow Growth Model is

illustrated in the diagram below and shows changes in physical capital for a given level of

human capital.

Figure 3: Decreased saving rates in the Solow Growth Model

Source: Perkins et al. (2006) Economics of Development. p. 125

The decrease in the saving rate as a result of HIV/AIDS reduces capital per worker from k1 to

k2 which in the long run may result in lower per capita income levels. Moreover, the

decreased saving level also lowers the output per worker from y1 to y2. These changes

indicate that the decreased saving rate is negative for economic growth.

4.1.2 Population

The Solow equation describes a negative relationship between changes in per capita

output/income and changes in population growth. However, as a result of increased mortality

rates because of HIV/AIDS, the population growth of a country rigorously affected by the

20

pandemic can be expected to decrease. A decrease in population growth increases the capital

per worker according to the Solow Growth Model. This is illustrated in the Figure 4 below as

an increase from k1 to k2. The diagram also shows that the decreased population increases the

output per worker in physical capital for a given level of human capital.

Figure 4: Changes in Population Growth

Source: Perkins et al. (2006) Economics of Development. p. 126

We have now learnt that the Solow Growth Model shows decreases in the levels output or

income per worker when there is a decrease in investment and savings in physical capital. If

there is a decrease in the level of population growth on the other hand, the result is increasing

levels of physical capital per worker.

4.1.3 Human capital

From the theories based on Haacker’s research presented above, the impact from a decline in

incentives to invest in education as well as in the human capital of the labour force, can be

expected to decrease the saving function in the Solow Growth Model. Can we then expect the

changes in human capital as a result of HIV/AIDS, to impact economic growth? The decline

in incentives to invest in human capital such as education, as a result of HIV/AIDS mortality

21

is likely to affect the saving and investment function. This change can be believed to be

similar to what we saw when there was a decrease in the saving level for physical capital as

we have assumed that human capital reacts similar to physical capital in the model. This is

illustrated in Figure 5 below. The decrease in investment in human capital could for example

be in the form of less on-the-job training. Additionally, the decrease in the labour force

because of higher mortality rates may also lower the production of firms. Greater illness of

workers could also result in lower efficiency which would decrease the productivity function

in the Solow Growth Model.

Figure 5: The modified Solow Growth Model with changes in saving and investment as a

consequence of HIV/AIDS

The diagram illustrates how a decrease in saving and investment results in lower output per

worker as well as in lower human capital per worker. These changes will eventually result in

a lower total income which likely results in lower economic growth. This further deepens the

decline in both the output and the human capital per worker, for a given amount of physical

capital. Both these changes result in various influences on the human capital as well as the

output per worker which leads to lower levels economic growth.

22

We have now seen that there are different effects on GDP per capita from HIV/AIDS through

the factors in the Solow Growth Model and human capital. Changes in saving, investments

and human capital are expected to decrease the GDP per capita whilst decreases in population

growth are anticipated to result in an increase in GDP per capita. Thus, the total effect to GDP

per capita because of HIV/AIDS is unclear.

4.2 HIV and its impact on economic growth; descriptive analysis

The Solow Growth Model assumes a negative relationship between output per worker,

population growth and diminished levels of investment in physical capital or savings. This

idea gets support from other economist’s theories and investigations. Since the Solow Growth

Model with added human capital have been analysed theoretically, is it possible to find

indications of these predictions in real world statistics? To see whether or not there is a

negative correlation between population growth and GDP per capita, data has been collected

from the 2008 World Development Indicators and the Human Development Report for the

year 2007/2008, both presented by The World Bank. In addition to the region sub-Saharan

Africa, five countries have been selected as parameters. The reason for the selection of these

countries is that these countries are the ones that have been common in investigations done by

other economists, such as those by Haacker. However, these facts do not describe casual

correlations, they are only descriptions from some countries of interest.

However, the result concerning population growth for countries with high HIV/AIDS

prevalence levels is not what the Solow Growth Model assumes. On the contrary, the

projected population growth between year 2005 to 2015 for countries in sub-Saharan Africa is

according to the World Bank’s Human Development Report 2007/2008 positive, with a

population growth of 2.3 percent (The World Bank, Human Development Report 2007/2008,

p. 246). Hence, there is a difference between the implications of the HIV/AIDS pandemic in

the Solow Growth Model and what is projected for the region. This conclusion emphasise that

there are other factors that affect a country’s economic growth prospects and that the

consequences of the HIV/AIDS epidemic are very complex to understand.

Furthermore, several sources have presented that there is a correspondence between HIV

prevalence and per capita GDP growth levels. In order to examine whether there is a

correspondence between these two factors, they must be put opposite each other as well.

23

Table 1 below shows the prevalence level of HIV and the annual GDP per capita growth rate

for the sub-Saharan region and the five selected countries.

Table 1: Prevalence of HIV and GDP per capita growth Prevalence of HIV in 2007 GDP per capita

Country (% of population aged 15-49) Annual growth rate (%) 1990-2005

Sub-Saharan Africa 5,2 0,5

Botswana 23,9 4,8

Kenya 7,8 -0,1

Malawi 11,9 1,0

South Africa 18,1 0,6

Swaziland 26,1 0,2

Zambia 15,2 -0,3

Source: The World Bank, Human Development Report 2007/2008, 2008 World Development Indicators

From the Table 1, it becomes clear that a high prevalence level of HIV is associated with low

and/or decreasing levels of GDP per capita growth. However, this description is simplified

which means that there are several other factors that could impinge on the result and the table

does not describe a causal correlation. The big exception is Botswana who had the second

largest HIV prevalence level and in spite of this had the highest GDP per capita growth

between 1990 and 2005. The annual growth rate in Botswana was 4.8 percent which was

much higher than the average of 0.5 percent in the region. Comparing this with the prevalence

level of 23.9 percent of the working population in Botswana to ”only” 5.2 percent in the sub-

Saharan Africa region, the country is clearly not reacting to the HIV/AIDS pandemic as other

countries are. One explanation for this uncommon development in Botswana may be what

Arndt and Lewis projected in their article from 2000, The Macro Implications of HIV/AIDS in

South Africa: A Preliminary Assessment where they discuss the implications of HIV/AIDS

when not only the size of the economy is reduced but the population is also condensed. They

reach the conclusion that this may lead to increases in GDP per capita (Arndt – Lewis, 2000,

p. 12). Based on this background, it is therefore possible that the high prevalence rate of HIV

in Botswana has had such a condensing effect on the population in relation to the economy

that the income per capita actually has increased.

Another interesting aspect of the effects of HIV/AIDS on economic growth and poverty is its

impact on income inequality. Researchers, for example Haacker, have pointed to a

24

relationship between high prevalence levels of HIV/AIDS and income inequality. Haacker

presents lower investments in education, i.e. human capital, because of poverty and

HIV/AIDS as one factor contributing to the increasing inequality. Furthermore, Piot, Greener

and Russel also investigated income inequality and its relation to HIV prevalence. They found

a strong correlation which was presented in Figure 1. In order to see whether their findings

correspond to present data, the data in Table 2 below will be used.

Table 2: Income inequality and HIV/AIDS

Prevalence of HIV in 2007 Gini Index (0-100)

Country (% of population aged 15-49)

Botswana 23,9 60,5

Kenya 7,8 42,5

Malawi 11,9 39,0

South Africa 18,1 57,8

Swaziland 26,1 50,4

Zambia 15,2 50,8

Source: The World Bank, Human Development Report 2007/2008, 2008 World Development Indicators

From the Table 2 above, it can be said that there seems to be a weak positive correlation

between income inequality and HIV prevalence although the data does not illustrate a causal

correlation. This finding supports other research which states that HIV is part of a vicious

circle since the impacts of HIV/AIDS enhance poverty and social deprivation while these

factors in turn increase vulnerability to HIV. The reason for a much weaker correlation

between HIV prevalence levels and the Gini coefficient compared to Piot, Greener and

Russel’s result, is that Table 2 presents fewer countries in comparison as well as that the data

used may differ.

From these comparisons with real world data and theories concerning the impact of

HIV/AIDS on factors of the Solow Growth Model we have seen that there seems to be

important aspects to consider for the countries affected by the epidemic. Unfortunately, many

countries suffer the consequences in more than one factor. This descriptive analysis

strengthens the projection that HIV/AIDS affect economic growth for countries with a high

HIV prevalence level in the population. Although the Solow Growth Model considers several

25

factors that can influence economic growth, there are aspects not taken into consideration.

One of these aspects is differences between gender.

4.3 Gender, HIV/AIDS and economic growth

We have now analysed the effects from HIV/AIDS on per capita economic growth and seen

that one consequence of HIV/AIDS is income inequality. However, another important issue

has been excluded, namely gender inequality. Therefore, we shall now look into how this

factor is affected by HIV/AIDS and economic growth.

There is a strong gender aspect of HIV/AIDS. First of all, women constitute the majority of

the people infected with HIV, 57 percent in sub-Saharan Africa. In addition, women also

carry a heavy burden of HIV/AIDS as they are the ones taking responsibility for the care of

those who are ill – on top of a heavy workload. Furthermore, when a husband dies, it is

possible that the woman lose their assets including land and households that continue with

their farming after the husband dies, usually have lower per capita incomes than when the

husband was alive (Bigsten – Durevall, 2008, p. 10, 11).

According to Bonnel, income inequality and gender makes societies more vulnerable to HIV

because a woman who is poor relative to men, will find herself exposed to a greater risk of

being infected with the virus. In addition, he argues that the empowerment of women through

greater economic independence is associated with a lower HIV prevalence rate (Bonnela,

2000, p. 8).

Moreover, research has shown that gender relationships matter for economic development

which can easily be illustrated through education, where human capital suffers, as girls are not

given the same opportunity to study as boys. This affects the overall economic and

developmental performance of countries since there are several economic externalities

deriving from female education, for example reduced child mortality and reduced fertility,

which in the long run indirectly affects per capita economic growth (Bigsten – Durevall,

2008, p. 46). Likewise, the education of women reduces the spread of HIV/AIDS in a larger

extent than the education of men (Perkins et al., 2006, p. 294).

26

What does these facts contribute with to the economic growth and poverty reduction picture

in the light of HIV/AIDS? The facts conclude that women are in a worse position than men

when it comes to HIV/AIDS since they are more vulnerable for infection but also since they

are the ones carrying a heavy burden of the AIDS care. Since women are not as often part of

the labour force nor owners of assets, it is likely that the decreases in capital and/or output per

worker are deeper for women than for men in the Solow Growth Model since they are likely

to start at a lower position.

From the facts presented above, it can be concluded that there is a need for female

empowerment since this would contribute to a pathway out of poverty. In addition both

Bonnel, Bigsten and Durevall argue that increased female empowerment through different

forms will lead to decreased levels of HIV prevalence. This would in turn, under the

assumption that HIV/AIDS is part of a vicious circle that deepens HIV infection and poverty,

mean that both the spread of the pandemic as well as poverty levels could be reduced.

Hence, as the Solow Growth Model does not consider the gender aspect, there are

implications for the analysis. Thus, it is important in future investigations to illustrate these

changes and to consider different situations.

5. Discussion

The analysis presents theories supporting the parameters of the Solow Growth Model; that

saving is positively related to economic growth whilst population growth and depreciation are

negatively related to economic growth. Additionally, several economists have stated and

shown support for the theory that human capital is a supplementary factor that has a

significant effect on economic growth since it affects the output of the companies through for

example, changes in production.

Decreasing saving rates clearly have a negative effect on economic growth since no rents that

can contribute to economic growth is created. Not only saving rates in themselves are affected

by the poverty in the sub-Saharan Africa region. Haacker and Salinas argue that the high

morbidity and mortality that results from HIV/AIDS discourages saving. This results in even

lower saving levels in the region which intensifies poverty and prohibits economic growth. In

addition it also discourages investment in human capital. Nevertheless, the Solow outline does

27

not consider human capital in its original form and since several economists have raised the

issue whether this should be taken into consideration or not and found that human capital is an

important factor for economic growth, there is a need for a more thorough equation. This

should in turn take into account saving and investment in physical capital, changes in

population growth, depreciation as well as human capital. From the modified framework of

the Solow Growth Model where human capital has been added, it is evident that the

consequences of HIV/AIDS can be severe. Hence a country relentlessly hit by the HIV/AIDS

pandemic will suffer in numerous ways from the outcomes of the disease – many of which in

the long run will affect economic growth negatively.

Furthermore based on the increased mortality levels because of HIV/AIDS, the population

growth of a country with a high prevalence of HIV can be expected to decrease. According to

the Solow Growth Model, decreased population levels have a positive impact on per capita

output or capital, a result equal both for physical and human capital. However, countries

severely affected by HIV have not showed decreased population growth levels nor negative

growth rates. For example, Botswana who had a HIV prevalence of 23.9 in 2007 had a

population growth of 1.2 percent (The World Bank, 2008 World Development Indicators,

2007/2008 Human Development Report, p. 245). Besides, the country has had a per capita

GDP growth of 4.8 percent for the last fifteen years. In The Macro Implications of HIV/AIDS

in South Africa: A Preliminary Assessment Arndt and Lewis conclude that HIV/AIDS both

reduces the size of the economy and condenses the population which is believed to increase

GDP per capita. This hypothesis may be what we can see in Botswana. Nonetheless worth

noting, is that Kenya, who had the highest population growth rate among the countries

selected, also showed a negative per capita GDP growth (The World Bank, Human

Development Report 2007/2008). This indicates that the Solow theory of a negative impact on

economic growth through population growth may correspond not only in theory. The idea that

high population growth contributes to low levels of GDP per capita is a common economic

theory for example expressed by Mankiw and Taylor. Additionally, the most evident trend for

countries in sub-Saharan Africa seem to agree with the Solow Growth Model equation where

population growth has a negative effect on per capita GDP, since the population growth in the

region has been around 2.3 percent and the GDP per capita growth has been only 0.5 percent

(The World Bank, Human Development Report 2007/2008). This concludes that the total

effects from HIV/AIDS on economic growth are unclear since the effects on saving and

investment, the production function and human capital are negative while the effect on the

28

population should increase economic growth. Hence I believe it is reasonable to conclude that

a high population growth may not enhance economic growth although it may not be an

obstruction either.

The overall negative influence of HIV/AIDS on per capita GDP and economic growth seem

to be corresponding generally except for Botswana where per capita changes in GDP have

been very high even tough the country has one of the highest HIV prevalence levels. The

reason behind different outcomes must therefore be a result of other factors cooperating

together, which leads to devastating effects in countries with already high HIV prevalence

levels and low per capita economic growth. This conclusion is a result of an unclear total

effect from HIV/AIDS on economic growth since there are both positive and negative effects

of the epidemic and we cannot know which effect that dominates. Therefore, it must be

concluded that HIV/AIDS is not necessarily as devastating as one could predict although most

countries affected suffer deeply.

Furthermore, several theories have indicated that HIV/AIDS undermines not only economic

growth but that it also enhances income inequality, undercuts economic development and

poverty reduction and deepens gender inequality. The evidence from this analysis supports

the theory of an increased income inequality as a result of HIV/AIDS since Table 2 shows a

weak correlation between these two factors. HIV/AIDS can therefore be said to be part of a

vicious circle. This conclusion is besides more evident for women who are more vulnerable

for the disease both biologically and economically.

Nonetheless, all economic theories concerning the effects of HIV/AIDS on economic growth

do not agree and the empirical evidence from countries in sub-Saharan Africa indicate

different patterns where some deviate in more than one aspect from the theories. This

emphasise the fact that the economic consequences of the HIV/AIDS pandemic may not be so

easy to deal with.

6. Conclusion

The aim of this analysis has been to investigate how the HIV/AIDS epidemic affects the

economic growth performance of countries in sub-Saharan Africa, the poorest as well as the

region most severely affected by HIV/AIDS in the world.

29

The material shows that factors commonly believed to influence economic growth such as

saving rates, investments, changes in the composition and the size of the population as well as

the depreciation of physical capital are factors influencing economic growth. However, other

theories bring forward arguments that investments in human capital and changes to this

parameter may also affect the economic growth process. As a result of these theories, the

Solow Growth Model framework was altered to also consider the effect from HIV/AIDS on

human capital since it has been argued that this parameter is an equally important factor

influencing the economic growth process.

The fact that several factors considered to be important for economic growth also emerge to

be affected by the HIV/AIDS epidemic, underlines the fact that the impact of the disease may

be severe and difficult to pin point. Besides, it implies that several factors may suffer from the

effects of the pandemic. This is emphasised in the negative trends the disease can cause on

economic growth, since the growth process is built up of other factors which can be

negatively affected or depressed by the disease.

The research question for this thesis has been; how does HIV/AIDS affect the economic

growth process in sub-Saharan Africa according to the Solow Growth Model? My conclusion

is that the total effect of HIV/AIDS on economic growth according to the Solow Growth

Model when also considering human capital is unclear. This is a consequence of the fact that

there are both positive as well as negative effects from the epidemic on economic growth and

we cannot know which effect that dominates.

However, the Sub-Saharan Africa region does not show the pattern for population growth that

is predicted from high mortality rates as a cause of a deadly disease namely, a diminished

population. This illustrates that the impact on societies affected by the disease may be altered

by other factors than merely the HIV/AIDS epidemic. Moreover, the analysis also found

results stating that there are gender inequalities being worsened because of HIV/AIDS since

women are more disprivileged both economically and biologically. Accordingly, the analysis

supports the theory that the epidemic increases income inequality.

Hence, since HIV/AIDS undermines essential macroeconomic factors that contribute to or

influence economic growth, it can obstruct the per capita economic growth process and

poverty reduction in sub-Saharan Africa and increase inequalities.

30

7. Summary

This thesis has discussed how the HIV/AIDS epidemic affects the economic growth

performance for countries in sub-Saharan Africa, where income is low and there is a high

prevalence level of HIV.

By focusing on the parameters of the Solow Growth Model the analysis aims to answer the

research question; how does HIV/AIDS affect the economic growth process in sub-Saharan

Africa according to the Solow Growth Model? After considering the parameters of the theory,

the conclusion was made that there was a need to adjust the framework to include human

capital, which in the Solow model was assumed to act alike physical capital. Hence, the focus

of the analysis has been the relationship between per capita economic growth and the

prevalence level of HIV/AIDS through a focus on three areas; saving and investment in

physical capital and in human capital as well as changes in the size of the population.

By looking at material presented by different development organisations such as the World

Bank, The International Monetary Fund, the Joint United Nations Programme on HIV/AIDS

(UNAIDS), and articles from different scientists and economists’ description of the obstacles

and the possibilities concerning HIV/AIDS and economic growth, the aim has been to get a

good picture of the current situation in sub-Saharan Africa. Most of the research conducted

emphasise that HIV/AIDS have negative effects on important parameters for economic

growth that are part of the Solow Growth Model as well as human capital. Statistic evidence

form countries in sub-Saharan Africa support this although there are some exceptions, for

example does not Botswana’s high HIV prevalence level appear to have led to a decline in per

capita GDP growth. The conclusion of the thesis is that there is an unclear total effect from

HIV/AIDS on economic growth as there are factors being both negatively and positively

effected by the pandemic and we cannot know which one that dominates. The overall trend

for the region is however that HIV/AIDS appear to be associated with low per capita

economic growth.

The connection between income inequality and HIV prevalence has additionally been brought

forward as a macroeconomic aspect of the pandemic. This underlines the fact that once a

country is affected by the pandemic, it becomes part of a vicious circle where HIV/AIDS

31

undermines economic growth and increases poverty that in turn increases vulnerability for

HIV infection.

In other words, the analysis has led to the conclusion that HIV/AIDS has an unclear effect on

the economic growth process that is described in the Solow Growth Model when human

capital is added to the framework. This is an outcome of factors in the framework being both

positively and negatively effected by the epidemic and it is unclear which of these effects that

dominate. In addition, the situation is more severe for women in sub-Saharan Africa as a

result of higher biological vulnerability to the infection as well as less empowerment and

fewer employment opportunities, which hampers the prospects of increased per capita

economic growth.

In conclusion, there are several factors that are important for economic growth that are being

affected by the HIV/AIDS epidemic. Since severely affected countries are influenced in more

than one parameter, the consequences may develop into brutal undercuts of economic growth

and development. Additionally, because women suffer more harshly from the consequences

of the disease, their pathway to higher per capita income levels and away from poverty is

harder to achieve than for men. This is thus an important area for further research.

List of references

Printed sources

The World Bank (2007/2008) Human Development Report 2007/2008. Washington D.C.

The World Bank (2008) 2008 World Development Indicators. Washington D.C.

The World Bank (2008) Poverty Data. A Supplement to World Development Indicators 2008.

Washington D.C.

UNAIDS (2008) Report on the global HIV/AIDS epidemic 2008: executive summary. Joint

United Nations Programme on HIV/AIDS. Switzerland.

UNAIDS/WHO (2007) Slides and graphics: global summary of the AIDS epidemic 2007.

Available [online]:

<http://data.unaids.org/pub/EPISlides/2007/071118_epicore2007_slides_en.pdf>

[28 april 2009 at 11.08]

Literature

Ahwireng-Obeng, F., Akussah, G. (2003) The Impact of HIV-AIDS on African Economies.

Africa Institute of South Africa. Research Paper no 67. Pretoria, South Africa.

Bigsten, A., Durevall, D. (2008) The African economy and its role in the world economy.

Current African Issues. No. 40. Nordiska Afrikainstitutet. Uppsala.

Elbadawi, I. A., Ndulu, B. J. (editors) (2001) Economic Development in SubSaharan Africa.

The African Economic Research Consortium. IEA Conference Volume No. 129. Palgrave in

association with African Economic Research Consortium and International Economic

Association.

Mankiw, N. G., Taylor, M. P., (2008) Macroeconomics. European Edition. Worth Publishers.

New York.

33

Perkins, D, H., Radelet, S., Lindauer, D. L. (2006) Economics of Development. Sixth Edition.

W.W. Norton & Company. New York and London.

Whiteside, A. (2008) HIV/AIDS: A Very Short Introduction. Oxford University Press. Oxford.

Articles

Arndt, C., Lewis, J.D., (2000) The Macro Implications of HIV/AIDS in South Africa: A

Preliminary Assessment. The World Bank. Washington D.C.

Bonnel, R. a (2000) HIV/AIDS: Does it Increase or Decrease Growth in Africa? ACT Africa.

The World Bank. Washington D.C.

Bonnel, R. b (2000) HIV/AIDS and Economic Growth: A Global Perspective. South African

Journal of Economics. Volume 68, Issue. 5. p 360-379

Dixon, S., McDonald, S., Roberts, J. (2002) The impact of HIV and AIDS on Africa’s

economic development. BMJ volume 324. 26 January 2002.

Haacker, M. (2002) The Economic Consequences of HIV/AIDS in Southern Africa.

International Monetary Fund. IMF Working Paper WP/02/38. Washington D.C.

Haacker, M., Salinas, G. (2006) HIV/AIDS: The Impact on Poverty and Inequality.

International Monetary Fund. IMF Working Paper WP/06/126. Washington D.C.

Piot P, Greener R, Russell S (2007) Squaring the Circle: AIDS, Poverty, and Human

Development. PLoS Med 4(10): e314. doi:10.1371/journal.pmed.0040314

Available [online]:

< http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0040314> [3 May 2009

at 16.01]

Whiteside, A. (2002) Poverty and HIV/AIDS in Africa. Third World Quarterly. Vol. 23 No. 2,

Global Health and Governance: HIV/AIDS p. 313-332.

34

Internet

USAID Africa: Health and Family Planning.

Available [online]:

<http://www.usaid.gov/locations/sub-saharan_africa/sectors/health/index.html> [28 April

2009 at 11.44]