DEPARTMENT OF ECONOMICS Uppsala University Thesis C Author: Johanna Ekhagen Supervisor: Karin Edmark Term and year: Spring 2009

Transcription

1 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 2

3 Table of Contents 1. Introduction Aim and research question Theoretical delimitation Previous and current research Method Material Theory The Solow Growth Model Empiricism The impact of HIV/AIDS on saving and investment in physical capital The impact of HIV/AIDS on the population The impact of HIV/AIDS on human capital Analysis The impact of the factors in the Solow Growth Model Saving and investment in physical capital Population Human capital HIV and its impact on economic growth; descriptive analysis Gender, HIV/AIDS and economic growth Discussion Conclusion Summary List of references

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 HIV 1 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 AIDS 2 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 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 4

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 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? 5

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 highprevalence 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 6

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 7

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 8

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 9

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. 10

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=s k y (n+δ k )k 11

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 δ k k (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, s k y which shows saving per capita, and the third curve is the line (n+δ k )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 12

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; s k y =(n+δ k )k. At this stage, investment has two purposes. The part, δ k k 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). 13

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 14

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 s h represents saving and investment in human capital, and δ h is the depreciation rate for human capital. This can be written as: Δh=s h y (n+δ h )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=s k y (n+δ k )k which shows the effect on physical capital per worker and: Δh=s h y (n+δ h )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. 15

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 ). 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). 16

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). 17

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 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, 18

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 k 1 to k 2 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 y 1 to y 2. These changes indicate that the decreased saving rate is negative for economic growth 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 19

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 k 1 to k 2. 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 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 20

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. 21

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. 22

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 (%) 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 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 23

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 24

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). 25

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 26

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 27