Economics of HIV and AIDS Research Paper

Economics of HIV and AIDS Research Paper

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The economics of HIV and AIDS is a strange creature. There is no so-called economics of mumps or economics of appendicitis. It is of course associated with sex, but then so are syphilis and gonorrhea, yet there is no economics of syphilis or even an economics of sexually transmitted infections. The difference lies in not only the fact that the virus is most often transmitted through sexual intercourse, an activity intrinsic to our humanity and therefore of universal interest, but also the fact that its presence is not always obvious, the consequences if untreated are fatal within only a few years, and there is as yet no known cure. It is therefore alarming in both its mode of transmission, striking at the very heart of one of our most intimate and pleasurable activities, and its catastrophic impact at the personal level. Because it affects adults who in many cases will be key household income earners, it also has profound social implications. Its impact on labor morbidity, productivity, medical and insurance costs, and public health expenditures affects business efficiency and a number of macroeconomic variables such as savings, labor and capital productivity, and private and public borrowing, and it raises important issues of the role of the state in prevention, care, and treatment. When the behavioral aspects of the risks of infection are included, then it is clear that it is a topic of considerable interest to economists.

To say that HIV is transmitted primarily through sexual intercourse is a reflection of its most common mode of transfer. More generally, the virus is transferred from one person to another by means of one person’s bodily fluids entering another’s bloodstream. It has a brief survival period out of the body and cannot be transferred via normal healthy skin contact, saliva, perspiration, or mosquito bites. The most common means are through heterosexual intercourse, homosexual intercourse, intravenous drug (IVD) ingestion by infected needles, and occasionally through contaminated blood products in a hospital or clinic environment. By far, the most common of these globally is the first, with a predominance in Africa, especially southern Africa where adult prevalence rates of above 20% are common, though IVD is an increasingly important source in former eastern bloc countries of Europe, central Asia, and India. In North America and western Europe, heterosexual, homosexual, and IVD have roughly equal weight as sources of infection but collectively amount to less than 1% of the relevant adult populations.

It is useful, before proceeding to a review of economic analysis in the area, to summarize the main characteristics of the disease. Only from 4 to 6 weeks following infection, and sometimes up to about 3 months later, can the presence of the HIV virus be detected. During this period, there will be no outward symptoms apart from a brief flulike illness, but the victim will be highly infectious. There then follows a period of 5 to 7 years when the HIV virus eats away at the infected person’s immune system. As this process develops, the individual becomes gradually weaker, in due course becomes highly prone to opportunistic infections such as TB and pneumonia, and if left untreated, will generally die within about 10 years. In the context of the developing world, death tends to occur sooner because of poorer general nutrition and greater environmental health hazards. For biological reasons, women are more likely to be infected than men (that is, the transfer from an infected man into the vagina is more probable than the reverse). Morbidity and mortality thus tend to follow infection after a lag of some 5 to 10 years, making for a complex epidemiological cycle.

There is no cure, but a number of drug combinations are available that when taken regularly and continuously for life will raise and keep the individual’s immune system at a level such that his or her life expectancy is considerably extended, though the individual will always remain HIV positive. Often, there are side effects that entail a shift to what are termed second line drugs, which tend to be more expensive. There is also around a 30% probability that a child born to an infected woman will be HIV positive. Treatment through intake of antiretroviral drugs can be costly, and there are important debates on international trade in pharmaceuticals concerning the rules of the WTO regarding which patent rights may be protected and when producers of generic supplies may legitimately trade. The research paper returns to this in a subsequent section.

For economists, all this gives rise to three broad areas of interest. One is the impact of HIV and AIDS on the economy at the macro, sectoral, or individual business level. The second concerns the choices made by individuals that expose them to the risk of infection and the consequences at household level, and the third is concerned with the whole area of public response, the role of the state, and the potential impact on public expenditure and taxation. A number of other issues arise from these, including the role of the social and institutional environments, the availability and cost of the drugs on which treatment depends, and the impact of stigma. The existing literature is composed of a very large number of heterogeneous papers, from which only a small representative selection is possible here. Although there are few classics specific to HIV and AIDS, most analysis draws on mainstream theory and its classic works.
Impact on the Economy

This is a disease that principally affects sexually active adults, and to the extent that they are disabled by it, there is an impact on labor productivity and economic output. A simple list includes reduced productivity while at work through fatigue, increased absenteeism, higher than normal attrition rates and costs of recruitment, loss of skills, and time off to attend funerals, care for sick family members, and attend them in the hospital. Intergenerational effects will also appear as children in many poor communities are withdrawn from school and adult skills are not passed on (Bell, Devarajan, & Gersbach, 2004). At the macroeconomic level, these microeffects manifest themselves in reduced savings levels, reduced size of labor force (varying by sector and skill level), impact on public health expenditure, inflation due to increased business costs (group medical insurance, taxation, frequent recruitment), and possibly increased government borrowing, leading in turn to increased imports, balance of payments, and exchange rate problems. It is clear that in countries such as South Africa, Botswana, Zimbabwe, and Zambia, where HIV prevalence rates have exceeded 20% of adults between the ages 15 and 49 for most of the twenty-first century to date, the macroeconomic impact is likely to be considerable.

The most common ways in which attempts have been made to measure the macroeconomic impact of HIV and AIDS are either by cross-country econometric estimation or by application of macroeconomic models of varying degrees of complication (for reviews, see Haacker, 2004a, and Booysen, Geldenhuys, & Marinkov, 2003). Econometric estimation takes the form of including an HIV variable among others conventionally seen as affecting economic growth, such as savings rates, private investment, and education levels of the labor force. This approach, although able to produce statistically significant results (e.g., McDonald & Roberts, 2006), is less satisfactory as an explanatory or predictive tool than macroeconomic growth models that contain behavioral equations. The simplest of the latter start from the traditional textbook Cobb-Douglas type of production function, where output is a function of capital and labor (taking a variety of mathematical forms entailing different assumptions). These use aggregate data on capital stock (by value) and labor and insert assumptions on the impact of HIV and AIDS on these input factors to estimate the effect on productivity and output, thus having two basic growth scenarios: with HIV and AIDS and without. The basic model can be extended to include several skill levels of labor and, important in the case of many developing countries, the formal and informal labor markets. The following is a simplified version of an example from an application in Botswana, a country with one of the highest rates of HIV infection in the world:

economics-of-hiv-and-aids-research-paper-formwhere Y is output, Es and Eu represent labor supplies of skilled and unskilled labor, respectively, and K is the capital stock. The shares of output attributable to each factor are Bs, Bu, and p= 1-Bs -Bu. An exogenous technological trend is represented by yt (Econsult, 2006; Jefferis, Kinghorn, Siphambe, & Thurlow, 2008). The authors then explore the principal ways in which HIV and AIDS are likely to affect the labor supply and the capital stock and feed this into the model. The impact on labor supply will be affected by the degree of availability of antiretroviral treatment (ART), which requires additional assumptions. Other assumptions underlie the validity of such models in representing economic behavior. They assume, for instance, that the economy responds to changes in factor prices and that markets will clear, but they also usually assume constant returns to scale and a fixed rate of factor substitution. The authors of this study on Botswana concluded that the annual growth rate of GDP at market prices from 2001 to 2021 would be 4.5% in the absence of AIDS, 2.5% with AIDS, and 3.3% with AIDS plus ART (Econsult, 2006, p. 55, Table 5.3).

An interesting extension of this approach is where the concept of health capital is introduced as an additional capital variable. McDonald and Roberts (2006), for instance, incorporate (in an augmented Solow model) technological change and labor, plus physical, education, and health capital. Health capital itself is defined in a reduced-form equation as a function of lagged per capita income, education capital, nutritional status, HIV and AIDS prevalence, and proportion of the population at risk of malaria in a cross-country analysis. Proxies for health capital (the dependent variable) are life expectancy at birth and infant mortality rate. The results of the statistical analysis for the African sample indicated that a 1% increase in the HIV prevalence rate was related to a 0.59% decrease in income per capita. For the world sample, the decrease in income per capita was 0.5%, and for the developing world sample, it was 0.8%, each case having been brought up by a suspect high rate for Brazil.

An alternative means of estimating the impact of HIV and AIDS on the macroeconomy, which attempts to deal with the more complex and more realistic situation where the economy is broken down into a number of interacting sectors, emerged during the second part of the twentieth century in the form of computable general equilibrium (CGE) models for forecasting macroeconomic outcomes. As the name indicates, these models are (or claim to be) computable and hence testable versions of general equilibrium models of an economy. That is, they are versions of mathematical models in which the macroeconomy is the product of a number of behavioral decisions by consumers and producers at the microlevel of supply and demand in individual markets. The theoretical foundations of such models are found in the work of Walras, Arrow, Debreu, and others in the early and mid-twentieth century and are reflected in a substantial literature on the conditions that determine the possibility and existence of a general equilibrium in which demand equals supply across all markets freely and simultaneously. From this body of theory and the development of increasingly powerful computer capacity, economists working in economies where there is an abundance of current and historical data have been able to evolve ever more sophisticated computable models based on this theoretical foundation.

In practice, however, the degree to which many applications do in fact adequately recognize and incorporate the variety of experience at a microeconomic level has been questioned (Booysen et al., 2003; Johnston, 2008; Mitra-Khan, 2008). The focus in most applications of specific country forecasts of macroeconomic growth rates and associated variables (for example, by the IMF and World Bank) leads unavoidably to the primacy of macroeconomic and aggregated sectoral data sources, most frequently in the form of a social accounting matrix (a matrix representation of the national accounts of a nation, indicating the flow of activities from one sector to another). Even at this level, the data demands are considerable, and for many of the countries most affected by AIDS, the data are inadequate. Botswana is one of the better-off in this respect, and in the study referred to previously, the results of a CGE model with 26 productive sectors, 5 occupational categories, 3 regional areas, and a male-female breakdown are that the rate of growth of GDP from 2003 to 2021 would be 4.6% in the absence of AIDS, 3.0% with AIDS, and 3.4% with AIDS plus ART (Econsult, 2006, p. 101, Table 9.2).

Much of the work on applying CGE models to the macroeconomic impact of HIV and AIDS on an economy has taken place in South Africa, where the availability of data and local economic expertise, combined with levels of HIV prevalence above 20%, have stimulated much activity with the appearance of a number of such models. Some of these are demand-side driven, some are supply-side driven, and others have used a human capital approach. In a detailed review by Frederik le Roux Booysen et al. (2003) two of these (by ING Barings and the Bureau for Economic Research) are shown to forecast not only a difference in annual real growth of the South African GDP between an AIDS and no-AIDS scenario of-0.5 to -0.6 percentage points, but also a difference in predicted average annual growth in real per capita GDP of 0.9 percentage points in each model. The latter, in other words, is saying that real per capita growth in GDP is 0.9% higher in the presence of HIV and AIDS than without it. This seemingly perverse conclusion is created where the population growth rate is lower, as a result of HIV and AIDS, than growth in GDP. On the other hand, a CGE application to the Indian economy in 2006 concluded that the real GDP per capita growth rate between 2002 to 2003 and 2015 to 2016 was 6.13% with AIDS and 6.68% in the no-AIDS scenario. Real GDP itself was predicted to grow at 7.34% with AIDS, compared with 8.21% without AIDS, a difference of 0.87 percentage points (Ojha & Pradhan, 2006, Table 1). The latter is slightly higher than the corresponding figures for the growth rates with AIDS and without AIDS in South Africa, but too much should not be made of the differences since they will reflect different assumptions and specifications in the models and differences in the respective economies themselves.

Although these various models exhibit a high degree of mathematical sophistication, their output depends nevertheless on the quality of the data that is inputted. This includes the accuracy of existing measures of HIV prevalence (by which is usually meant the percentage rate of infection among adults aged between 15 and 49), which in most countries can be estimated from only a number of indicators since not all those infected will have come forward to be tested. In many developing countries, moreover, testing facilities are few and far between, and causes of death are often put down to an opportunistic disease such as TB or malaria. The most reliable figures historically have tended to come from testing of pregnant women at antenatal clinics, from which extrapolation, based on various assumptions, is made to the adult population as a whole. The introduction of mobile testing equipment has enabled more accurate prevalence rates to be gathered through house-to-house surveys, but accurate measurement still remains a problem in many countries, especially if there is a recent history of civil disorder.

Such data uncertainty also makes it difficult to forecast the epidemiological progress of the disease and hence the likely impact on the labor force, especially when possible behavioral changes in response to public-awareness-raising campaigns are taken into account. Equally uncertain is the timing of the appearance of AIDS, which will depend on the degree to which ART is likely to be available in 10 to 20 years’ time, its adherence rates, and the likely costs to the public health services. There is also in many countries a relative absence of reliable and relevant micro-economic information, such as the effect of HIV and AIDS on labor morbidity and productivity, for the purposes of the macroeconomic models. Will labor productivity be reduced by 20%, 30%, or even 50% by the HIV epidemic in certain countries? Assumptions very often have to be made on the basis of very little empirical evidence, and conclusions must be tested for their sensitivity to different assumed values.

The accuracy of the forecasts of such models on the macroeconomic impact of HIV and AIDS has also been questioned on the grounds that the division of labor in many countries is heavily genderized and that the impact at household level differs depending on whether an adult man or an adult woman (and in either case, a household head) is hit by AIDS. Evidence suggests that a higher proportion of female nonagricultural workers in sub-Saharan Africa are in the informal sector than the corresponding figure for men, and thus, that to the extent that women tend be more susceptible to HIV, the impact on the informal sector (which is substantial in many developing countries) will be understated by models that do not recognize the gendered segmentation of the labor market. On the other hand, where the burden of maintaining household production falls on women, their productivity is likely to increase, and hence, the negative impact will tend to be overstated (Johnston, 2008). This example illustrates the importance of understanding institutional and cultural constraints at microlevel.

Moreover, in addition to these obvious direct monetary costs of an epidemic, including both internal and external, there are welfare losses that are less easily measurable. For an individual infected by HIV who doesn’t receive treatment, there will be not only a loss of income earning ability but also the loss of years of life and quality of remaining years. Nicholas Crafts and Markus Haacker (2004) illustrate this in a standard utility curve diagram in which expected lifetime utility is a function of annual income and life expectancy. The effect of HIV infection is to move the individual to a lower utility curve, at a point where both income and life expectancy are lower than before. Thus, the fall in income alone does not capture the total welfare loss to the infected individual. The authors then develop this model algebraically and use estimates of the value of a statistical life (VSL) to estimate the welfare effect of increased mortality across a sample of AIDS-affected countries. The VSL is a concept that measures the value of a variation in the risk of death and has been frequently estimated by surveys on individual willingness to pay for a given reduction in that risk. Given some qualifications regarding the paucity of data to estimate VSL in many developing countries, the authors show that the total welfare loss to countries such as South Africa, Zambia, and Botswana could range from 67% to 93% of each country’s GDP (Crafts & Haacker, 2004, Table 6.2). Other theoretical work on welfare includes highly mathematical models (such as overlapping generations models) on the optimum control problem of social planners as they allocate limited resources in an economy to control an HIV epidemic at the cost of reduced levels of consumption (Shorish, 2007).
Choices and Behavior of Individuals

As the discussion in the previous section indicated, any model of general equilibrium, or one that explicitly recognizes the links between consumers and producers at the microeconomic level and their aggregate impact in macro-economic terms, must begin with assumptions about microlevel behavior. The common theoretical benchmark of a perfectly competitive equilibrium depends on a number of structural axioms, such as each consumer and producer having perfect knowledge, being a price taker, and striving to maximize either utility (satisfaction) or profits; diminishing marginal utility and diminishing marginal rates of substitution between goods demanded by the consumer and between factors of production used by the producer prevail (that is, indifference curves and isoquants are concave and production functions are convex); resources being perfectly mobile; and transaction costs being zero. Many if not most of these require modification to reflect real-life situations. The sort of rational individual they imply is traditionally referred to in the literature as homo economicus, or economic man, an expression criticized by many feminist economists as much for its conceptual roots as for its terminology.

The relevance of this to individual behavior in the context of HIV and AIDS may not be immediately obvious, but a moment’s reflection shows that the sexual relationship is one in which each person concerned is making a choice between alternatives that have a number of possible outcomes. One set of outcomes in particular may affect the individual’s health and hence future lifetime income. A common starting point for analysis at this microlevel is provided by human capital models in which individuals invest in education and health in order to enhance their future stock of health capital (and hence income earning opportunities) and the general quality of their own lives and those of partners and near relatives. In doing so, they are forced to make choices between work and leisure, between activities that improve health or that have the potential to reduce it, and between more medical insurance and reduced current consumption and vice versa. These all lend themselves to traditional analysis of utility maximization, duly time discounted and adjusted for uncertainty, and many models of this type derive from original work by Michael Grossman (see Folland, Goodman, & Stano, 2007, for a summary). In the case of HIV uncertainty takes the form of ignorance about a partner’s HIV status, of the probability that they may be seropositive, and of the risk of becoming infected through a single act of intercourse. Unless the partner is in an advanced stage of AIDS, it is impossible to tell visually if he or she is infected, and hence, the exchange takes place in a context of incomplete information. In economic welfare terms, and somewhat unromantically and at its simplest, mutually agreed sexual intercourse involves an exchange of access to the most intimate parts of one’s body in order to achieve an anticipated sensual satisfaction, whether or not money is present, and as such has the potential to be Pareto improving, except for the fact that complete information is absent in one or both of the parties to the exchange (Gaffeo, 2003).

Various mathematical models of microlevel behavior

Economics of HIV and AIDS Research Paper
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