“Two Decades of Human Development” by Vignesh Ashok
The objectives of growth
Since its emergence in the second half of the twentieth century, the field of development studies has tried to answer two questions: what is the end-goal of human development and how can we achieve it? The former question is addressed in the 1990 Human Development Report that calls for the “widening [of] people’s choices and their level of achieved well-being” (United Nations Development Programme 1990, p. 10). The report claims to distinguish itself from its predecessors by viewing growth in income as only one of the many components of development. Its central argument rests on the idea that economic growth indicators, such as Gross National Product (GNP) and Gross Domestic Product (GDP), do not sufficiently reflect the plurality of concerns surrounding human development. To address this, the UNDP introduced the Human Development Index (HDI), a composite metric that aims to reflect the capabilities of a collective by incorporating three dimensions that are equally weighted: life expectancy, knowledge and standard of living (United Nations Development Programme 2007/2008, p. 355).
The criticisms leveled against the HDI are predominantly centered on two broad themes. The first is that the HDI, while ostensibly aiming to be a better measure of human development, simply repackages traditional assessments of development based on economic growth under a new label (Srinivasan 2001; Gelman 2009; Wolfers 2009). The second criticism, based on the mathematical computation of the index, relates to the paradoxical results that are obtained when boundary conditions are encountered (Noorbaksh 1998). While both these criticisms have been popular, neither has thwarted the widespread use and increasing prevalence of the HDI.
Despite the HDI being widely used to influence both policy decisions and academic research in the field of development, the proponents of the composite metric have been unable to show why a composite measure is better than several independent measures of human development. In this paper it is argued that while it is necessary to factor in measures other than GDP and GNP, a single composite measure of human development does not accurately prioritize developmental concerns. It encourages the belief that an HDI-rated stage of development univocally determines the optimal set of policy responses irrespective of the HDI metric’s components.
Focusing on the developing world, it will first be shown that income growth alone cannot improve the ‘capabilities’ of an individual, where ‘capabilities’ are defined as the substantive freedoms necessary to enable individuals to enjoy the kind of life he or she values (Sen 1999). Second, it will be shown that the philosophical grounding for the rejection of purely economic indicators of development also apply to composite metrics such as the HDI. Furthermore, it will be argued that it is often the case that progress can only be achieved by prioritizing certain capabilities; hence a case-by-case approach to development sets minimum standards of attainment for each developmental concern and better describes the endogenous relationships between different concerns. In essence, this paper argues for the replacement of the HDI with several independent measures, each reflecting progress made on distinct problems that obstruct development.
Beyond the economy: do economic growth indicators give us the whole picture?
Several economists have pointed out that rankings based on the HDI do not enlighten us any further than those based on traditional metrics such as GDP. It has been noted that the HDI simply tries to reinvent the wheel (Srinivasan 1990). Srinivasan argues that economists and policymakers have never seen income as the sole indicator of development and that the HDI does not show us anything that we did not know already. To some extent, this argument is indeed accurate. A study at the Applied Statistics Center at Columbia University compared U.S. state rankings based on average income to the rankings based on a human development measure and found an 86% correlation. (Gelman 2010) When these results were extrapolated to an international scale, it was found that the correlation between a country’s ranking on the HDI scale with its ranking on average income was even stronger – nearly 95% (Wolfers 2009).
It is only when we look at the rates of change of the HDI and GDP that differences between them emerge. The 86%-95% correlation between HDI and GDP at the present time, although perhaps of some statistical significance, will arguably decrease with time, since HDI and GDP change at two different rates. Rodriguez (in Wolfers 2009) points out that the correlation between the rate of change of HDI and the growth rate of per-capita income is only 43%. The correlation between changes in the nonincome components of HDI and the growth rate of GDP is 3%. The conclusion that can be drawn from this is that HDI-growth curves and GDP-growth curves are different in that they are plots of two different functions.
The differences in the information captured by the HDI and GDP do not seem to lend credibility to the HDI as such. Given that the information contained in changes in health and education indicators appears to be independent of that contained in changes in income indicators, it seems logical that countries can enjoy growth in per-capita income while not enjoying better health-care, school/university enrolment rates and literacy rates. If we would not intuitively say that a country is thereby ‘developing,’ then this would seem, prima facie, to score a point for the HDI. However, it is important to recognize that all this shows is that factors other than income serve to explain, and provide a metric for, what we mean by development, rather than the HDI as such. It does not tell us why using a single composite metric is the best mechanism to assess development levels.
It could be argued that HDI is a better measure of human development than GDP insofar as any composite metric that takes into account factors other than income is better than one that focuses on economic growth alone. This argument is addressed in the next section where it will be shown that the same problem exists in measuring developmental stages regardless of whether a composite index or a singular index is used.
Does the HDI change the way we measure development?
The tendency to evaluate alternate policy outcomes using a strictly economic calculus is problematic for several reasons. For one, it presumes that there exists, for some obligatory reason, a need to concentrate on economic indicators alone when evaluating the degree to which a collective is ‘developed’. Efforts have been made, often tenuous, to present positive correlations between GDP and other developmental concerns such as literacy, life expectancy, political freedom, etc. Indeed, if we were forced to restrict our focus to a single variable, a good place to start would be to maximize income. However, this ‘monoconcentrationist’ approach, argue the authors of the Human Development Report, is neither desirable nor necessary (Sen 2000). In order to assess whether the HDI serves as a better measure than economic indicators alone, it is important to first identify the crux of the problem in using monoconcentrationist measures of human development.
The rejection of the monoconcentrationist measure of human development is centered on the idea that we cannot accurately predict the range of observable socio-economic properties of a society by measuring only a single aspect of human development. Indices such as GDP or GNP attempt to measure what philosophy of science would generally categorize as an ‘unobservable property’. One cannot measure ‘development levels’ directly, through mere experiential observation, in the same way as the speed of light cannot be measured with the naked eye. Thus any measure of human development can be understood as a mechanism to describe, using a value, a certain stage of development, together with a suitably constructed model. The resulting value should attempt to provide us with information and allow us to predict a range of observable socioeconomic properties of the society in question. The fact that countries can share similar levels of GDP and yet have large variations in other observable attributes, such as equality, education levels, literacy rates, life expectancy or political freedoms, is precisely the reason why using a monoconcentrationist approach to human development is deemed to be undesirable.
Does the HDI enable us to better predict the situation on the ground? No, for the very same problem present in using singular metrics of human development is also present when we employ the HDI. Using the HDI, Country A with a very high GDP per-capita, moderate education levels and low life expectancy would be considered to be equally developed to Country B with moderate levels of GDP, education and health. Despite having similar values for their HDI indices, they have substantially different problems. Country A might have poor health infrastructure that consequently results in low life expectancies whereas Country B may have moderately good health, education and economic infrastructures. In these cases, a HDI value does not allow us to predict the observable socio-economic features of the society and consequently the developmental concerns that need to be addressed.
The need for triage
Uganda is a good example of how donors’ efforts in increasing longevity are falling apart. The ‘golden window’ of the last decade that witnessed the number of people on anti-retroviral medication increase from 10,000 to nearly 200,000 is coming to an end. Donors have decided that the cost of treating AIDS is too high; that concentrating on child-killers like pneumonia, diarrhea, malaria, measles and tetanus can save more lives (McNeil 2010). Alongside this, UNAIDS determined that for every 100 people put on antiretroviral treatment each year, 250 are getting infected (UNAIDS 2010). The situation in Kampala reflects how donors try to maximize each capability without taking a closer look at the interplay between different capabilities and their chronological importance. The capital for generating longevity in the case of Uganda ought to be heavily biased toward removing the causes of HIV, of which unsafe sexual practices remain the most notable. People refuse to practice the simple A-B-C (abstain, be faithful and use a condom) or the new fourth C (circumcision) (McNeil 2010). In such a scenario, policies that aim to generate the capability of knowledge are potentially cheaper to implement and can go further in the long run to increase life expectancy than policies that directly engage in creating longevity.
Let us now look at the conceptual problems that arise as we attempt to apply the HDI metric to this case-scenario. A composite index fails in this context for two reasons: it does not sufficiently reflect the variations in the importance of enhancing each component of the HDI and the interplay between them. With regard to the first problem, the use of the HDI prompts policy makers to channel aid to those areas that help the numbers look better (and faster), instead of focusing on more systemic and comprehensive long-term objectives. Investments into development and the ensuing returns are measured from the perspective of ‘the importance of raising HDI’ rather than ‘the importance of raising enrollment rates, longevity or per-capita income.’ Consequently, development policies fail to ensure that a country reaches a minimum level of attainment in each of the indicators. In the current system, based on the illustrations of Country A and Country B presented in the previous section, the capability set available to the people of Country A could be far less than that available to Country B if the length of their lives does not allow them to meaningfully make choices and expand their freedoms. A piecemeal approach avoids this problem by setting standards of attainment in each of the three components. This is important because human development requires a basic foundation to build upon. For instance, it would be difficult to generate the capability of longevity, as is the case in Uganda, unless there is a basic degree of education that encourages the use of safe and hygienic sexual practices. Similarly, it would be difficult to generate greater per-capita income if a very low life expectancy does not give enough time to increase income. Only when minimum standards are established can we develop efficiently.
With regard to the second problem (i.e. the interplay between the components of the HDI metric) the use of HDI can conceal relevant causal relations between socio-economic factors. Assume that, if GDP per-capita increases, literacy rates increase as a result. Then the HDI will increase both in response to per-capita GDP increase, as well as the increase in literacy rates. However, the way HDI is presented masks such interplay, so that donors may not be aware of the interplay even though the final HDI measure captures it. On the other hand, if we used several independent metrics to evaluate each component, this interplay becomes more evident. To illustrate this, consider a low-HDI country where the donor community has implemented a private sector development program and at the same time, has not implemented new policies or modified old ones to improve literacy rates or educational enrolment. As a result of greater employment, if more people can afford to send their children to schools, we record an increase in both income and school enrolment despite not implementing policy changes for the latter. This could potentially give us an idea regarding the endogenous causal relation between raising GDP and its effect on education; something we would not get from the use of an all-encompassing HDI.
However, it should be acknowledged that using separate indices does not always provide us with this information. For instance, consider a situation where two policies, one to improve GDP per-capita and another to improve literacy rates, are implemented simultaneously. As a result, both literacy rates and GDP increase. In such a scenario, using non-aggregative indices does not make it any easier for policy-makers to evaluate the individual causal efficacy of either policy. The point, however, is not that separate indices give us information about causal relations in every single case but that in those cases where policies are not implemented simultaneously, there is a greater likelihood that these relations are easier to observe when non-aggregative indices are used.
The case for change
Santosh Mehrotra (2010, p. 1), of the Institute of Applied Manpower Research in New Delhi, points out that “since the HDI is a broad indicator of development, it inevitably commands more attention from both governments as well as journalists, and hence, the media within each country watches out for that country’s HDI rank within the global league table – and the HDI is regularly remarked upon by commentators from different disciplines.” The HDI’s accelerated popularity within academic and bureaucratic circles has resulted in its overuse well beyond the scope for which it was devised. Today, HDI maximization has replaced comprehensive approaches as the tool which shapes donors’ aid agendas and formulates the developing world’s domestic policies. The proponents of the development index were aware of the pitfalls of overreliance on the composite index. Sen (2000, p. 22) recognized that “it would be a great mistake to concentrate too much on the Human Development Index, or on any other such aggregative index. These are useful indicators in rough-and-ready work, but the real merit of the human development approach lies in the plural attention it brings to bear on developmental evaluation, not in the aggregative measures it presents as an aid to digestion of diverse statistics.”
Prof. Sen’s concerns are echoed in the four points highlighted in this paper. First, the supposed greater intuitive adequacy of the HDI (over GDP) in explaining which socio-economic dynamics qualify as ‘development’ does not lend credence to the HDI itself. Nonetheless, it points to the fact that other underlying economic and social factors, over and above GDP per capita, have to be called on to evaluate development. It may seem that using an aggregative index that incorporates concerns other than economic growth is a better measure of human development. However, HDI as an aggregative index fails since it runs into the same problem that afflicts all monoconcentrationist measures, namely, that they cannot univocally describe different states of development. Different societies that are at different stages of development may receive the same HDI rating.
Furthermore, because of its indeterminacy, the HDI also brings different capability-enhancing policies to the same level, although they might require different priorities. In other words, one can say that, due to its indeterminacy, it lacks moral cogency. Lastly, it is argued that the HDI conceals endogenous causal relationships between different problems that obstruct development. These relationships are more likely to be evident when we use independent measures of human development.
The time has come for a cognitive shift in our approach to development from wholesale to retail – in order to take the abstract promises of capability generation stored in the warehouses of academic thought and deliver them to the developing world. Development studies should go beyond increasing the HDI to generating capabilities using a more fundamental understanding of the interplay between capabilities and their relative importance. The inadequacy of the HDI in reliably explaining the set of observable socio-economic conditions should be recognized and its use should be qualified or, better still, replaced with several independent indices of human development.
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Vignesh Ashok is a master’s candidate at the University of St. Andrews where he is reading for a degree in Peace & Conflict. He has previously studied at Lady Margaret Hall College, Oxford University where he received the Sir John Johnson Award for Academic Excellence for his work on diplomatic theory. He also holds an Honors degree in Engineering from the National University of Singapore.