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How useful is the capabilities approach in
determining the value of development policy
compared to traditional economic indicators
such as GDP growth?
Sian Day, B5932766
Word count:4,889
Submitted on: 03/10/2013
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Contents Page
Introduction 3.
Literature Review 3.
Research Method 5.
Research & Anlaysis 6.
Conclusion 10.
Appendix 11.
References 14.
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INTRODUCTION
This report sets out to determine whether or not the capabilities approach provides a useful way of
looking at the value of development policy; and more specifically whether it is any more or less
valuable than measuring development in terms of economic growth. As outlined by Anand (2010) in
the DD309 course material, the capabilities approach was developed by Amartya Sen and so
unsurprisingly his views are a focal point in the literature I have reviewed.
Anand (2010) also makes reference to further research he has carried out and as such I started my
literature review by identifying some papers to which he had contributed (Anand et. al, 2005, 2009).
In reading through Anand’s work two other names came up who, on further investigation, provided
information which enabled me to further build on the theory behind the capability approach (Alkire,
2005) (Robeyns, 2005, 2006).
The research element focuses on data collected from three Human Development Reports, United
Nations publications which were designed with input from Amartya Sen so have a much wider focus
than just GDP. However in order to keep within the scope of the project and look specifically at any
links between human development and GDP, education and health indicators are the main
development policy outcomes that are analysed in depth.
LITERATURE REVIEW
Vasanti is a Gujurati lady who was married to a gambler and alcoholic. To support his addictions he
spent their savings and took the cash incentive offered for a vasectomy. Vasanti had to leave the
abusive relationship and went to live with her Brothers. She was able to use a sewing machine from
her late Father’s business to earn some money doing repairs, and her Brothers gave her a loan so
she could upgrade her machine to do more jobs. As they had families she wanted to pay them back,
so took out a loan from a local women’s business association, through which she also has access to
education so she can learn to read and write and become more independent (Nussbaum, 2009).
The capability approach is a shift away from the traditional view of welfare economics – which is
largely interested in the efficient allocation of resources – and towards a more individualistic
perspective of what makes a good life (Anand et. al, 2010, p. 10). Anand et. al (2009) explain that the
capabilities approach was developed by Sen because of some of the shortcomings he identified in
traditional preference and consumption based welfare economic theories. As well as including rights
and freedoms, not covered by the concept of utility, he saw a need to exclude negative preferences
such as those based on racial discrimination. Furthermore, issues of distribution were not accounted
for in traditional welfare economic theories.
Measuring the welfare or utility of individuals and society is difficult – in part because of the
tendency to rely on information about consumption to convey utility which does not show the full
picture. Anand et. al (2005) cite the view from Sugden (1993), that the evaluation of individual or
societal good is not worth investigating. Rather, individuals should be left to act on whatever
preferences they choose and without having them questioned, as long as they are acting within the
agreed boundaries of their society. While Sen’s contrasting capability approach does not necessarily
encourage state intervention in the economy, it does highlight some areas which would be worth
focussing on should intervention occur (Anand et. al, 2005, p. 10).
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Because economic decision making is not purely limited to the pursuit of economic growth, Sen
argues that it is necessary to draw on more than one economic theory in order to asses each area of
welfare economics. This need for plurality challenges the traditional view of homo economicus and
recognises the complex economic choices individuals make. In terms of welfare economics, this
challenges the Bergson-Samson Welfare Theorem which has its sole purpose of maximising utility
and defining the economic welfare of society by its aggregate utility. Instead, societal improvements
are driven by the expansion of the availability of capabilities (Alkire, 2005, p. 125).
Amartya Sen’s capabilities and human development approach, is described as “multi-dimensional”
(Anand, 2010, p.202), where using GDP as the only indicator of progress is rejected. Instead, the
“enhancement of living conditions must clearly be an essential — if not the essential — object of the
entire economic exercise and that enhancement is an integral part of the concept of development”
(Sen, cited by Alkire, 2005, p. 117).
Sen’s capabilities framework outlines three key welfare outcomes. Firstly, functionings, which are
the activities that people take part in as a result of their physical and social resources. Secondly,
happiness; the achievement of which is a direct result of individual functionings, and not just
consumption. The third welfare outcome is termed Q (Anand, 2010, p.203). The capability set (Q) is
the range of possible functionings available to a person based on their individual features and access
to commodities (Anand et. al, 2009, p. 129). While the capabilities approach does account for things
like physical resource allocation, because it is multi-dimensional any individual factor can only
contribute to whether someone is achieving their capabilities (Robeyns, 2005, p. 100).
Some goods and services can be used as functionings (beings and doings) – although this
relationship depends on personal, social and environmental conversion factors. Essentially, whether
or not a good can be used to achieve a capability depends on the personal, social and environmental
context. It is also noted that that goods and services are not the only means to achieving capabilities;
social norms, traditions and institutions may also contribute (Robeyns, 2005, p. 98).
While Sen has not given a definitive list of the various dimensions that influence capability,
Nussbaum has identified ten central capabilities following collaboration with him. These are: life,
bodily health, bodily integrity, thought, emotions, reason, affiliation, other species, play and control
over one’s environment; crucially the satisfaction of one dimension does not reduce another (cited
by Anand et. al, 2005, p. 13). Once criticism of this list is that people may be likely to put weightings
against each headline indicator, potentially undermining its multi-dimensional nature, another is a
cynicism about how universal any such a list can be (Anand et. al, 2009). A further issue with the list
created by Nussbaum, despite her claims that it is “humble and open-ended” is that it lacks
legitimacy, due to the fact that the people to which the list could apply have had no say in the
matter (cited by Robeyns, 2006, p. 354).
Sen’s refusal to define a list of capabilities opens him up to the criticism that the capability approach
cannot be operationalised – however his response is that the desire to make a list is in fact the
problem. Sen suggests that the important capabilities should become apparent as the outcome of
the democratic process. This however does again raise the issue of legitimacy; how this democratic
process takes place, and who has control over it (Robeyns, 2005, p. 106). While Alkire (2005, p. 116)
acknowledges the desire to operationalise the capability approach, John Hicks is cited as
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emphasising the importance of “constructing ‘more general’ theories,” in order to cause a shift in
the way that economics as a whole is approached.
While Nussbaum believes that capabilities should be the main element which directs public policy
decision making and analysis, she recognises functionings and their ability to influence an
individual’s quality of life (cited by Anand et. al, 2005, p. 13). The focus for political outcomes is on
capabilities because in reality, and considering the importance of individual choice, it is accepted
that people with the same capability sets are unlikely to achieve the same functionings (Robeyns,
2005, p. 101). Robeyns (2006, p. 354) suggests that it is sometimes necessary and useful to look at
functionings. This is largely because of the nature of information that is included in datasets used for
large scale studies – however even without specific data on capability sets the comparison of
functionings can prove useful, especially if there is a stark and unexplained difference in the
functionings of two separate groups.
Srinivasen critiques the capabilities approach because the metrics required to collect data remove
the subjective and individualistic nature of capabilities, thus rendering any studies conducted
irrelevant and incomparable over time (cited by Anand et. al, 2005, p. 14). Sugden also picks up on
the level to which the approach can be operationalised, questioning its use as an alternative to GDP
and John Rawls said that it is “an unworkable idea” (both cited by Robeyns, 2006, p. 352). While
Anand et. al (2005) concur that this is likely to contribute to the lack of studies that exist in this area,
they highlight some challenges around existing economic indicators, specifically in errors of
measurement.
The capability approach can be used to evaluate aspects of life for an individual or within a society
such as inequality and poverty, or as a framework within which to develop and evaluate policies. It is
a normative approach; it does not seek to explain poverty however it does look at the context within
which such social phenomena exist (Robeyns, 2006, p. 352). To explain how it works in practice,
Alkire is cited as conducting a study on small scale development projects in Pakistan (Robeyns, 2006,
p. 362), including goat rearing and female literacy classes. While the goat rearing produced a
tangible return on investment, as well as other benefits such as learning a skill and meeting people;
the female literacy classes did not impact on poverty. This is because there is a lack of data on
female employment available for the area. By looking at the programme only from an economic
perspective its continuation would be hard to justify. Furthermore, there were many non-financial
benefits over and above the women being able to read; including learning their equal value to men
and the fact that they should not suffer abuse. This is an outcome that enables them to live a life of
value, and one where they have an element of choice that would not be picked up by analysing the
project in purely financial terms – highlighting the importance of the capability approach.
RESEARCH METHOD
As outlined in the 2010 HDR which looks back over the 20 years for which the series has been
published, “People are the real wealth of a nation” (HDR 2010, p. iv), with the reports looking
beyond GDP as a single measure of progress. They use a measure called the Human Development
Index (HDI) to measure improvements in human development focussing on three key areas: health,
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education and income, which are all factors that can enhance people’s freedoms and capabilities.
While the HDI is examined to some extent, where possible the focus is on looking at the information
about specific areas like health or education.
The information in these reports was selected in terms of trends and analysis that specifically relate
to GDP. This was necessary due to the wealth of information available on a range of capabilities.
Because the capability approach outlined by Sen does not set out to specify capability indicators
which can be used in all contexts (and any attempts, for example, by Nussbaum, are still broad
enough to be irrelevant in this context) the data analysis is limited by the information that was
available and focuses largely on health and education.
While not representative of the capabilities approach as a whole, the idea is to get an idea of how
useful traditional economic indicators such as GDP are when looking at human development, in
order to understand whether there is a need for an alternative way of looking at human
development. Even though a large amount of quantitative data was available, because of the specific
interest in the relationship between non-income dimensions and GDP the majority of information
used is already processed.
Initially, two more sources were identified; The OECD How’s Life?: Measuring Well-Being report and
Anand et al’s Development of Capability Indicators (2009). These were selected because of their
emphasis on human capabilities. However, because they are both concerned with well-being more
broadly their findings are not obviously linked to GDP and as such have not been included within the
limited scope of the project.
As this report does focus very heavily on information produced by the same body and from the same
series of reports, care is taken when drawing conclusions to examine the information on the basis of
the credibility of the data and by highlighting any potential bias.
RESEARCH & ANALYSIS
The first HDR, published in 1990, states that “human development is a process of enlarging people’s
choices.” While education, health and a standard of living are defined as the most critical
dimensions, through which other capabilities can be achieved. A range of other examples are given
of dimensions to which people attach value – such as political and social freedoms and human rights.
While it recognises the importance of income in enabling people to access resources, it is a means
rather than an end, in line with the capability approach.
The 2010 HDR (The Real Wealth of Nations: Pathways to Human Development) uses data collected
on 135 countries between 1970 and 2010 to compare various regions in the developing and
developed world on their income – based on purchasing power parity (which enables cross country
comparisons to be made even in the absence of GNI information), life expectancy, literacy rates and
gross enrolment in education – which combined form the HDI. This shows that regions with higher
income levels have better outcomes in the key health and education indicators based on 2010 values
(appendix, figure 1). Sub-Saharan Africa has the lowest income per capita at $1,466, and also has the
lowest life expectancy (52 years), literacy rate (65%) and gross educational enrolment rate (54%). In
contrast, the highest income is in the non-OECD developed region, with $40,043 income, life
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expectancy of 80 years, a 96% literacy rate and 79% educational enrolment rate. While positive, the
correlation between income and education and health indicators is not without exceptions – for
example the OECD region has a slightly lower income at $37,105, but an enrolment rate of 93%.
Furthermore, the Latin American and Caribbean region is a developing country with $11,092 income
but a life expectancy of 74, literacy rate of 92% and gross educational enrolment rate of 83%.
The correlation between income, health and education is further emphasised by the 1996 HDR
(Economic Growth and Human Development) which uses 1993 data to display the relationship
between growth and the HDI (p. 66). However, despite the observed trend, it suggests that growth
in itself is not the answer in relation to development policy. This is because it depends on a country’s
ability to transform income into human development, or “human development efficiency” (HDR,
1996, p. 66).
In measures that are not affected by GDP growth (HDI*), countries with income at all levels can
achieve good HDI* rankings. Sri Lanka, for example, has an income of under $1,000 GDP per capita
but has an HDI* ranking of 0.8 thanks to its investment in basic health and education in the 1970s
(HDR, 1996, p. 81) – not far behind Singapore with GDP per capita of around $20,000. Singapore
could, however, move further towards the human development frontier by becoming more efficient
at translating increases in income to increases in HDI*, while Sri Lanka is operating at maximum
human development efficiency (appendix, figure 2).The variation between HDI* and GDP per capita
works in the other direction too –countries with similar income levels may have very different HDI*
rankings. For example, Senegal and Guinea have similar income levels to Sri Lanka however they
have HDI* of less than 0.4.
Some of the policies that have been pursued in Sri Lanka include educating mothers, which has
impacted health outcomes more generally (HDR 1996, p. 69) and investing in child nutrition which as
well as less hungry people means stronger adult workers (HDR 1996. p. 76). These basic investments
in health and education during the 1970s became valuable through its industrial growth in the 1980s
(HDR 1996, p. 81), and have seen the relationship between growth and human development
become mutually reinforcing.
The 2010 HDR plots the relationship between the HDI and income growth (GDP per capita) over
time, as well as income growth with the non-income components of HDI (appendix, figure 3). It
shows that income growth is positively correlated to HDI, but this is expected as income is one of the
components of the HDI. When the HDI value is adjusted to look only at health and education
measures, the correlation with economic growth over time becomes statistically insignificant (HDR,
2010, p. 46) – even countries with contracting or stagnating economies continue to make progress in
life expectancy and education levels. While this is an interesting result, and useful to bear in mind
when drawing conclusions about the value of HDI as a measure of income if making comparisons to
GDP, both household and government spending can influence human development (HDR, 1996,
p.67), so it may not be particularly useful to exclude income from the analysis altogether. For
example, increased income could mean that better quality food or other material goods can be
purchased which may expand capabilities given the right social and environmental conversion
factors.
The result that changes in income are not correlated with changes in health and education seems
somewhat paradoxical to the fact that countries with high incomes tend to have higher HDI levels.
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The HDR report suggests that this could be because the relationship observed at a point in time may
not be representative of the relationship (HDR, 2010, p. 48). This suggestion is similar to the criticism
put forward by Srinvasen of the capability approach and leads to the question – if the relationship is
not reliable at a single point in time, are comparisons over time relevant?
The ability of some countries to better utilise human development efficiency better than others
suggests that looking at changes over time is relevant – at least in terms of health and education. By
looking at the changes it is possible to identify any policies or contexts that have driven any such
changes. Another suggestion from the HDR 2010 is that the path by which developing countries are
making their improvements is different to those that are already developed, and this affects the
overall relationship. Developed nations have used increases in income to drive technological change
that affect health in particular. Over time basic treatments (which were once ground breaking)
become more widely available at a lower cost and so can be picked up by developing countries with
a significant and immediate impact. Once health improves above a certain point, further advances
are costly to achieve and so income becomes important again (HDR 2010).
Despite the fact that 95% of the global population across 155 countries have seen real terms
increase in their per capita GDP income since 1970, this has been largely skewed towards already
developed countries with average increases in GDP per annum of 2.3% compared to 1.5% for
developing countries (HDR, 2010, p. 42). Based on the index used to calculate the HDI, income has
ranged from between under 0.1 to over 0.9 across countries (with the greater number representing
the better position) from 1970 to 2010 (appendix, figure 4). Comparatively, the health index range
has shifted from between just over 0.2 and just under 0.9 in 1970 to between just under 0.4 and 1 in
2010 (appendix, figure 5); and the education index range from between under 0.1 and just over 0.8
in 1970 to between around 0.3 and 1 in 2010 (appendix, figure 6). For education and health, there
has been more convergence towards higher outcomes than for income, where the gap between the
richest and poorest countries has widened (HDR, 2010, p. 40).
This means that, despite the fact that the gap between the richest and the poorest in society has
widened, people in developing countries are catching up in terms of health and education. This
result sets the HDI in particular apart from GDP as a measure of progress. While it paints a positive
picture – better educated people are more empowered, able to make informed decisions about
health and earn more; and longer life spans suggests that people have access to better basic services
– using an aggregate measure such as literacy rates or longevity does not give the whole picture. Any
average figure can mask large inequalities in distribution; however this is also an issue with GDP.
Even in the first HDR in 1990, the importance of distribution is emphasised – this could be in any of
the key indicators analysed by the HDI; between genders; ethnic groups or regionally. However at
the time the most widely used measure of inequality, the Gini coefficient, was not well used enough
to provide meaningful insights across the dataset (HDR 1990, p. 13). In 2010 though, an inequality
adjusted HDI as well as a gender inequality measure is introduced. While the results are not
discussed here it is noteworthy as a reflection of the continual aim to widen the scope of the data
collected, to more accurately reflect the way that people across countries represented. This is the
people centred approach that goes beyond GDP.
The 2010 HDR also looks at countries over time in terms of their improvements in HDI ranking
relative to their starting point using deviation from fit. This means that progress is measured against
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the expected improvements of countries with similar starting points, as shown in (appendix, figure
7). Using this measure, Oman tops the table of improvers and this is because of its gains in health
and education. While its income level has risen dramatically, ranking 26th in economic growth since
1970, its increase in spending on education and health has been even more significant and this is
reflected in its HDI improvement ranking (HDR, 2010, p. 54).
While improvements in health, education and income certainly seem positive, especially if the result
holds true once inequality adjustment takes place, looking at improvements instead of absolute
measures still does not give the whole story. Using Oman as an example, despite making great
progress in income growth, health and education, political freedom is extremely limited with an
unelected leader and a ban on the formation of political parties (HDR 2010, p. 54). Further
information regarding its political and social freedoms can however be analysed using the capability
approach framework – none of this information would be picked up by GDP.
The 1990 HDR (Concept and Measurement of Human Development) does not have the benefit of a
measurement such as the HDI to provide insights over time, so instead selects the mortality rates of
under 5s as a non-income measure which is reflective of the aims of human development. This is
because there is a relationship between it and other dimensions which affect the formation of
capabilities; such as nutrition, literacy and life expectancy (HDR, 1990, p. 44). It puts forward the
idea that in the long run, a combination of economic growth, relatively equitable income distribution
and well targeted social spending is likely to be the most beneficial approach for advancing human
development, especially in terms of increasing education and health outcomes (HDR, 1990, p. 42).
Three countries are identified which are said to have missed out on opportunities for human
development; Brazil, Pakistan and Nigeria (appendix, figure 8). All of these countries experienced a
period of economic growth, and failed to translate that into meaningful improvements in their infant
mortality rate comparable to countries with similar income levels. Take Brazil, despite being a
middle income country in 1997 (with a GDP per capita of $2,020) having experienced healthy growth
of around 3% in the 1950s rising to over 6% in the 1970s, infant mortality was 85 out of 1000 in
1988. This is twice the level of Sri Lanka, with an income around one fifth the size of Brazil, and hides
regional variations from 116 to 52 deaths in 1000. Interestingly, Brazil did embark on social
spending policies totalling 8 – 10% of GDP between 1973 and 1976. However, due to the inefficient
and untargeted nature of the spending, meaning that it was not received by the people who it would
most benefit, as well as significant income inequality, the increase in growth has not transformed
into the kind of outcomes in human development that could have been achieved (HDR, 1990, p. 56 –
58).
While widely measured variables like education and health are certainly important factors in
expanding an individual’s capability set, there are a number of other dimensions which are captured
in the 2010 HDR. Even without using Nussbaum’s high level capability indicators, it is reasonable to
expect that access to democracy (which may represent political participation), equality (to live a life
of value without facing discrimination), and sustainability (the right of future generations to live a
life they would value) could be contributing factors to expanding an individual’s capability set. While
countries with less inequality tend to have higher measures of HDI, there are still around 11% with
high HDI scores that do not have access to equal participation in society (appendix, figure 9). The
relationship between democracy and HDI is less significant, and between environmental
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sustainability there is no relationship. The 2010 HDR does not, however, go into detail about the
relationship between these variables and GDP.
The main limitation of this report is that the quantitative information used does not adequately
represent the extent of the capabilities approach. However, the literature review showed that one
of the major criticisms of the approach is in the difficulties operationalising it. In a sense, one of the
main strengths of the approach – its breadth – is also its weakness when used in comparison to GDP.
While the capabilities approach may not be easily operationalised, the existence and continuation of
the report coupled with the creation of other reports with similar aims of going beyond GDP (such as
the OECD How’s Life? Report), and an increased interest from policy makers around the world (HDR
2010, p. 12) might suggest that it is a valuable framework from which to design and evaluate public
policy. Being able to look at countries in depth and on an individual level is key to the capabilities
approach; any attempt to put a value on a capability set is likely to be incomplete and may even
undermine the theory behind the approach.
While the data collected in the report comes from many credible sources – from the United Nations
Human Development Reports Office through to a variety of academic experts across the world and
also gathering information from national and international databases – it is worth bearing in mind
that the series of reports and the use of the HDI as a measure were developed by Amartya Sen and
other proponents of the capability approach as an alternative to GDP growth as the sole measure of
human development. In talking about the intellectual foundations for the capabilities approach, it is
even mentioned that “Sen’s perspective deeply informs the report” (p. 16). As such, we would
expect there to be a strong case put forward for the value of using the capabilities approach.
The 2010 HDR draws some broad conclusions and insights which would be useful for policy makers.
From making poverty reduction and equity a central part of policy, developing institutions and
policies which promote equality and inclusion, domestic investment (public or private), integrating
into international markets while maintaining some domestic control offer scope to improve incomes,
through to environmental sustainability. It is worth mentioning, in answer to anti-interventionist
critics such as Sugden that any such innovations do not necessarily have to be undertaken by the
state. In most countries though, it is likely that the majority of people would view such things as the
responsibility of the state. Finally, the fact that observed successes of human development are
highly contextual needs to be accounted for; what works for one country may not for another.
CONCLUSION
GDP growth is a relatively simple measure that is comparable across countries and over time.
However, the issues with GDP growth as a measure of human development have been shown
through the analysis of the data in the HDR reports – countries fare very differently in world rankings
when alternative indicators, such as health and education, are assessed. Furthermore, GDP growth
does not automatically mean that a country will see improvements in its wider development – some
low income countries are able to achieve as much if not more than higher income countries.
While the capabilities approach recognises the importance of economic growth to allow a country
and its citizens to have increased access to resources, income is seen as a means, not an end, to
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development. Despite the apparent bias in the HDR reports in favour of using the HDI instead of GDP
for its shift towards people as the focus for human development, it is reasonable to conclude that
the wider purpose of the report, looking at various capabilities and their expansion around the world
(or otherwise) is useful in a development policy context.
On whether the capabilities approach is a suitable alternative to GDP – will it replace it? Unlikely.
However as a complementary tool for looking beyond growth in order to understand how policies
affect people, it seems like a step in the right direction.
APPENDIX:
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