1.3: A yardstick for the evaluation of prosperity and progress

For many decades, the dominant way to measure prosperity and social progress has been to focus on Gross Domestic Product (GDP) or Gross National Product (GNP) per capita. The more we produce, the more developed our country has been taken to be. Yet a large literature has emerged showing that GDP per capita is limited and often flawed as a measure of social and economic progress (Fleurbaey 2009; Stiglitz, Sen and Fitoussi 2010; Fleurbaey and Blanchet 2013; Coyle 2015).

In one of the very first empirical applications of the capability approach, Amartya Sen (1985a) used some very simple statistics to illustrate how deceiving GDP per capita can be as a measure of prosperity and progress.⁶ Sen showed that, in the early 1980s, the (roughly equivalent) GNP per capita of Brazil and Mexico was more than seven times the (roughly equivalent) GNP per capita of India, China and Sri Lanka — yet performances in life expectancy, infant mortality and child death rates were best in Sri Lanka, better in China compared to India and better in Mexico compared to Brazil. Important social indicators related to life, premature death and health, can thus not be read from the average national income statistic. Another finding was that India performs badly regarding basic education but has considerably higher tertiary education rates than China and Sri Lanka. Thus, Sen concluded that the public policy of China and especially Sri Lanka towards distributing food, public health measures, medical services and school education have led to their remarkable achievements in the capabilities of survival and education. What can this application teach us about the capability approach? First, the ranking of countries based on GNP per capita can be quite different from a ranking based on the selected functionings. Second, growth in GNP per capita should not be equated with growth in living standards.

Sen has often made use of the power of comparing the differences in the ranking of countries based on GDP per capita with indicators of some essential functionings. Recently Jean Drèze and Amartya Sen (2013, 46–50) used the capability approach to develop an analysis of India’s development policies. For example, as table 1.1 shows, they compared India with the fifteen other poorest countries outside sub-Saharan Africa in terms of development indicators.⁷

Of those sixteen countries, India ranks on top in terms of GDP per capita, but ranks very low for a range of functionings, such as life expectancy at birth, infant mortality, undernourishment, schooling and literacy. Other countries, with fewer financial means, were able to achieve better outcomes in terms of those functionings. Once again, the point is made that focussing on income-based metrics such as disposable income at the household level, or GDP per capita at the national level, gives limited information on the lives people can lead.

Table 1.1 Selected Indicators for the World’s Sixteen Poorest Countries Outside Sub-Saharan Africa

	India	Average for other poorest countries	India's rank among 16 poorest countries
GDP per capita, 2011 (PPP Constant 2005 international $)	3,203	2,112	1
Life expectancy at birth, 2011 (years)	65	67	9
Infant mortality rate, 2011 (per 1,000 live births)	47	45	10
Under-5 mortality rate, 2011 (per 1,000 live births)	61	56	10
Total fertility rate, 2011 (children per woman)	2.6	2.9	7
Access to improved sanitation, 2010 (%)	34	57	13
Mean years of schooling, 25+, 2011	4.4	5.0	11
Literacy rate, age 14–15 years, 2010 (%)
Female	74	79	11
Male	88	85	9
Proportion of children below 5 years who are undernourished, 2006–2010 (%)
Underweight	43	30	15
Stunted	48	41	13
Child immunization rates, 2011 (%)
DPT	72	88	13
Measles	74	87	11

Source: Drèze and Sen (2013, 47).

This type of illustration of the power of the capability approach, whereby at the macro level the quality of life in a country is compared with GDP per capita, is not restricted to poor countries only. For example, the capability approach has recently also been taken up by the ‘Better Life Initiative’ of the OECD, the Organisation for Economic Co-operation and Development. The aim of this initiative is to track wellbeing, both in the present day and historically, by looking at ten dimensions of wellbeing: per capita GDP, real wages, educational attainment, life expectancy, height, personal security, the quality of political institutions, environmental quality, income inequality and gender inequality. Several of these dimensions can be conceptualized through a capability lens and others (such as per capita GDP or real wages) are needed for a comparison between capability dimensions and income dimensions, or can be seen as core capability determinants or capability inputs. In a recent report, which reconstructed the outcomes on those dimensions between 1820 and 2000, it was found that some dimensions, such as education and health outcomes, are strongly correlated with per capita GDP, but others are not — such as the quality of political institutions, homicide rates and exposure to conflicts (Van Zanden et al. 2014).

Another example that illustrates the difference the capability approach can make is the analysis of gender inequality, for which it is clear that we are missing out the most important dimensions if we only focus on how income is distributed. There are two main problems with an income-based approach to gender inequalities. The first is that it is often assumed that income within households will be shared. Yet that assumption makes most of the economic inequalities between women and men invisible (Woolley and Marshall 1994; Phipps and Burton 1995; Robeyns 2006a). Moreover, gender scholars across the disciplines have argued that one of the most important dimensions of gender inequality is the distribution of burdens between men and women (paid work, household work and care work); the fact that women are expected to do the lion’s share of unpaid household work and care work makes them financially vulnerable and restricts their options. Any account of gender inequality that wants to focus on what really matters should talk about the gender division of paid and unpaid work, and the capability approach allows us to do that, since both paid and unpaid work can be conceptualized as important capabilities of human beings (e.g. Lewis and Giullari 2005; Robeyns 2003, 2010; Addabbo, Lanzi and Picchio 2010).

Moreover, for millions of girls and women worldwide, the most important capability that is denied to them is extremely basic — the capability to live in the first place. As Sen showed in an early study and as has been repeatedly confirmed since, millions of women are ‘missing’ from the surface of the Earth (and from the population statistics), since newborn girls have been killed or fatally neglected, or female foetuses have been aborted, because they were females in a society in which daughters are more likely to be seen as a burden, especially when compared to sons (Sen 1990b, 2003b, 1992b; Klasen 1994; Klasen and Wink 2003). In sum, tracking the gap between women’s achievements in income and wealth or labour market outcomes will not reveal some crucial dimensions of gender inequality, whereas the capability approach draws attention to these non-income-based dimensions.

Using the capability approach when thinking about prosperity and social progress has another advantage: it will impede policy makers from using mistaken assumptions about human beings in their policies, including how we live together and interact in society and communities, what is valuable in our lives and what kind of governmental and societal support is needed in order for people (and in particular the disadvantaged) to flourish. For example, in their study of disadvantage in affluent societies, in particular the UK and Israel, Jonathan Wolff and Avner De-Shalit discuss the effects of a government policy of clearing a slum by moving the inhabitants to newly built tower blocks. While there may be clear material advantages to this policy — in particular, improving the hygiene conditions in which people live — a capabilitarian analysis will point out that this policy damages the social aspects of people’s wellbeing, since social networks and communities are broken up and cannot simply be assumed to be rebuilt in the new tower blocks (Wolff and De-Shalit 2007, 168, 178–79). Since social relationships among people are key to their wellbeing, this may well have additional derivative effects on other dimensions of people’s lives, such as their mental health. Understanding people as beings whose nature consists of a plurality of dimensions can help governments to think carefully through all the relevant effects of their policies.

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6 An even earlier empirical study, in which the capability approach is referred to as the right evaluative framework, was done by Amartya Sen and Sunil Sengupta (1983).

7 Those other countries are Afghanistan, Bangladesh, Burma, Cambodia, Haiti, Kyrgyzstan, Laos, Moldova, Nepal, Pakistan, Papua New Guinea, Tajikistan, Uzbekistan, Vietnam and Yemen.