2.6 Distributional and equity aspects

This section discusses how different equity concepts can be applied to the evaluation of climate change policies and provides examples on how the climate literature has addressed equity issues. See also Chapter 20 in IPCC (2007b), and Chapters 12 and 13 of this report for additional discussions on the equity dimensions of sustainable development and climate change policies.

2.6.1 Development opportunities and equity

Traditionally, success in development has been measured in economic terms – increase in Gross National Income (GNI) per capita remains the most common measure^[18]. Likewise, income distribution has been one of the key components in equity, both within and between countries, and has been measured in terms of inequalities of income, through measures such as the ‘GINI’ coefficient.^{[19] [20]} Although a great deal has been written in recent years on the components of well-being, the development literature has been slow to adopt a broader set of indicators of this concept, especially as far as equity in well-being is concerned, despite the fact that some authors have argued that absolute changes in income and other indicators of human well-being (e.g. education, mortality rates, water, sanitation etc.) are just as important as the distribution within these indicators (Maddison, 2003; Goklany, 2001).

Probably the most important and forceful critic of the traditional indicators has been Sen (1992, 1999). Sen’s vision of development encompasses not only economic goods and services but also individuals’ health and life expectancy, their education and access to public goods, the economic and social security that they enjoy, and their freedom to participate freely in economic interchange and social decision-making. While his criticism is widely acknowledged as addressing important shortcomings in the traditional literature, the ideas still have not been made fully operational. Sen speaks of ‘substantive freedoms’ and ‘capabilities’ rather than goods and services as the key goals of development and provides compelling examples of how his concepts can paint a different picture of progress in development compared to that of changes in GNI. It remains the case, however, that actual indicators of equity still do not cover the breadth of components identified by Sen.

The UNDP Human Development Index (HDI) is an important attempt to widen the indicators of development, and initially included per capita national income, life expectancy at birth and the literacy rate. However, it is important to recognize that no single all-encompassing indicator can be constructed, will be understandable or useful to either policymakers or the public, so different indexes have to be used that reflect different issues and purposes.

Rather than synthesizing these three components into a single index, as the HDI has done, we can also look at changes in the inter-country equity of the individual components. Table 2.3^[21] provides data for the period 1980–2001 for per capita national income (GNI) and life expectancy at birth (LE) and from 1990 to 2001 for the literacy rate (ILL). The increase in average GNI has been much faster over this period than those of life expectancy and literacy rates. The increase in coefficient of variations for GNI per capita (by 6%) and life expectancy (by 14%) therefore show an increase in dispersion over this period, indicating a wider disparity of these parameters across countries. However, literacy rates have become more equal, with a decline in the coefficient of variation by 22% (see Table 2.3). However, a study by Goklany (2002) concluded that inequality between countries does not necessarily translate into inequality between individuals.

Table 2.3: Measures of Inter-country Equity

Notes: Literacy rates are for 1990 and 2001. GNI and LE data are for 1980, 1990, and 2001. Ninety-nine countries are included in the sample. Coefficient of variation is the standard deviation of a series divided by the mean. The standard deviation is given by the formula:

Where ‘x’ refers to the value of a particular observation, is the mean of the sample and ‘n’ is the number of observations.

Source: WB, 2005 (World Development Indicators)

As Sen notes, the problem of inequality becomes magnified when attention is shifted from income inequality to inequality of ‘substantive freedoms and capabilities’, as a result of a ‘coupling’ of the different dimensions – individuals who are likely to suffer from higher mortality and who are illiterate are also likely to have lower incomes and a lower ability to convert incomes into capabilities and good standards of living. While this is certainly true at the individual level, at the country level the correlation appears to be declining.

This wider analysis of equity has important implications for sharing the costs of mitigation and for assessing the impacts of climate change (see Chapter 1 for a more detailed discussion of climate change impacts and the reference to the UNFCCC Article 2). As generally known, the impacts of climate change are distributed very unequally across the planet, hurting the vulnerable and poor countries of the tropics much more than the richer countries in the temperate regions. Moreover, these impacts do not work exclusively, or even mainly, through changes in real incomes. The well-being of future generations will be affected through the effects of climate change on health, economic insecurity and other factors. As far as the costs of actions to reduce GHGs are concerned, measures that may be the least costly in overall terms are often not the ones that are the most equitable – see Sections 2.6.4 and 2.6.5 for a further discussion of the links between mitigation policy and equity.