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Intra-generational equity and sustainable welfare: a time series analysis for the UK and Sweden
Ecological Economics 33 (2000) 219 – 236 www.elsevier.com/locate/ecolecon
ANALYSIS
Intra-generational equity and sustainable welfare: a time series analysis for the UK and Sweden Susanna Stymne, Tim Jackson * Centre for En6ironmental Strategy, Uni6ersity of Surrey, Guildford, Surrey, GU2 5XH UK Received 4 May 1999; received in revised form 14 October 1999; accepted 18 October 1999
Abstract This paper discusses the importance of intra-generational equity to sustainable development. It outlines a number of methodologies for measuring income inequality in the economy, and presents several possible ways of incorporating the impact of distributional effects into measures of welfare in the economy. The authors highlight in particular an index developed by Atkinson (Atkinson, A.B., 1970. Distributive politics and economic growth. Q. J. Econ., May, 465–490.) based on the social welfare model. This method possesses two main advantages over other methods. Firstly, it is expressed directly in terms of social well-being. Secondly, value judgements incorporated into the measure are made explicit through the parameter o which expresses society’s degree of aversion to income inequality. The paper calculates the value of the Atkinson index for two case study countries (Sweden and the UK) between 1950 and 1996 for a central estimate of o=0.8. The results show that the welfare loss due to inequalities in the distribution of income varied between 5 and 10% for Sweden, and between 6 and 14% for the UK, with the higher values coming towards the end of the period. The paper explores the sensitivity of these results to changes in the value of o for the case of the UK, and discusses the relevance of the work to the measurement of sustainable welfare. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Equity; Sustainability; Income distribution; Income inequality; Gini coefficient; Atkinson index
1. Introduction Equity is a key concept in sustainable development. The literature on sustainable development * Corresponding author. E-mail addresses: [email protected] [email protected] (T. Jackson)
(S.
Stymne),
and on ecological economics has devoted most attention to the concept of inter-generational equity. Although well recognised in economic theory, the concept of intra-generational equity has received less attention in the ecological economics literature. Nevertheless, it is clearly important to sustainable development because there are recognised links between income inequality, economic
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growth, human capital and the environment. Thus, levels of inequality in the economy may have considerable impact not only on present levels of well-being, but also on the well-being of future generations. This paper discusses those links in conceptual terms (Section 2). It then outlines a number of methods for measuring income inequalities (Section 3) and discusses the question of integrating those measures into measures of national welfare (Section 4). Using two of these measures, it then presents a time series analysis on trends in the distribution of incomes in two case study countries (the UK and Sweden) and carries out a sensitivity analysis (for the UK) on one key parameter — the value of o in the Atkinson inequality index (Section 5). The differences between equity, equality, fairness and justice have been extensively discussed in the literature (e.g. Le Grand et al., 1976; Daly 1992; Dasgupta, 1995; Sen 1997). Quite clearly the concept of intratemporal equity is broader than the concept of intratemporal income equality. A thorough analysis of the former issue must pay attention to the intratemporal distribution of a wide variety of resources, including natural, environmental, cultural, human and social resources as well as purely financial ones. Acknowledging these limitations, it is nonetheless our contention that the distribution of incomes in the economy represents a reasonable proxy with which to illustrate the welfare impacts of intratemporal equity, and this paper proceeds on that basis. 2. Well-being and income inequality Traditional measures of economic growth, such as the gross domestic product (GDP), reflect changes in the absolute level of activity but tend to ignore relative and positional changes. A dollar income rise to a poor person is assumed to have the same welfare effect as a dollar increase to a rich person, and aggregate increases in income are assumed to yield equivalent increases in well-being no matter how they are distributed. In reality, however, we would expect the distribution of incomes to have differential effects on well-being for a number of reasons.
In the first place, most societies express some kind of social preference for equality over inequality; i.e. a society with less inequality in the distribution of resources is preferred to one with more inequality. As a rule, therefore, societies tend to strive for a more equal distribution of resources, although there are different views on what the right le6el of equality for a society is. Some countries might emphasise the poorest people in society, while others strive for total equality. Daly (1992) argues that a ‘good distribution is one that is just or fair, or at least one in which the degree of inequality is limited within some acceptable range.’ Le Grand et al. (1976) identify several approaches to the question of a fair distribution: the minimum standard approach — which is concerned only with the poor in the society and argues that nobody’s income should fall below a certain minimum level; the total equality approach — which argues that everyone should have the same income, i.e. the bottom 10% of the population should receive 10% of the income; the need or desert approach — which accepts inequalities either on the grounds that some people need more income or because people deserve more due to own effort, sacrifice, intelligence, etc; equality of opportunity or procedural approach — inequality accepted if everyone has had the same opportunity, or if the distribution is a result of a fair process. The social justice approach introduced by Rawls (1971) is what Le Grand et al. (1976) refers to as a ‘combined approach’ in which inequalities are only justified to the extent that they benefit the least advantaged. Related to the issue of fairness is that of the diminishing marginal utility of income: when a person is poor s/he would benefit more from an income rise than if s/he were rich. This, in turn, would suggest that a transfer from a rich person to a poor person decreases inequalities in a society, and thereby raises the overall level of national well-being. Dalton (1920) pointed out that all inequality measures should have this characteristic, i.e. that a transfer from a rich person to a poor person should always reduce the value of the inequality index.1
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A third issue linking inequality and well-being is the relationship between economic growth and equality. The question here is whether there is a trade-off between economic efficiency (higher national income) and equity (a more equally distributed income). The conventional view has been that striving for income equality slows down economic growth for several reasons. Firstly, it is argued that higher equality will lead to less incentive to work and less incentive to be productive. (This is related to the impact of tax rates, and is only one of many incentive effects.) It has also been argued that higher equality can lead to a reduction in domestic savings and thereby a reduction in growth. This argument is based on the assumption that rich people have a higher marginal propensity to save (Klasen, 1994). In recent years, however, the issue of the relationship between growth and income inequality has been turned on its head. Income equality is now being advanced by some as a promoter of growth (Perotti, 1993; Alesina and Rodrick, 1994; Persson and Tabellini, 1994; Be´nabou, 1996). In these studies, it has been argued that pre-tax income equality could dampen the demands for redistribution policy (financed by taxes) and hence enhance investment, education and R and D. A further reason for incorporating considerations of intra-generational equity into assessments of sustainable welfare is the relationship between investment and income inequality. The potential conflict between investment in savings (for future welfare) and investment in improvements in intra-generational equity has already been remarked upon. The level of direct and indirect investment in human capital is also of importance for the sustainability of an economy. A healthy and well-educated work force will help to ensure future generations’ consumption possibilities. Research has shown the equalising income differentials might have greater effect on the status of health and mortality than increasing income (Fritzell and Lundberg, 1995; Wilkinson, 1996). This is of particular importance in developed countries where the relative dimension, i.e. 1 This has become known as the Pigou–Dalton criterion (Sen, 1997).
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how a person’s economic situation compares to others can trigger ‘psychological mechanisms’ that can affect the status of health. From the point of view of sustainable development, it is clearly important to question whether or not there is a relationship between intra-generational equity and environmental quality. A now well-known hypothesis put forward by Kuznets (1967) supposes that as income levels increase (through economic growth), income inequality passes through an inverted U-shaped curve, with increasing levels of inequality in the early years of development giving way to diminishing inequities as development advances. A similar curve (termed the Environmental Kuznets Curve) has been proposed for the relationship between environmental degradation and levels of income. It should be noted that both these hypotheses are contentious;2 and any conclusions that could be drawn from these parallel relationships are beyond the scope of this paper. However, recent investigations do indicate that there are important relationships between equity and environmental quality. Boyce (1994) has argued that a more equitable distribution of power contributes to improvements in environmental quality. His definition of a power function is based on a combination of an income inequality index (Gini), a literacy variable, political rights and civil liberties, and certain other factors (mainly geographical). The overall conclusion from a study of seven different environmental factors for a cross-section of high and low income countries is that the ‘results provide fairly robust support for the hypothesis that greater inequality in the distribution of power leads to more pollution’ (Torras and Boyce, 1998). This hypothesis also appears to be supported by empirical work in relation to the distribution of power within a country (Boyce et al., 1999). The basis for the correlation between greater inequalities and increased environmental degrada2
On the environmental Kuznets curve, see the special issue of Ecological Economics, 25 (2), 1998, in relation to income inequality; it should be noted that the results reported in this paper provide no obvious support for the Kuznets curve hypothesis.
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tion can be summarised in three points (Boyce, 1994). 1. In a situation where there are benefits as well as costs of environmental degradation, the extent of the degradation will depend on who is most powerful (the winner or the loser). As power and wealth are often correlated, it is likely that the rich will be the ones with power. If these are the ones who benefit from the degradation, there will be greater environmental degradation since the difference in distribution leads to some groups in society not having the power to counteract the costs. This is the main argument in Torras and Boyce (1998). 2. Greater inequality leads to less concern for the future, i.e. a higher rate of environmental time preference. The poor have a high environmental time preference as they are concerned with day-to-day survival rather than future environmental degradation. The rich, Boyce argues, also experience high rates of environmental time preference because political and economic inequality pose threats to the legitimacy of the powerful (for instance, through social unrest). This prompts those in power to pursue the extraction of short-term profits even if this is at the expense of future environmental degradation. 3. Environmental degradation is often valued in willingness to pay, which is related to the ability to pay — income will affect the valuation of the costs and benefits. Greater inequality raises the benefits to the rich, relative to the costs of the poor. There are clearly a number of other complex relationships between income distribution and the environment, exemplified, for example, by the extent to which security in low income families in developing countries is often gained through larger families, which in turn leads to higher environmental impacts (Markandya, 1998), or by the extent to which identity in developed economies is developed through materially intensive consumption patterns (Jackson and Marks, 1999). The underlying issue in all of these relationships is the question of the distribution of benefits versus the distribution of costs. Higher
consumption patterns benefit richer communities, but the cost of these consumption patterns often impact most on poorer communities. It is clear from these considerations that the relationships between intra-generational equity and sustainable welfare are complex, but of considerable importance. As the UNDP (1996) has pointed out: ‘average material welfare can be defined by the per capita GDP. However, statistical averages can mask the diversity that exists within any country. Therefore, from a sustainable development perspective, it is informative to examine income and wealth distribution throughout a population.’ This brings us to the issue of how to measure inequalities and how to include consideration of these inequalities into measures of national well-being. This is the subject matter of the following two sections.
3. Measuring income inequalities There are several different types of inequality measures. Coulter (1989) divides inequality measures into four distinct types, according to the mathematical model on which they are based. These are: measures based on the combinatorial model; measures based on the entropy model; measures based on deviation models; measures based on the social welfare model. The first type of measure, based on combinatorial analysis, ‘reflects the probability of randomly selecting a pair of identical units (for equality polarity) or different units (for inequality polarity) from a pool of units divided among two or more components’ (Coulter, 1989). The second type of index, using the entropy model, is ‘generally based on an interpretation involving the number of bits of information that are necessary to identify the location of any unit in its component’ (Coulter, 1989). Measures based on the deviation model aim to illustrate to what extent a value deviates from a set standard. Measures belonging to this group are mainly based on the absolute, relative and squared deviations from the mean or mode. These are all frequently used measures for assessments
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of intra-generational and inter-generational equity. The most commonly used deviation index is probably the Gini coefficient. The final type of measure, based on the social welfare model, attempts to measure the social welfare implications associated with particular levels of inequality. In this context, social welfare is taken to mean the well-being or happiness of a society. However, since it is difficult to actually measure well-being or happiness, the utility from income is often used as a proxy for welfare. For example, Dalton (1920) proposed measuring social welfare W as the aggregate of the utilities U(yi ) associated with each income yi. Thus: W= %i U(yi )
(1)
Dalton is also often referenced as the first to argue that a measure of income inequality could be based on this social welfare model. In practice, of course, what is required to carry out this measurement is a way of relating different incomes to the utility associated with them. In this paper, we focus on two specific types of welfare measure, namely, a deviation-type measure based on the Gini coefficient, and a method first proposed by Atkinson (1970) based on the social welfare model. These two measures are examples of what Sen (1997) classifies as objective and normative measures, respectively. Where the Gini coefficient is used only to rank different levels of inequality in an objective fashion, the Atkinson index is normative in the sense that it incorporates specific value perspectives by relating income inequality to social welfare. In the following subsections, we present time series data on the distribution of incomes in Sweden and the UK for each of these different types of measures.
3.1. Gini coefficient for Sweden and the UK The Gini coefficient is measured as one-half of the average of the absolute difference between all pairs of relative incomes. The Gini coefficient is often explained graphically as the ratio of the area difference between the curve of actual income distribution and the line of equal distribution. The coefficient takes a value between 0 and 1, where 0
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represents total equality. The higher the value of the Gini coefficient, the greater the level of inequality. Fig. 1 shows the value of the Gini coefficient in the UK and Sweden between 1950 and 1996. It is clear from the figure that prior to 1980, income inequality declined consistently in Sweden, mainly as a result of a number of specific social welfare policies. In the UK, by contrast, the distribution of income remained more or less constant until about the mid-1960s. From then, until the mid-1970s inequality in the UK fell slightly. In both countries, however, income inequality increased during the later years of the period, although this trend is considerably more noticeable in the UK than it is in Sweden.3
3.2. Atkinson index in Sweden and the UK The Atkinson index can be interpreted as ‘the proportion of the present total income that would be required to achieve the same level of social welfare as at present if incomes were equally distributed’ (Atkinson, 1983). Atkinson suggested that it is possible to derive the total welfare corresponding to a particular distribution of income according to the following formula:
W= Y* %i (yi /y)(1 − o)·pi
n
(1/1 − o)
(2)
where Y is the total income; yi is the mean income of the i th group; y is the mean income of the total income population; pi is the proportion of the 3 The Swedish index is based on several different studies, as no single study covers the whole time period in a consistent fashion. The three main sources were a preliminary study by Bjo¨rklund (1995) on individual income distribution for the years 1951 – 1958, 1960 – 1976, and on disposable household income distribution for years between 1975 – 1996 from the income distribution study 1995 (SCB, 1997) and (Jansson, 1994, 1994a). For a discussion of the data set used, see Jackson and Stymne (1996). The UK index is calculated for the period 1954 – 1984 from income distribution data compiled on a tax unit basis and published in Economic Trends (ET, various years). A second data set for 1977 – 1996 is based on income distribution data by household units compiled in the Family Expenditure Surveys (FES, various years). For a discussion of the data set used, see Jackson and Marks (1994) and Jackson et al. (1997).
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Fig. 1. The Gini coefficient in Sweden and the UK, 1950 – 1996.
total income population in the i th group; and o is a factor which represents the weight attached by society to inequality in the distribution of income. The Atkinson index is then defined by: I =1−
W Y
(3)
Since welfare falls as the inequality of income distribution rises, the Atkinson index provides an increasing function of inequality in the economy, defined by the difference (normalised with respect to total income) between the total income and the welfare which it delivers. In a perfectly distributed economy, yi =y for each income group, and so the welfare level is given by:
n
W = Y* %i pi
1 1−o
=Y
(4)
In this case, the inequality measure I reduces to 0, as would be expected. The factor o is an important parameter in the measure. It represents society’s preference for
equality of distribution of incomes. Since it is possible to conceive of societies which have a positive preference for an unequal distribution of income, it is clear that o can take both negative and positive values. When o = 0, society is indifferent to the distribution of income, and welfare again reduces to the total income in the economy:
n
W=Y* %i
yi ·pi = Y y
(5)
and welfare is considered equal to the total income.4 The parameter o therefore allows explicitly for the possibility of attributing different welfare levels according to different attitudes towards inequality in society. A value of 0 would mean that society is indifferent to the distribution of income. As the value of o rises, more weight is placed by society on the lower income groups. When o reaches , society will accept nothing less 4
To see this, note that y = Y/P where P is the total income population and Yi= yi ·pi ·P is the total income in the ith group. W then reduces to SiYi =Y
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Fig. 2. The Atkinson index for Sweden and the UK, 1950 – 1996.
than total equality for all sectors of the population. By contrast, a value below 0 would mean that society is prepared to lose some income in order to achieve greater income inequality. The value of o can be determined, in theory, in terms of transfer efficiency. The method is explained by Atkinson (1983) through a ‘thought experiment’ in which he looked at how much a rich person would be prepared to lose in transfer costs (from administration or inefficiency for example) when distributing income from the rich to the poor. According to Atkinson, a transfer will only take place if the net benefit (including transfer losses) is positive. This thought experiment provides a formula for determining o given by: 1 =do x
(6)
where x is the proportion of income that is to be transferred to the poorer person for the rich person to accept the transfer and d is the (proportional) distance between the rich and the poor person. As an example, suppose that a richer
person has twice the income of a poorer one (i.e. d= 2) and that s/he is prepared to lose 40 pence in transfer costs (i.e. x=0.4). Then o is given by 1/0.6 = 2o (i.e. o= 0.74). Fig. 2 illustrates the value of the Atkinson index for Sweden and the UK between 1950 and 1996, using an o value of 0.8.5 The basic trends illustrated in Fig. 1 are also apparent in Fig. 2: improvements in income distri5 The income distribution data for the UK has been taken mainly from a report prepared by the Institute of Fiscal Studies providing decile shares of post tax income for the years 1961 – 1991 (See Table 2.3 in Goodman and Webb (1994)). For the years not covered by this study, we have used an index based on Gini coefficient data to extrapolate the Atkinson index. For Sweden we have used disposable income per consumption unit for family units in decile groups published by Statistics Sweden (Statistiska meddelanden: Be21SM various years). For those years where income per consumption unit was not available, income per family unit was used and linked to the years where income per consumption unit was available. For those years where no decile data on disposable income could be found, we used an index based on Gini coefficient data to extrapolate the Atkinson index.
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bution during earlier years of the period are offset by greater inequality in the later years. Again, the trend towards increased inequality since about 1975 is more marked in the UK. In this case, however, Fig. 2 provides an interpretation of this increase in terms of social welfare. The Atkinson index I can be interpreted as the loss of welfare associated with a given level of inequality in the distribution of incomes. Fig. 2 reveals that in 1978 this loss of welfare for the UK was around 6.5%, a slight improvement over the 9% loss associated with income inequality in 1950. By 1996, on the other hand, the welfare loss had more than doubled to over 14%.
4. Incorporating income inequality into a welfare index It is clear from the discussion above that the Atkinson index has the advantage of offering an immediate interpretation in terms of social welfare, and can thus be used to incorporate the effects of income inequality directly into welfare measures. For example, where income is used directly as a proxy for social welfare, we find that Eq. (3) can be recast as: Yadj =Y*(1− I)
(7)
Yadj now represents the distribution-adjusted welfare measure. This method can be generalised in a straightforward fashion to other kinds of welfare measures W through: Wadj = W *(1−I)
(8)
In the following section we present a case study in which the Atkinson index is used to adjust several different kinds of welfare measure in the two case study countries (Sweden and the UK). First, however, it is worth pointing out that a number of other suggestions have been made concerning the incorporation of distributional aspects into welfare measures. In the literature, distributional adjustments have been made, for example, to the GDP, the World Bank’s human development index (HDI) and Daly and Cobb’s index of sustainable economic welfare (ISEW) (Daly and Cobb, 1989). Each of these indicators
incorporates some kind of income concept as its basis, and it this income variable that is most obviously open to adjustment from a distributional perspective. Perhaps the most widely used methodology incorporates the Gini coefficient in some form. A Gini-based welfare indicator was derived, for example, by Sen (1976, 1997) and has been used in several empirical works, such as by UNDP (1993) (to correct the HDI) and by Klasen (1994) (to adjust income in the USA). A welfare function adjusted using the Gini coefficient could take the following shape (as in the Human Development Index (UNDP, 1993)):Wadj = W *(1− G)where W is the welfare index, G is the Gini coefficient and Wadj is the distribution-adjusted welfare index. Alternatively, the adjustment could be made using a Gini index formulated relative to a particular base year:
(10)
(11)
Wadj = where Grel =
W * 100 Grel
100 * Gn Gbase
Gbase is the Gini coefficient in the base year, and Gn is the Gini coefficient in the year of interest. Even though this method is quite widely used there are several problems with it. Firstly, although the Gini coefficient satisfies the principle of transfers — i.e. a transfer from a rich person to a poor person always reduces the inequality measure — it does not satisfy the principle of diminishing transfers — i.e. that the effect of a transfer diminishes as the absolute level of income increases (Schwartz and Winship, 1979). Further, in spite of the classification of the Gini coefficient as an objective measure, it does implicitly include value judgements. For example, distributions towards the middle are implicitly preferred in the index. However, these value judgements remain hidden within the index. Perhaps the most intractable problem is that there is no direct welfare-theoretic interpretation of the Gini index. By contrast, there are several specific advantages to the Atkinson index. Firstly, of course, the interpretation in welfare terms is straightforward,
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since the Atkinson index is formulated from a welfare-theoretic model. In addition, however, there is much greater transparency with regard to value judgements. Given that the conventional summary measures inevitably introduce distributional values, Atkinson (1983) argues that ‘it may be preferable to consider such values explicitly. Only then can it be clear just what distributional objectives are being incorporated as a result of adopting a certain measure.’ The Atkinson index incorporates these value judgements explicitly through the value o in Eq. (2). This allows the user of the index to incorporate particular value judgements about the importance of distributional elements to welfare. It should perhaps be mentioned that it would also be possible to construct a distribution-adjusted welfare model using a relative Atkinson index by a straightforward analogy with the method proposed in Eqs. (10) and (11) for the Gini coefficient. In this case, the distribution-adjusted measure Wadj would be given by:
(12)
(13)
Wadj =
W * 100 Irel
where Irel =
100 * I Ibase n
Ibase is the Gini coefficient in the base year, and In is the Atkinson index in the year of interest. It is not clear however, that this method offers any advantages over a direct welfare-theoretic adjustment. Table 1 summarises a variety of attempts to adjust welfare measures for distributional properties.
5. Case study: distribution-adjusted welfare measures for Sweden and the UK This section reports on a time-series analysis of the impact of adjusting two specific measures for distributional effects using the Atkinson index. Firstly, we apply the Atkinson index to time series data on personal consumer expenditure in Sweden and the UK between 1950 and 1996. Secondly, we apply the index to adjust the index of sustainable
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economic welfare in each of these case study countries. As noted in the previous section, all inequality measures include value judgements. In most cases these value judgements remain hidden within the methodological assumptions made. However, in the Atkinson index, some of these values are made explicit through the parameter o. This parameter is defined as: ‘the weight attached by society to inequality in the distribution’ (Atkinson, 1983). Although this construction works in theory, placing an appropriate value on o at the national level is difficult. Empirical studies of the value are scarce. Schwartz and Winship (1979) refer to Stevens (1959), Schwartz (1974) and Winship (1976) who all used ‘attitudinal survey data about the level of well-being associated with different levels of income’. The results indicated that o should take a value between 0.5 and 0.75. Schwartz and Winship (1979) also refer to Stern (1977) who examined data on individual consumer maximising behaviour. His results indicated that o should range between 0 and 10 with a best ‘guesstimate’ of 2. Schwartz and Winship themselves argued that ‘most sociologists would agree that when using Atkinson’s measure to address normative questions, o should be between − 0.5 and 2.5’ (Schwartz and Winship, 1979). In choosing appropriate values of o for this study, we have been guided mainly by a study by Blundell et al. (1994) (cited by Pearce and Ulph (1995)) based on household consumption behaviour over time. The value of o emerging from this study was 0.8. It is most probable that inequality aversion in the UK and Sweden differ, and therefore arguable that o should also differ. However, at the current stage of the research, no value of o has been found for Sweden, and we therefore used 0.8 as our central value in both case study countries. However, it is clearly appropriate to investigate the sensitivity of distributional adjustments to changes in the value of o. Table 2 below shows the variation in the Atkinson index (I) in Sweden and the UK for a range of o values. Using a value of o= 0.8, the Atkinson index for the UK in 1992 is 0.136. The interpretation of this figure is that the UK could reach the same level of social welfare with only 86.4% (i.e.
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Table 1 Overview of distributional adjustments to welfare measures Description
Income inequality index used
Basis adjusted
Result
Income inequality adjusted growth rates (Klasen, 1994)
Integrates distributional components into changes in well-being, where well-being is expressed as income.
4 different types used: 1. Equal weights 2. Poverty weights 3. Gini 1 4. Gini 2
Family income before and after tax. Applied to the USA 1947–1991.
Gini coefficient
The income component of the HDI. This component is then multiplied by (1−Gini).
An attempt to enlarge the Gini coefficient scope of distributional issues in the HDI, to include distribution in longevity and education.
Each of the three components of the HDI are adjusted for inequality by a factor of li (1−Gi ), where Y is a weighting factor so each dimension could be given a different weight.
The income distribution adjusted measure shows an improvement in the growth rate during the 1960s and a down-turn during the 1980s, i.e. without the income distribution adjustment, the growth rates are underestimated during the 1960s and overestimated during the 1980s. The HDI index is lower when accounting for income inequalities. The ranking of the countries slightly changes. Sweden, for example, changed from 5th place to 3rd place, and the UK from 10th to 9th place (year 1993). Only looked at developing nations. The percentage loss of HDI varies from 30–57%, but does not change ranking by more than four places.
Income adjusted human Attempts to adjust the human development index (HDI) development index using (UNDP, 1992, 1993) income distribution. The HDI is a decomposition index consisting of three variables: income; education; and longevity. Inequality adjusted human development index (Hicks, 1997)
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Name and author
Table 1 (Continued) Description
The index of sustainable A measure of sustainable economic welfare (ISEW) welfare that takes the (Daly and Cobb, 1989) distribution of income into account.
Income inequality adjusted national income (Beckerman, 1980)
Income inequality index used
Basis adjusted
Result
Low quintile index, where variations in the lowest quintile are monitored. This fits in with Rawl’s theory of justice. 1950 is set as a base year (= 100).
The basis for the ISEW is personal consumption, which is adjusted for income inequality.
The weighting has a negative effect on the USA index, penalising rising income inequality. The ISEW has been applied to several other countries, of which the UK and Sweden are two. The methodology for accounting for income distribution has changed in these studies, and is described in the empirical section of this paper. Beckerman comes to the conclusion that taking changes in income distribution into account ‘barely affects the growth rates of most countries’. Applied to several developed nations including UK and USA over the period of two decades (between 1950 and 1973).
An experimental calculation Atkinson income inequality index where the conventionally measured growth rates are compared with the growth rates of ‘equivalently distributed income’.
National income
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Name and author
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Table 2 Atkinson index in the UK and in Sweden in 1992 for different o values o= −0.5
Atkinson index (I)
SWE −0.034
o =0.8 UK −0.065
SWE 0.083
1 – 0.136) of present total income, if the incomes were equally distributed. (it is to be noted, of course, that the value of I depends not only on the value of o, but also on how current income is distributed). Figs. 3 and 4 show distributionally adjusted personal consumer expenditure for Sweden and the UK (respectively) using an o value of 0.8. It is clear from the figures that the adjustment has a depressive effect on the chosen measure, although the effect is somewhat more marked for the UK than it is for Sweden. Since the beginning of this study period (year 1950) both Sweden and the UK have been characterised by rising GDP per capita and rising levels of consumer expendi-
o =1.6 UK 0.136
SWE 0.168
o =2.5 UK 0.250
SWE 0.265
UK 0.351
ture. The two countries have, however, had different income distribution policies. In Sweden, one of the main long-term goals of the government has been to smooth out inequalities in the economy, and this was clearly successful (as Figs. 1 and 2 illustrate) at least until the early 1980s. In the UK, by contrast, intervention by the government has been limited. It is, for example, only very recently that the government has established a minimum wage for the UK. Atkinson (1993) points out several domestic reasons behind rising inequalities in the UK: a shift from workrelated to benefit-related income, changes in benefits coupled with a rising number of unemployed and pensioners, rising inequalities among
Fig. 3. Distribution-adjusted per capita consumer expenditure in Sweden (1950 – 1996).
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Fig. 4. Distribution-adjusted per capita consumer expenditure in the UK (1950 – 1996).
those not in work and a rise in earnings inequalities. The same kind of distributional adjustment can also be applied to the Daly and Cobb ISEW. The original formulation of the ISEW incorporated income inequality through the use of a relative Gini-coefficient adjustment (as set out in Eqs. (10) and (11)). In the most recent version of the UK ISEW, however, Jackson et al. (1997) proposed using the Atkinson method in place of the Gini coefficient method for the reasons discussed at the end of Section 4. Figs. 5 and 6 show the effects of this adjustment on the ISEW for Sweden and the UK, respectively, using an o value of 0.8. These graphs illustrate the now-familiar departure of the trend in ISEW from the trend in GDP over the later years of the study. However, they also show the impact which income inequality adjustment has on the index. In both case study countries, the distribution-adjusted ISEW is depressed below the unadjusted measure. Fig. 5 illustrates that the negative impact due to income inequality adjustments in Sweden is relatively con-
stant over the time period, indicating that the welfare impact of inequalities in Sweden has not changed drastically over the time period of the study. However, Fig. 6 shows that the negative effect is considerably greater for the UK. Indeed, the impact of the income inequality adjustment changes the shape of the ISEW over the later years of the study from one in which sustainable economic welfare is relatively stable (although with some variations) to one in which sustainable economic welfare is declining. It is clear from this analysis that distributional adjustments can have a significant influence over judgements about the trend in real welfare over time. However, as Fig. 7 shows, these influences are critically dependent upon the particular value chosen for the parameter o. Fig. 7 shows a sensitivity analysis on the distribution-adjusted ISEW for the UK over the period 1950–1996, using values of o ranging from − 0.5 to 2.5. It should be remembered (Figs. 1 and 2) that in general terms income inequality has increased in the UK over this time, particularly
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towards the later years of the study. Thus, in a society which is averse to income inequality (o \ 0), the measure would be expected to experience a downward influence in the later years. Conversely, in a society which positively favours income inequality (oB 0), the reverse trend would be visible. Both these trends are visible in Fig. 7. At o = 0, of course, the ISEW reduces to an index which takes no account of income distribution, since at this value society has no aversion to income inequality. For higher negative values of o, Fig. 7 illustrates a rather significant depressive effect on the welfare index over time. In fact, the choice of an o value of 2.5 leads to a shift in the ISEW which dominates most of the other adjustments to the index, including those introduced by ecological variables (Jackson et al., 1997). Thus, in a society where there is a high aversion towards income inequality (i.e. there is a high o value), distributional issues could be given as high a priority as environmental issues, or perhaps even a higher one.
It would be possible to take an even broader approach to the distributional issue, which accounts not only for income inequalities, but also for inequalities in the distribution of ecological resources. This could change the relative emphasis on ecological and distributional variables in the ISEW considerably. One possible outcome might be that a country with a high aversion to income inequality would also have a high aversion to ecological inequalities, and the depressive effect on the welfare measure would be increased further over time. Taken in conjunction with the arguments of Boyce and his coworkers discussed in Section 2, these considerations reinforce the conclusion that addressing the problem of income inequality is a critical component in the search for sustainable development.
6. Conclusions This paper has argued that there are good reasons for incorporating some account of the
Fig. 5. Distribution-adjusted ISEW and GDP per capita in Sweden (1950 – 1992).
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Fig. 6. Distribution-adjusted ISEW and GDP per capita in the UK (1950 – 1996).
level of intra-generational equity into national measures of well-being in the economy. Furthermore, it has been pointed out that intra-generational equity also plays an important part in the determination of future well-being, and a critical role in the search for sustainable development. We have reviewed a number of attempts to construct indices of inequality in the distribution of income-related variables and to incorporate such indices into measures of welfare. In particular, we have examined in some detail an index proposed by Atkinson (1970) based on the social welfare model, and applied this index to measures of welfare in two case study countries. The results of the empirical analysis suggest that adjusting for distributional effects can have significant impacts both on the value of welfare measures, at particular points in time, and on the trend in such measures over time. The magnitude of this impact will depend both on the degree of inequality in the distribution of incomes during the time period in question, and also on the value of the parameter o
— the degree of aversion to income inequality in society. The work reported in this paper suffers from some clear limitations. In the first place, empirical data on appropriate values of o are sparse. Limited references in the literature suggest a value of 0.8 as appropriate in the UK, but this work is now somewhat dated, and no comparable data were found for Sweden. Work on evaluating o in the case study countries is continuing. This paper has limited the discussion of intragenerational equity to the distribution of incomerelated variables. However, it could clearly be argued that the distribution of other resources has important consequences for sustainable welfare. For example, the income concept could be widened to include ecological factors. This was, for example, done by Ruitenbeek (1996) when he looked at the distribution of ecological income in a village in the Cameroon. Eisner (1994) suggested that distributional adjustments should be made to the total ISEW rather than just personal
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Fig. 7. Sensitivity of distributional adjustments in the UK to the value of o.
consumption. Hicks (1997) has suggested a technique for adjusting the longevity and educational variable of the HDI with a distributional variable. The relationship between income distribution and the environment was explored by Boyce (1994), reviewed in Section 2 above. In spite of its limitations, the analysis in this paper has confirmed the value of incorporating distributional aspects into measures of current well-being in society, and has indicated the relevance of distributional issues for future welfare levels. Moreover, the techniques developed in this paper could potentially be extended to other aspects of welfare including the distribution of ecological, social and human capital.
5110, under the Environment and Climate Programme), by the Engineering and Physical Sciences Research Council and by the Royal Academy of Engineering. An earlier version of the paper was presented at the European Ecological Economics Society’s conference in Geneva March 4–7 1998, and we are grateful for critical input and advice from a number of people including Anthony Atkinson, Giles Atkinson, Steven Dodds, Alissa Goodman, Andrew Klemer, KarlGo¨ran Ma¨ler and Jack Ruitenbeek. The views expressed and any remaining errors are, of course, the responsibility of the authors.
References Acknowledgements The work described in this paper has been supported in part by the European Commission (TMR Marie Curie Research Training Grant: numbers ENV4-CT96-5033 and ENV4-CT98-
Alesina, A., Rodrick, D., 1994. Distributive politics and economic growth. Quart. J. Econ. May, 465 – 490. Atkinson, A.B., 1970. On the measurement of inequality. J. Econ. Theory 22, 44 – 263. Atkinson, A.B., 1983. The Economics of Inequality, second ed. Oxford University Press, NY. Atkinson, A.B., 1993. What is happening to the distribution of income in the UK? Proc. Brit. Academy 82, 319 – 351.
S. Stymne, T. Jackson / Ecological Economics 33 (2000) 219–236 Beckerman, W., 1980. Comparative growth rates of ‘measurable economic welfare’: some experimental calculations. In: Matthews, R.C.O. (Ed.), Economic Growth and Resources, vol. 2. Macmillan, London and NY. Be´nabou, R., 1996. Inequality and growth. NBER Working Paper No. 5658. National Bureau of Economic Research, Cambridge, MA. Bjo¨rklund, A., 1995. Preliminary report on income distribution. Mimeo, SOFI 95-06-11. Stockholm University, Stockholm. Blundell, R., Brewning, M., Meghit, C., 1994. Consumer demand and the life-cycle allocation of household expenditures. Rev. Econ. Stud. 61, 57–80. Boyce, J.K., 1994. Inequality as a cause of environmental degradation. Ecol. Econ. 11, 169–178. Boyce, J.K., Klemer, A.R., Templet, P.H., Willis, C.E., 1999. Power distribution, the environment, and public health: a state-level analysis. Ecol. Econ. 29 (1), 127–140. Coulter, P.B., 1989.. Measuring Inequality: a Methodological Handbook. Westview Press, Boulder, San Francisco and London. Dalton, H., 1920. The measurement of the inequality of incomes. Econ. J. 30, 348–361. Daly, H., 1992. Allocation, distribution, and scale: towards an economics that is efficient, just, and sustainable. Ecol. Econ. 5, 185 – 193. Daly, H., Cobb, J., 1989. For the Common Good — Redirecting the Economy Towards Community, the Environment and a Sustainable Future. Beacon Press, Boston. Dasgupta, P., 1995. The population problem: theory and evidence. J. Eco. Lit. 33, 1879–1902. Eisner, R., 1994. The index of sustainable welfare: comment. In: Cobb, C., Cobb, J. (Eds.), The Green National Product. University of Americas Press. ET, various years. Economic Trends — Annual Supplement 1993. Central Statistical Office, HMSO, London. FES, various years. Family Expenditure Surveys. Central Statistical Office, HMSO, London. Fritzell, J., Lundberg, O., 1995. Income Distribution, Income Change and Health: On the Importance of Absolute and Relative Income for Health Status in Sweden. Reprint Series No. 452. Swedish Institute for Social Research, Stockholm University, Stockholm. Goodman, A., Webb, S., 1994. For Richer, for Poorer. The changing distribution of income in the United Kingdom, 1961 – 91. Commentary No. 42. The Institute for Fiscal Studies (IFS), London. Hicks, D.A., 1997. The inequality-adjusted human development index: a constructive proposal. World Dev. 25 (8), 1283 – 1298. Jackson, T., Marks, N., 1994. Measuring Sustainable Economic Welfare: a Pilot Index 1950–1990. Stockholm Environment Institute/New Economics Foundation (UK), Stockholm. Jackson, T., Marks, N., 1999. Consumption, sustainable welfare and human needs — with reference to UK expenditure patterns 1954 – 1994. Ecol. Econ. 28 (3), 421–442.
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Jackson, T., Stymne, S., 1996. Sustainable Economic Welfare in Sweden: a Pilot Index 1950 – 1992. Stockholm Environment Institute, Stockholm. Jackson, T., Marks, N., Ralls, J., Stymne, S., 1997. An Index of Sustainable Economic Welfare for the UK 1950 – 1996. Centre for Environmental Strategy (University of Surrey)/ New Economics Foundation, London. Jansson, K., 1994. Inkomstfo¨rdelningen i Sverige 1975 – 1992 med sa¨rskild beskrivning av perioden 1989 – 1992. Rapport 1994:1 (1994-08-17) Programmet fo¨r Inkomster och Fo¨rmo¨genhet, Statistics Sweden, SCB publication service, O8 rebro. Jansson, K., 1994a. Inkomstfo¨rdelningen i Sverige 1980 – 1991 med sa¨rskild analys av skattereformen 1990 – 91. Rapport 1993:1 (1994-05-11). Programmet fo¨r Inkomster och Fo¨rmo¨genhet, Statistics Sweden, SCB publication service, O8 rebro. Klasen, S., 1994. Growth and well-being: introducing distribution-weighted growth rates to revaluate US post-war economic performance. Rev. Income Wealth 40 (3), 251 – 272. Kuznets, S., 1967. Population and economic growth. Proc. Am. Phil. Soc. 3, 170 – 193. Le Grand, J., Propper, C., Robinson, R., 1976. The Economics of Social Problems, third ed. Macmillan, Hampshire and London. Markandya, A., 1998. Poverty, income distribution and policy-making. Environ. Resour. Econ. 11 (3/4), 459 – 472. Pearce, D., Ulph, D., 1995. A social discount rate for the United Kingdom. CSERGE working paper GEC 95-01, CSERGE, London. Perotti, R., 1993. Political equilibrium, income distribution, and growth. Rev. Econ. Stud. 60, 755 – 776. Persson, T., Tabellini, G., 1994. Is inequality harmful for growth? Amer. Econ. Rev. 84 (3), 600 – 621. Rawls, J., 1971. A Theory of Justice. Harvard University Press, Cambridge, MA. Ruitenbeek, H.J., 1996. Distribution of ecological entitlements: implications for economic security and population movement. Ecol. Econ. 17, 49 – 64. SCB, 1997. Inkomstfo¨rdelningsunderso¨kningen 1995. BE 21 SM 9701. Statistics Sweden, SCB Publication Service, O8 rebro. Schwartz, J.E., 1974. Taking a look at income. Mimeo, Harvard University, Cambridge, MA. Cited in Schwartz and Winship, 1979. Schwartz, J., Winship, C., 1979. The welfare approach to measuring inequality. In: Schuessler, K.F.K (Ed.), Sociological Methodology 1980. Jossey – Bass Publishers, San Francisco, Washington and London (Chapter 1). Sen, A., 1976. Real national income. Rev. Econ. Stud. 43, 19 – 36. Sen, A., 1997. On Economic Inequality. Expanded edition with a substantial annexe by Foster, J.E and Sen, A. Clarendon Press, Oxford. Stern, N.H., 1977. Welfare weights and the elasticity of the marginal valuation of income. In: Artis, M.J., Nobay, A.R. (Eds.), Studies in Modern Economic Analysis: the
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S. Stymne, T. Jackson / Ecological Economics 33 (2000) 219–236 UNDP, 1993. Human Development Report 1993. Published for the United Nations Development Programme (UNDP). Oxford University Press, NY and London. UNDP, 1996. Indicators of Sustainable Development Framework and Methodologies. Methodology Sheets. United Nations Department for Policy Co-ordination and Sustainable Development (DPCSD). http://www.undp.org. Wilkinson, R.G., 1996. Unhealthy Society: the Afflictions of Inequality. Routledge, London and NY. Winship, C., 1976.. Psychological Well-being, Income and Income Inequality. Mimeo, Harvard University, Cambridge MA.
Proceedings of the Association of University Teachers of Economics. Blackwell, Oxford. Stevens, S.S., 1959. Measurement, psychophysics, and utility. In: Churchman, C.W., Ratoosh, P. (Eds.), Measurement: Definition and Theories. Wiley, NY. Torras, M., Boyce, J.K., 1998. Income, inequality, and pollution: a reassessment of the environmental Kuznets curve. Ecol. Econ. 25 (2), 147–160. UNDP, 1992. Human Development Report 1992. Published for the United Nations Development Programme (UNDP). Oxford University Press, NY and London.
.
ANALYSIS
Intra-generational equity and sustainable welfare: a time series analysis for the UK and Sweden Susanna Stymne, Tim Jackson * Centre for En6ironmental Strategy, Uni6ersity of Surrey, Guildford, Surrey, GU2 5XH UK Received 4 May 1999; received in revised form 14 October 1999; accepted 18 October 1999
Abstract This paper discusses the importance of intra-generational equity to sustainable development. It outlines a number of methodologies for measuring income inequality in the economy, and presents several possible ways of incorporating the impact of distributional effects into measures of welfare in the economy. The authors highlight in particular an index developed by Atkinson (Atkinson, A.B., 1970. Distributive politics and economic growth. Q. J. Econ., May, 465–490.) based on the social welfare model. This method possesses two main advantages over other methods. Firstly, it is expressed directly in terms of social well-being. Secondly, value judgements incorporated into the measure are made explicit through the parameter o which expresses society’s degree of aversion to income inequality. The paper calculates the value of the Atkinson index for two case study countries (Sweden and the UK) between 1950 and 1996 for a central estimate of o=0.8. The results show that the welfare loss due to inequalities in the distribution of income varied between 5 and 10% for Sweden, and between 6 and 14% for the UK, with the higher values coming towards the end of the period. The paper explores the sensitivity of these results to changes in the value of o for the case of the UK, and discusses the relevance of the work to the measurement of sustainable welfare. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Equity; Sustainability; Income distribution; Income inequality; Gini coefficient; Atkinson index
1. Introduction Equity is a key concept in sustainable development. The literature on sustainable development * Corresponding author. E-mail addresses: [email protected] [email protected] (T. Jackson)
(S.
Stymne),
and on ecological economics has devoted most attention to the concept of inter-generational equity. Although well recognised in economic theory, the concept of intra-generational equity has received less attention in the ecological economics literature. Nevertheless, it is clearly important to sustainable development because there are recognised links between income inequality, economic
0921-8009/00/$ - see front matter © 2000 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 1 - 8 0 0 9 ( 9 9 ) 0 0 1 4 4 - 5
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growth, human capital and the environment. Thus, levels of inequality in the economy may have considerable impact not only on present levels of well-being, but also on the well-being of future generations. This paper discusses those links in conceptual terms (Section 2). It then outlines a number of methods for measuring income inequalities (Section 3) and discusses the question of integrating those measures into measures of national welfare (Section 4). Using two of these measures, it then presents a time series analysis on trends in the distribution of incomes in two case study countries (the UK and Sweden) and carries out a sensitivity analysis (for the UK) on one key parameter — the value of o in the Atkinson inequality index (Section 5). The differences between equity, equality, fairness and justice have been extensively discussed in the literature (e.g. Le Grand et al., 1976; Daly 1992; Dasgupta, 1995; Sen 1997). Quite clearly the concept of intratemporal equity is broader than the concept of intratemporal income equality. A thorough analysis of the former issue must pay attention to the intratemporal distribution of a wide variety of resources, including natural, environmental, cultural, human and social resources as well as purely financial ones. Acknowledging these limitations, it is nonetheless our contention that the distribution of incomes in the economy represents a reasonable proxy with which to illustrate the welfare impacts of intratemporal equity, and this paper proceeds on that basis. 2. Well-being and income inequality Traditional measures of economic growth, such as the gross domestic product (GDP), reflect changes in the absolute level of activity but tend to ignore relative and positional changes. A dollar income rise to a poor person is assumed to have the same welfare effect as a dollar increase to a rich person, and aggregate increases in income are assumed to yield equivalent increases in well-being no matter how they are distributed. In reality, however, we would expect the distribution of incomes to have differential effects on well-being for a number of reasons.
In the first place, most societies express some kind of social preference for equality over inequality; i.e. a society with less inequality in the distribution of resources is preferred to one with more inequality. As a rule, therefore, societies tend to strive for a more equal distribution of resources, although there are different views on what the right le6el of equality for a society is. Some countries might emphasise the poorest people in society, while others strive for total equality. Daly (1992) argues that a ‘good distribution is one that is just or fair, or at least one in which the degree of inequality is limited within some acceptable range.’ Le Grand et al. (1976) identify several approaches to the question of a fair distribution: the minimum standard approach — which is concerned only with the poor in the society and argues that nobody’s income should fall below a certain minimum level; the total equality approach — which argues that everyone should have the same income, i.e. the bottom 10% of the population should receive 10% of the income; the need or desert approach — which accepts inequalities either on the grounds that some people need more income or because people deserve more due to own effort, sacrifice, intelligence, etc; equality of opportunity or procedural approach — inequality accepted if everyone has had the same opportunity, or if the distribution is a result of a fair process. The social justice approach introduced by Rawls (1971) is what Le Grand et al. (1976) refers to as a ‘combined approach’ in which inequalities are only justified to the extent that they benefit the least advantaged. Related to the issue of fairness is that of the diminishing marginal utility of income: when a person is poor s/he would benefit more from an income rise than if s/he were rich. This, in turn, would suggest that a transfer from a rich person to a poor person decreases inequalities in a society, and thereby raises the overall level of national well-being. Dalton (1920) pointed out that all inequality measures should have this characteristic, i.e. that a transfer from a rich person to a poor person should always reduce the value of the inequality index.1
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A third issue linking inequality and well-being is the relationship between economic growth and equality. The question here is whether there is a trade-off between economic efficiency (higher national income) and equity (a more equally distributed income). The conventional view has been that striving for income equality slows down economic growth for several reasons. Firstly, it is argued that higher equality will lead to less incentive to work and less incentive to be productive. (This is related to the impact of tax rates, and is only one of many incentive effects.) It has also been argued that higher equality can lead to a reduction in domestic savings and thereby a reduction in growth. This argument is based on the assumption that rich people have a higher marginal propensity to save (Klasen, 1994). In recent years, however, the issue of the relationship between growth and income inequality has been turned on its head. Income equality is now being advanced by some as a promoter of growth (Perotti, 1993; Alesina and Rodrick, 1994; Persson and Tabellini, 1994; Be´nabou, 1996). In these studies, it has been argued that pre-tax income equality could dampen the demands for redistribution policy (financed by taxes) and hence enhance investment, education and R and D. A further reason for incorporating considerations of intra-generational equity into assessments of sustainable welfare is the relationship between investment and income inequality. The potential conflict between investment in savings (for future welfare) and investment in improvements in intra-generational equity has already been remarked upon. The level of direct and indirect investment in human capital is also of importance for the sustainability of an economy. A healthy and well-educated work force will help to ensure future generations’ consumption possibilities. Research has shown the equalising income differentials might have greater effect on the status of health and mortality than increasing income (Fritzell and Lundberg, 1995; Wilkinson, 1996). This is of particular importance in developed countries where the relative dimension, i.e. 1 This has become known as the Pigou–Dalton criterion (Sen, 1997).
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how a person’s economic situation compares to others can trigger ‘psychological mechanisms’ that can affect the status of health. From the point of view of sustainable development, it is clearly important to question whether or not there is a relationship between intra-generational equity and environmental quality. A now well-known hypothesis put forward by Kuznets (1967) supposes that as income levels increase (through economic growth), income inequality passes through an inverted U-shaped curve, with increasing levels of inequality in the early years of development giving way to diminishing inequities as development advances. A similar curve (termed the Environmental Kuznets Curve) has been proposed for the relationship between environmental degradation and levels of income. It should be noted that both these hypotheses are contentious;2 and any conclusions that could be drawn from these parallel relationships are beyond the scope of this paper. However, recent investigations do indicate that there are important relationships between equity and environmental quality. Boyce (1994) has argued that a more equitable distribution of power contributes to improvements in environmental quality. His definition of a power function is based on a combination of an income inequality index (Gini), a literacy variable, political rights and civil liberties, and certain other factors (mainly geographical). The overall conclusion from a study of seven different environmental factors for a cross-section of high and low income countries is that the ‘results provide fairly robust support for the hypothesis that greater inequality in the distribution of power leads to more pollution’ (Torras and Boyce, 1998). This hypothesis also appears to be supported by empirical work in relation to the distribution of power within a country (Boyce et al., 1999). The basis for the correlation between greater inequalities and increased environmental degrada2
On the environmental Kuznets curve, see the special issue of Ecological Economics, 25 (2), 1998, in relation to income inequality; it should be noted that the results reported in this paper provide no obvious support for the Kuznets curve hypothesis.
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tion can be summarised in three points (Boyce, 1994). 1. In a situation where there are benefits as well as costs of environmental degradation, the extent of the degradation will depend on who is most powerful (the winner or the loser). As power and wealth are often correlated, it is likely that the rich will be the ones with power. If these are the ones who benefit from the degradation, there will be greater environmental degradation since the difference in distribution leads to some groups in society not having the power to counteract the costs. This is the main argument in Torras and Boyce (1998). 2. Greater inequality leads to less concern for the future, i.e. a higher rate of environmental time preference. The poor have a high environmental time preference as they are concerned with day-to-day survival rather than future environmental degradation. The rich, Boyce argues, also experience high rates of environmental time preference because political and economic inequality pose threats to the legitimacy of the powerful (for instance, through social unrest). This prompts those in power to pursue the extraction of short-term profits even if this is at the expense of future environmental degradation. 3. Environmental degradation is often valued in willingness to pay, which is related to the ability to pay — income will affect the valuation of the costs and benefits. Greater inequality raises the benefits to the rich, relative to the costs of the poor. There are clearly a number of other complex relationships between income distribution and the environment, exemplified, for example, by the extent to which security in low income families in developing countries is often gained through larger families, which in turn leads to higher environmental impacts (Markandya, 1998), or by the extent to which identity in developed economies is developed through materially intensive consumption patterns (Jackson and Marks, 1999). The underlying issue in all of these relationships is the question of the distribution of benefits versus the distribution of costs. Higher
consumption patterns benefit richer communities, but the cost of these consumption patterns often impact most on poorer communities. It is clear from these considerations that the relationships between intra-generational equity and sustainable welfare are complex, but of considerable importance. As the UNDP (1996) has pointed out: ‘average material welfare can be defined by the per capita GDP. However, statistical averages can mask the diversity that exists within any country. Therefore, from a sustainable development perspective, it is informative to examine income and wealth distribution throughout a population.’ This brings us to the issue of how to measure inequalities and how to include consideration of these inequalities into measures of national well-being. This is the subject matter of the following two sections.
3. Measuring income inequalities There are several different types of inequality measures. Coulter (1989) divides inequality measures into four distinct types, according to the mathematical model on which they are based. These are: measures based on the combinatorial model; measures based on the entropy model; measures based on deviation models; measures based on the social welfare model. The first type of measure, based on combinatorial analysis, ‘reflects the probability of randomly selecting a pair of identical units (for equality polarity) or different units (for inequality polarity) from a pool of units divided among two or more components’ (Coulter, 1989). The second type of index, using the entropy model, is ‘generally based on an interpretation involving the number of bits of information that are necessary to identify the location of any unit in its component’ (Coulter, 1989). Measures based on the deviation model aim to illustrate to what extent a value deviates from a set standard. Measures belonging to this group are mainly based on the absolute, relative and squared deviations from the mean or mode. These are all frequently used measures for assessments
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of intra-generational and inter-generational equity. The most commonly used deviation index is probably the Gini coefficient. The final type of measure, based on the social welfare model, attempts to measure the social welfare implications associated with particular levels of inequality. In this context, social welfare is taken to mean the well-being or happiness of a society. However, since it is difficult to actually measure well-being or happiness, the utility from income is often used as a proxy for welfare. For example, Dalton (1920) proposed measuring social welfare W as the aggregate of the utilities U(yi ) associated with each income yi. Thus: W= %i U(yi )
(1)
Dalton is also often referenced as the first to argue that a measure of income inequality could be based on this social welfare model. In practice, of course, what is required to carry out this measurement is a way of relating different incomes to the utility associated with them. In this paper, we focus on two specific types of welfare measure, namely, a deviation-type measure based on the Gini coefficient, and a method first proposed by Atkinson (1970) based on the social welfare model. These two measures are examples of what Sen (1997) classifies as objective and normative measures, respectively. Where the Gini coefficient is used only to rank different levels of inequality in an objective fashion, the Atkinson index is normative in the sense that it incorporates specific value perspectives by relating income inequality to social welfare. In the following subsections, we present time series data on the distribution of incomes in Sweden and the UK for each of these different types of measures.
3.1. Gini coefficient for Sweden and the UK The Gini coefficient is measured as one-half of the average of the absolute difference between all pairs of relative incomes. The Gini coefficient is often explained graphically as the ratio of the area difference between the curve of actual income distribution and the line of equal distribution. The coefficient takes a value between 0 and 1, where 0
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represents total equality. The higher the value of the Gini coefficient, the greater the level of inequality. Fig. 1 shows the value of the Gini coefficient in the UK and Sweden between 1950 and 1996. It is clear from the figure that prior to 1980, income inequality declined consistently in Sweden, mainly as a result of a number of specific social welfare policies. In the UK, by contrast, the distribution of income remained more or less constant until about the mid-1960s. From then, until the mid-1970s inequality in the UK fell slightly. In both countries, however, income inequality increased during the later years of the period, although this trend is considerably more noticeable in the UK than it is in Sweden.3
3.2. Atkinson index in Sweden and the UK The Atkinson index can be interpreted as ‘the proportion of the present total income that would be required to achieve the same level of social welfare as at present if incomes were equally distributed’ (Atkinson, 1983). Atkinson suggested that it is possible to derive the total welfare corresponding to a particular distribution of income according to the following formula:
W= Y* %i (yi /y)(1 − o)·pi
n
(1/1 − o)
(2)
where Y is the total income; yi is the mean income of the i th group; y is the mean income of the total income population; pi is the proportion of the 3 The Swedish index is based on several different studies, as no single study covers the whole time period in a consistent fashion. The three main sources were a preliminary study by Bjo¨rklund (1995) on individual income distribution for the years 1951 – 1958, 1960 – 1976, and on disposable household income distribution for years between 1975 – 1996 from the income distribution study 1995 (SCB, 1997) and (Jansson, 1994, 1994a). For a discussion of the data set used, see Jackson and Stymne (1996). The UK index is calculated for the period 1954 – 1984 from income distribution data compiled on a tax unit basis and published in Economic Trends (ET, various years). A second data set for 1977 – 1996 is based on income distribution data by household units compiled in the Family Expenditure Surveys (FES, various years). For a discussion of the data set used, see Jackson and Marks (1994) and Jackson et al. (1997).
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Fig. 1. The Gini coefficient in Sweden and the UK, 1950 – 1996.
total income population in the i th group; and o is a factor which represents the weight attached by society to inequality in the distribution of income. The Atkinson index is then defined by: I =1−
W Y
(3)
Since welfare falls as the inequality of income distribution rises, the Atkinson index provides an increasing function of inequality in the economy, defined by the difference (normalised with respect to total income) between the total income and the welfare which it delivers. In a perfectly distributed economy, yi =y for each income group, and so the welfare level is given by:
n
W = Y* %i pi
1 1−o
=Y
(4)
In this case, the inequality measure I reduces to 0, as would be expected. The factor o is an important parameter in the measure. It represents society’s preference for
equality of distribution of incomes. Since it is possible to conceive of societies which have a positive preference for an unequal distribution of income, it is clear that o can take both negative and positive values. When o = 0, society is indifferent to the distribution of income, and welfare again reduces to the total income in the economy:
n
W=Y* %i
yi ·pi = Y y
(5)
and welfare is considered equal to the total income.4 The parameter o therefore allows explicitly for the possibility of attributing different welfare levels according to different attitudes towards inequality in society. A value of 0 would mean that society is indifferent to the distribution of income. As the value of o rises, more weight is placed by society on the lower income groups. When o reaches , society will accept nothing less 4
To see this, note that y = Y/P where P is the total income population and Yi= yi ·pi ·P is the total income in the ith group. W then reduces to SiYi =Y
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Fig. 2. The Atkinson index for Sweden and the UK, 1950 – 1996.
than total equality for all sectors of the population. By contrast, a value below 0 would mean that society is prepared to lose some income in order to achieve greater income inequality. The value of o can be determined, in theory, in terms of transfer efficiency. The method is explained by Atkinson (1983) through a ‘thought experiment’ in which he looked at how much a rich person would be prepared to lose in transfer costs (from administration or inefficiency for example) when distributing income from the rich to the poor. According to Atkinson, a transfer will only take place if the net benefit (including transfer losses) is positive. This thought experiment provides a formula for determining o given by: 1 =do x
(6)
where x is the proportion of income that is to be transferred to the poorer person for the rich person to accept the transfer and d is the (proportional) distance between the rich and the poor person. As an example, suppose that a richer
person has twice the income of a poorer one (i.e. d= 2) and that s/he is prepared to lose 40 pence in transfer costs (i.e. x=0.4). Then o is given by 1/0.6 = 2o (i.e. o= 0.74). Fig. 2 illustrates the value of the Atkinson index for Sweden and the UK between 1950 and 1996, using an o value of 0.8.5 The basic trends illustrated in Fig. 1 are also apparent in Fig. 2: improvements in income distri5 The income distribution data for the UK has been taken mainly from a report prepared by the Institute of Fiscal Studies providing decile shares of post tax income for the years 1961 – 1991 (See Table 2.3 in Goodman and Webb (1994)). For the years not covered by this study, we have used an index based on Gini coefficient data to extrapolate the Atkinson index. For Sweden we have used disposable income per consumption unit for family units in decile groups published by Statistics Sweden (Statistiska meddelanden: Be21SM various years). For those years where income per consumption unit was not available, income per family unit was used and linked to the years where income per consumption unit was available. For those years where no decile data on disposable income could be found, we used an index based on Gini coefficient data to extrapolate the Atkinson index.
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bution during earlier years of the period are offset by greater inequality in the later years. Again, the trend towards increased inequality since about 1975 is more marked in the UK. In this case, however, Fig. 2 provides an interpretation of this increase in terms of social welfare. The Atkinson index I can be interpreted as the loss of welfare associated with a given level of inequality in the distribution of incomes. Fig. 2 reveals that in 1978 this loss of welfare for the UK was around 6.5%, a slight improvement over the 9% loss associated with income inequality in 1950. By 1996, on the other hand, the welfare loss had more than doubled to over 14%.
4. Incorporating income inequality into a welfare index It is clear from the discussion above that the Atkinson index has the advantage of offering an immediate interpretation in terms of social welfare, and can thus be used to incorporate the effects of income inequality directly into welfare measures. For example, where income is used directly as a proxy for social welfare, we find that Eq. (3) can be recast as: Yadj =Y*(1− I)
(7)
Yadj now represents the distribution-adjusted welfare measure. This method can be generalised in a straightforward fashion to other kinds of welfare measures W through: Wadj = W *(1−I)
(8)
In the following section we present a case study in which the Atkinson index is used to adjust several different kinds of welfare measure in the two case study countries (Sweden and the UK). First, however, it is worth pointing out that a number of other suggestions have been made concerning the incorporation of distributional aspects into welfare measures. In the literature, distributional adjustments have been made, for example, to the GDP, the World Bank’s human development index (HDI) and Daly and Cobb’s index of sustainable economic welfare (ISEW) (Daly and Cobb, 1989). Each of these indicators
incorporates some kind of income concept as its basis, and it this income variable that is most obviously open to adjustment from a distributional perspective. Perhaps the most widely used methodology incorporates the Gini coefficient in some form. A Gini-based welfare indicator was derived, for example, by Sen (1976, 1997) and has been used in several empirical works, such as by UNDP (1993) (to correct the HDI) and by Klasen (1994) (to adjust income in the USA). A welfare function adjusted using the Gini coefficient could take the following shape (as in the Human Development Index (UNDP, 1993)):Wadj = W *(1− G)where W is the welfare index, G is the Gini coefficient and Wadj is the distribution-adjusted welfare index. Alternatively, the adjustment could be made using a Gini index formulated relative to a particular base year:
(10)
(11)
Wadj = where Grel =
W * 100 Grel
100 * Gn Gbase
Gbase is the Gini coefficient in the base year, and Gn is the Gini coefficient in the year of interest. Even though this method is quite widely used there are several problems with it. Firstly, although the Gini coefficient satisfies the principle of transfers — i.e. a transfer from a rich person to a poor person always reduces the inequality measure — it does not satisfy the principle of diminishing transfers — i.e. that the effect of a transfer diminishes as the absolute level of income increases (Schwartz and Winship, 1979). Further, in spite of the classification of the Gini coefficient as an objective measure, it does implicitly include value judgements. For example, distributions towards the middle are implicitly preferred in the index. However, these value judgements remain hidden within the index. Perhaps the most intractable problem is that there is no direct welfare-theoretic interpretation of the Gini index. By contrast, there are several specific advantages to the Atkinson index. Firstly, of course, the interpretation in welfare terms is straightforward,
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since the Atkinson index is formulated from a welfare-theoretic model. In addition, however, there is much greater transparency with regard to value judgements. Given that the conventional summary measures inevitably introduce distributional values, Atkinson (1983) argues that ‘it may be preferable to consider such values explicitly. Only then can it be clear just what distributional objectives are being incorporated as a result of adopting a certain measure.’ The Atkinson index incorporates these value judgements explicitly through the value o in Eq. (2). This allows the user of the index to incorporate particular value judgements about the importance of distributional elements to welfare. It should perhaps be mentioned that it would also be possible to construct a distribution-adjusted welfare model using a relative Atkinson index by a straightforward analogy with the method proposed in Eqs. (10) and (11) for the Gini coefficient. In this case, the distribution-adjusted measure Wadj would be given by:
(12)
(13)
Wadj =
W * 100 Irel
where Irel =
100 * I Ibase n
Ibase is the Gini coefficient in the base year, and In is the Atkinson index in the year of interest. It is not clear however, that this method offers any advantages over a direct welfare-theoretic adjustment. Table 1 summarises a variety of attempts to adjust welfare measures for distributional properties.
5. Case study: distribution-adjusted welfare measures for Sweden and the UK This section reports on a time-series analysis of the impact of adjusting two specific measures for distributional effects using the Atkinson index. Firstly, we apply the Atkinson index to time series data on personal consumer expenditure in Sweden and the UK between 1950 and 1996. Secondly, we apply the index to adjust the index of sustainable
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economic welfare in each of these case study countries. As noted in the previous section, all inequality measures include value judgements. In most cases these value judgements remain hidden within the methodological assumptions made. However, in the Atkinson index, some of these values are made explicit through the parameter o. This parameter is defined as: ‘the weight attached by society to inequality in the distribution’ (Atkinson, 1983). Although this construction works in theory, placing an appropriate value on o at the national level is difficult. Empirical studies of the value are scarce. Schwartz and Winship (1979) refer to Stevens (1959), Schwartz (1974) and Winship (1976) who all used ‘attitudinal survey data about the level of well-being associated with different levels of income’. The results indicated that o should take a value between 0.5 and 0.75. Schwartz and Winship (1979) also refer to Stern (1977) who examined data on individual consumer maximising behaviour. His results indicated that o should range between 0 and 10 with a best ‘guesstimate’ of 2. Schwartz and Winship themselves argued that ‘most sociologists would agree that when using Atkinson’s measure to address normative questions, o should be between − 0.5 and 2.5’ (Schwartz and Winship, 1979). In choosing appropriate values of o for this study, we have been guided mainly by a study by Blundell et al. (1994) (cited by Pearce and Ulph (1995)) based on household consumption behaviour over time. The value of o emerging from this study was 0.8. It is most probable that inequality aversion in the UK and Sweden differ, and therefore arguable that o should also differ. However, at the current stage of the research, no value of o has been found for Sweden, and we therefore used 0.8 as our central value in both case study countries. However, it is clearly appropriate to investigate the sensitivity of distributional adjustments to changes in the value of o. Table 2 below shows the variation in the Atkinson index (I) in Sweden and the UK for a range of o values. Using a value of o= 0.8, the Atkinson index for the UK in 1992 is 0.136. The interpretation of this figure is that the UK could reach the same level of social welfare with only 86.4% (i.e.
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Table 1 Overview of distributional adjustments to welfare measures Description
Income inequality index used
Basis adjusted
Result
Income inequality adjusted growth rates (Klasen, 1994)
Integrates distributional components into changes in well-being, where well-being is expressed as income.
4 different types used: 1. Equal weights 2. Poverty weights 3. Gini 1 4. Gini 2
Family income before and after tax. Applied to the USA 1947–1991.
Gini coefficient
The income component of the HDI. This component is then multiplied by (1−Gini).
An attempt to enlarge the Gini coefficient scope of distributional issues in the HDI, to include distribution in longevity and education.
Each of the three components of the HDI are adjusted for inequality by a factor of li (1−Gi ), where Y is a weighting factor so each dimension could be given a different weight.
The income distribution adjusted measure shows an improvement in the growth rate during the 1960s and a down-turn during the 1980s, i.e. without the income distribution adjustment, the growth rates are underestimated during the 1960s and overestimated during the 1980s. The HDI index is lower when accounting for income inequalities. The ranking of the countries slightly changes. Sweden, for example, changed from 5th place to 3rd place, and the UK from 10th to 9th place (year 1993). Only looked at developing nations. The percentage loss of HDI varies from 30–57%, but does not change ranking by more than four places.
Income adjusted human Attempts to adjust the human development index (HDI) development index using (UNDP, 1992, 1993) income distribution. The HDI is a decomposition index consisting of three variables: income; education; and longevity. Inequality adjusted human development index (Hicks, 1997)
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Name and author
Table 1 (Continued) Description
The index of sustainable A measure of sustainable economic welfare (ISEW) welfare that takes the (Daly and Cobb, 1989) distribution of income into account.
Income inequality adjusted national income (Beckerman, 1980)
Income inequality index used
Basis adjusted
Result
Low quintile index, where variations in the lowest quintile are monitored. This fits in with Rawl’s theory of justice. 1950 is set as a base year (= 100).
The basis for the ISEW is personal consumption, which is adjusted for income inequality.
The weighting has a negative effect on the USA index, penalising rising income inequality. The ISEW has been applied to several other countries, of which the UK and Sweden are two. The methodology for accounting for income distribution has changed in these studies, and is described in the empirical section of this paper. Beckerman comes to the conclusion that taking changes in income distribution into account ‘barely affects the growth rates of most countries’. Applied to several developed nations including UK and USA over the period of two decades (between 1950 and 1973).
An experimental calculation Atkinson income inequality index where the conventionally measured growth rates are compared with the growth rates of ‘equivalently distributed income’.
National income
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Name and author
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Table 2 Atkinson index in the UK and in Sweden in 1992 for different o values o= −0.5
Atkinson index (I)
SWE −0.034
o =0.8 UK −0.065
SWE 0.083
1 – 0.136) of present total income, if the incomes were equally distributed. (it is to be noted, of course, that the value of I depends not only on the value of o, but also on how current income is distributed). Figs. 3 and 4 show distributionally adjusted personal consumer expenditure for Sweden and the UK (respectively) using an o value of 0.8. It is clear from the figures that the adjustment has a depressive effect on the chosen measure, although the effect is somewhat more marked for the UK than it is for Sweden. Since the beginning of this study period (year 1950) both Sweden and the UK have been characterised by rising GDP per capita and rising levels of consumer expendi-
o =1.6 UK 0.136
SWE 0.168
o =2.5 UK 0.250
SWE 0.265
UK 0.351
ture. The two countries have, however, had different income distribution policies. In Sweden, one of the main long-term goals of the government has been to smooth out inequalities in the economy, and this was clearly successful (as Figs. 1 and 2 illustrate) at least until the early 1980s. In the UK, by contrast, intervention by the government has been limited. It is, for example, only very recently that the government has established a minimum wage for the UK. Atkinson (1993) points out several domestic reasons behind rising inequalities in the UK: a shift from workrelated to benefit-related income, changes in benefits coupled with a rising number of unemployed and pensioners, rising inequalities among
Fig. 3. Distribution-adjusted per capita consumer expenditure in Sweden (1950 – 1996).
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Fig. 4. Distribution-adjusted per capita consumer expenditure in the UK (1950 – 1996).
those not in work and a rise in earnings inequalities. The same kind of distributional adjustment can also be applied to the Daly and Cobb ISEW. The original formulation of the ISEW incorporated income inequality through the use of a relative Gini-coefficient adjustment (as set out in Eqs. (10) and (11)). In the most recent version of the UK ISEW, however, Jackson et al. (1997) proposed using the Atkinson method in place of the Gini coefficient method for the reasons discussed at the end of Section 4. Figs. 5 and 6 show the effects of this adjustment on the ISEW for Sweden and the UK, respectively, using an o value of 0.8. These graphs illustrate the now-familiar departure of the trend in ISEW from the trend in GDP over the later years of the study. However, they also show the impact which income inequality adjustment has on the index. In both case study countries, the distribution-adjusted ISEW is depressed below the unadjusted measure. Fig. 5 illustrates that the negative impact due to income inequality adjustments in Sweden is relatively con-
stant over the time period, indicating that the welfare impact of inequalities in Sweden has not changed drastically over the time period of the study. However, Fig. 6 shows that the negative effect is considerably greater for the UK. Indeed, the impact of the income inequality adjustment changes the shape of the ISEW over the later years of the study from one in which sustainable economic welfare is relatively stable (although with some variations) to one in which sustainable economic welfare is declining. It is clear from this analysis that distributional adjustments can have a significant influence over judgements about the trend in real welfare over time. However, as Fig. 7 shows, these influences are critically dependent upon the particular value chosen for the parameter o. Fig. 7 shows a sensitivity analysis on the distribution-adjusted ISEW for the UK over the period 1950–1996, using values of o ranging from − 0.5 to 2.5. It should be remembered (Figs. 1 and 2) that in general terms income inequality has increased in the UK over this time, particularly
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towards the later years of the study. Thus, in a society which is averse to income inequality (o \ 0), the measure would be expected to experience a downward influence in the later years. Conversely, in a society which positively favours income inequality (oB 0), the reverse trend would be visible. Both these trends are visible in Fig. 7. At o = 0, of course, the ISEW reduces to an index which takes no account of income distribution, since at this value society has no aversion to income inequality. For higher negative values of o, Fig. 7 illustrates a rather significant depressive effect on the welfare index over time. In fact, the choice of an o value of 2.5 leads to a shift in the ISEW which dominates most of the other adjustments to the index, including those introduced by ecological variables (Jackson et al., 1997). Thus, in a society where there is a high aversion towards income inequality (i.e. there is a high o value), distributional issues could be given as high a priority as environmental issues, or perhaps even a higher one.
It would be possible to take an even broader approach to the distributional issue, which accounts not only for income inequalities, but also for inequalities in the distribution of ecological resources. This could change the relative emphasis on ecological and distributional variables in the ISEW considerably. One possible outcome might be that a country with a high aversion to income inequality would also have a high aversion to ecological inequalities, and the depressive effect on the welfare measure would be increased further over time. Taken in conjunction with the arguments of Boyce and his coworkers discussed in Section 2, these considerations reinforce the conclusion that addressing the problem of income inequality is a critical component in the search for sustainable development.
6. Conclusions This paper has argued that there are good reasons for incorporating some account of the
Fig. 5. Distribution-adjusted ISEW and GDP per capita in Sweden (1950 – 1992).
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Fig. 6. Distribution-adjusted ISEW and GDP per capita in the UK (1950 – 1996).
level of intra-generational equity into national measures of well-being in the economy. Furthermore, it has been pointed out that intra-generational equity also plays an important part in the determination of future well-being, and a critical role in the search for sustainable development. We have reviewed a number of attempts to construct indices of inequality in the distribution of income-related variables and to incorporate such indices into measures of welfare. In particular, we have examined in some detail an index proposed by Atkinson (1970) based on the social welfare model, and applied this index to measures of welfare in two case study countries. The results of the empirical analysis suggest that adjusting for distributional effects can have significant impacts both on the value of welfare measures, at particular points in time, and on the trend in such measures over time. The magnitude of this impact will depend both on the degree of inequality in the distribution of incomes during the time period in question, and also on the value of the parameter o
— the degree of aversion to income inequality in society. The work reported in this paper suffers from some clear limitations. In the first place, empirical data on appropriate values of o are sparse. Limited references in the literature suggest a value of 0.8 as appropriate in the UK, but this work is now somewhat dated, and no comparable data were found for Sweden. Work on evaluating o in the case study countries is continuing. This paper has limited the discussion of intragenerational equity to the distribution of incomerelated variables. However, it could clearly be argued that the distribution of other resources has important consequences for sustainable welfare. For example, the income concept could be widened to include ecological factors. This was, for example, done by Ruitenbeek (1996) when he looked at the distribution of ecological income in a village in the Cameroon. Eisner (1994) suggested that distributional adjustments should be made to the total ISEW rather than just personal
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Fig. 7. Sensitivity of distributional adjustments in the UK to the value of o.
consumption. Hicks (1997) has suggested a technique for adjusting the longevity and educational variable of the HDI with a distributional variable. The relationship between income distribution and the environment was explored by Boyce (1994), reviewed in Section 2 above. In spite of its limitations, the analysis in this paper has confirmed the value of incorporating distributional aspects into measures of current well-being in society, and has indicated the relevance of distributional issues for future welfare levels. Moreover, the techniques developed in this paper could potentially be extended to other aspects of welfare including the distribution of ecological, social and human capital.
5110, under the Environment and Climate Programme), by the Engineering and Physical Sciences Research Council and by the Royal Academy of Engineering. An earlier version of the paper was presented at the European Ecological Economics Society’s conference in Geneva March 4–7 1998, and we are grateful for critical input and advice from a number of people including Anthony Atkinson, Giles Atkinson, Steven Dodds, Alissa Goodman, Andrew Klemer, KarlGo¨ran Ma¨ler and Jack Ruitenbeek. The views expressed and any remaining errors are, of course, the responsibility of the authors.
References Acknowledgements The work described in this paper has been supported in part by the European Commission (TMR Marie Curie Research Training Grant: numbers ENV4-CT96-5033 and ENV4-CT98-
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