Ecological sustainability, social inclusion and the quality of life:
Identifying potentials for prosperity without growth
Martin Fritz (GESIS Cologne; Martin.Fritz@gesis.org) and Max Koch (Lund University;
max.koch@soch.lu.se)
First draft
Abstract
Recent contributions to ecological economics and related social sciences indicate that issues
such as climate change, resource depletion and environmental degradation cannot be effectively addressed under conditions of continued economic growth. This paper aims to identify
potentials for prosperity in the absence of economic growth. Its theoretical focus builds on the
growing literature that interprets economic policy goals in terms other than quantitative GDP
growth and instead highlights individual and social welfare, well-being, capabilities and the
quality of life. The paper employs an empirical three-dimensional approach to operationalise
‘prosperity’ in terms of social inclusion, ecological sustainability and the quality of life. Subsequently, it provides and interprets cluster and correspondence analyses for 35 advanced capitalist countries on the basis of data from sources such as the World Bank, EUROSTAT, the
Global Footprint Network and the OECD. The result is a typology of ‘prosperity regimes’ that
are contrasted with established welfare and employment regime that do not consider ecological indicators. The paper concludes with identifying countries that combine decent levels of
prosperity with comparatively low levels of GDP per capita and with raising issues for future
research and policy making.
1
Introduction
Recent contributions to ecological economics and related social sciences indicate that issues
such as climate change, resource depletion and environmental degradation cannot be effectively addressed under conditions of continued economic growth (Victor 2008; Stiglitz et al.
2009; Gough 2011; Royal Society 2012). Indeed, in the absence of evidence for absolute decoupling of GDP growth and carbon emissions, it is remarkable that most economic policy
approaches do not question the priority placed on GDP growth. This paper aims to identify
potentials for prosperity, which we operationalize in terms of ecological sustainability, social
inclusion and the quality of life, in the absence of economic growth. Its theoretical focus
builds on the growing literature that interprets economic policy goals in terms other than GDP
growth and instead highlights individual and social welfare (Kasser 2009; Koch 2013), wellbeing (Sustainable Development Commission 2007), the quality of life (Nussbaum and Sen
1993) or prosperity (Jackson 2009).
However, any transition towards an economy, where GDP growth is de-prioritized and/or
replaced by other parameters, will have to take into account and depart from the institutional
structures of existing economies and societies. Such transition is facilitated if the different
degrees of success to which present countries are promoting prosperity are empirically identified. For this purpose, the paper employs an empirical three-dimensional approach to measure
prosperity in terms of social inclusion, ecological sustainability and the quality of life. Subsequently, we carry out cluster and correspondence analyses for 35 advanced capitalist countries
using data from different organizations such as the World Bank, EUROSTAT, the Global
Footprint Network, and the OECD. On this empirical basis, we create a typology of prosperity
regimes that we contrast with established welfare regime typologies (Esping-Andersen 1990)
that do not consider ecological indicators. Hence, we aim to identify countries that combine
decent levels of prosperity with comparatively low levels of GDP per capita: If overdeveloped countries in terms of GDP have sustained high levels of social welfare but at the
cost of severe ecological damage, we ask whether there are also countries with relatively high
levels of social cohesion and life quality in combination with comparatively low levels of
ecological stress. The paper concludes with a discussion of the implications of the empirical
results for policy-making.
2
Theorising prosperity and economic development
Prosperity is commonly conceptualised in socio-economic terms, that is, in terms of equity,
highlighting distributive issues within growing economies in terms of GDP. While GDP, income growth and rising material standards of living are normally not questioned as priorities
in both welfare theories and policy making, there is growing evidence that Western welfare
standards are not generalizable to the rest of the planet if environmental concerns such as resource depletion or climate change are considered. Consequently, the Intergovernmental Panel on Climate Change (2013) emphasizes socio-economic aspects of climate change, including issues of livelihoods and poverty, in its most recent report. Tim Jackson (2009: 488)
demonstrates that in order to achieve conditions where the entire world population enjoys an
equivalent income to EU citizens today, the global economy would need to improve in absolute decoupling of carbon emissions and economic activity by 11.2 percent per year to 2050
and global carbon intensity would need to be less than one percent of its current level. He
concludes that there is as yet ‘no credible, socially just, ecologically sustainable scenario of
continually growing incomes for a world of nine billion people.’ (Jackson 2009: 86)
Increasing doubts in the capability of GDP as an appropriate measurement of societal development and the associated need to complement it with other types of management (Stiglitz et
al. 2009) do normally not lead scholars to question economic growth as an essential requirement for human prosperity as such. This is remarkable, since economics has not always been
interpreted as synonymous with a science of prices and the growth of monetary value (De
Gleria 1999: 84). In the Physiocratic system, for example, the notion of natural resources was
central. The wealth of nations was derived solely from the value of land and the entire economic process was understood by focusing upon a single physical factor: the productivity of
agriculture, which was the only kind of work that created value and surplus. In the seventeenth century, William Petty characterised labour as the ‘father’ of material wealth and the
‘earth its mother’ (cited in Marx 1961: 43). This was also reflected in the classical tradition of
Adam Smith and David Ricardo as well as by Karl Marx, who, far from abstracting from natural resources and matter in his analysis, began Capital with an examination of the commodity and its twofold character as use value and exchange value, which renders his analysis amenable to ecological laws. While the exchange value aspect of the commodity emphasises the
logic of unlimited valorisation, quantitative and geographic expansion of the scale of production and the circular and reversible moments of the production process, the use value aspect
3
considers qualitative matter and energy transformations and hence irreversibility, the narrowed stock of natural resources, and their limited capability to serve as both sources and
sinks for the increasing flow and throughput of matter and energy (Koch 2012: 25–35). John
Stuart Mill is credited for arguing that economic growth was necessary only up to the point
where everyone enjoyed a reasonable standard of living (Victor, 2008: 124; Daly and Farley
2009: 55). He envisioned a ‘stationary state’ of the economy that would move beyond individual status competition and in which both population and the capital stock ceased to grow.
Indeed, writing in the 1840s, Mill precluded the essentials of the contemporary ‘degrowth’
debate by not conflating a stationary condition of capital and population with a stationary
state of societal development (Mill 1848). John Maynard Keynes (1963: 96), for his part, predicted that by his grandchildren’s lifetime the economy would not need to grow further in
order to meet basic human needs. Hence, despite significant disagreement in other matters,
these economists have in common not to regard quantitative economic growth as an ahistorical and quasi eternal goal of economic action and policy but as a temporary and historically
specific necessity in order to reach a socio-economic level of development, in which basic
needs are satisfied and where social actors devote more time to other than economic purposes.
Herman Daly’s steady-state economy (SSE) is probably the most prominent contemporary
approach in ecological economics. Instead of GDP growth, which is a value index of the
physical flows in an economy, the point of departure of a SSE, a primarily physical concept,
is that of a relatively stable population and ‘artifacts’ (stock of physical wealth) and the lowest feasible rates of matter and energy throughput in production and consumption. The scale
of the economy does not erode the environmental carrying capacity over time. Daly is not in
favor of abandoning growth in all sectors of the economy but of viewing it as a ‘process to be
consciously and politically monitored and regulated’ (Barry 2012: 133). Hence, while two
basic physical magnitudes, population and artifacts, are to be held relatively constant in an
SSE, mainly qualitative parameters such as ‘culture, genetic inheritance, knowledge, goodness, ethical codes … the embodied technology, the design, and the product mix of the aggregate total stock of artifacts’ (Daly 1977: 6–7) are free and welcome to evolve. This is also
reflected in Daly’s distinction between ‘growth’ and ‘development’, whereby the former refers to a quantitative increase of GDP, and the latter to qualitative change. Continued technological advances in combination with shorter working hours facilitate the maintenance of high
4
living standards with relative low resource consumption and carbon emissions (Koch and
Fritz 2013). The goal of an SSE is also supported by ‘degrowth’ economists such as Victor
(2008), who has made the greatest effort to date in simulating how an advanced economy and
society could cope without economic growth, Martínez-Alier (Martínez-Alier et al. 2010),
Kallis (2011) and Sekulova (Sekulova et al. 2013).
The case for a SSE and/or ‘degrowth’ is backed up by other disciplines as different as happiness research, sociology of consumption, psychology of well-being and more general concepts of the living standard. Happiness research indicates that once countries have sufficient
wealth to meet the basic needs of their citizens and reach a certain per capita income reported
levels of (un)happiness show little correlation with GDP growth (Layard 2011). As a corollary, extra happiness provided by extra income is greatest for the poorest and declines steadily
as people get richer. Wilkinson and Pickett (2010: 6) make a similar argument in relation to
life expectancy. Among the rich countries, life expectancy increases by between two and three
years every decade, yet this occurs largely ‘regardless of economic growth, so that a country
as rich as the United States no longer does better than Greece or New Zealand …”. Since
Thorstein Veblen’s pioneer studies (Veblen 1970) sociologists of consumption argue that in
rich countries buying things is not in the first place about the goods themselves but rather
about the symbolic message that the act of purchase conveys (Soper et al. 2009). Both acquisition and possession of use values symbolise much of our social standing in society as well
as our identity and sense of belonging. What Hirsch (1976) called the competition for ‘positional goods’ is mediated through a genuinely social logic that Bourdieu (1984) referred to as
‘distinction’. This sets in motion a never-ending cycle of defining taste by the avant-garde and
keeping-up strategies by the mainstream that plays into the hands of the valorisation interests
of various culture industries, but does not contribute to human welfare in the longer term and
contradicts the principal reproductive needs of the earth as an ecological system.1
Psychologists of well-being assume that humans must have certain psychological needs satisfied in order to flourish and experience personal wellbeing (Kasser 2009: 175). Notwithstand1
Buying and consuming stuff tends to imbalance the carbon cycle, since such practices are normally bound to
matter and energy transformations that necessitate the burning of fossil fuels.
5
ing societal particulars and contexts, these needs include feeling safe and secure but also
competent and efficient. People also require love and intimacy but struggle under conditions
of loneliness, rejection, and exclusion. Finally, people have a need for autonomy, that is, the
ability to choose in relative independence from coercion and internal or external pressures.
However, where ‘economic growth is a key goal of a nation’ (Kasser 2011: 194–196), with its
encouragement of self-enhancing, hierarchical, extrinsic and materialistic values, the fundamental needs required for human wellbeing are contradicted, since materialistic people are
more likely to be dissatisfied with life, to lack vitality, and to suffer from anxiety, depression
and addiction problems. Finally, critical economists and philosophers question the utilitarian
perspective that individuals are best able to determine what contributes to their quality of life.
The capability approach, especially, is not so much concerned with the actual choices that
people make as with the options they are free to choose from. While, roughly speaking, ‘functionings’ come close to what psychologists of well-being describe as human needs, ‘capabilities’ include both states of being and opportunities for doing (Hick, 2012). According to Amartya Sen (1993: 37), they encompass ‘such elementary ones as escaping morbidity and mortality, being adequately nourished, having mobility, etc., to complex ones such as being happy, achieving self-respect, taking part in the life of the community, appearing in public without shame’. Martha Nussbaum (2006: 74–8), for her part, proposes a list of ten central human
capabilities sought for each and every person, ranging from physical health and integrity to
the control of one’s environment. Many of these needs or capabilities are interrelated and
complementary and some of them are limited and finite. Most of Nussbaum’s list of central
human capabilities requires few, if any, material resources, allowing for a surplus in welfare
for one person or one generation while still leaving room for the development of others.
Though these theoretical proposals essentially point in the same direction as degrowth economists, insofar they fundamentally question the priority of GDP growth in economic and social policy making, they are as yet mainly studied in ‘separate silos’ (Gough 2011). While
much theoretical work remains to integrate these diverse approaches to a coherent theory, the
present paper addresses some more practical issues in the transition towards a SSE or at least
an economy, where GDP growth is de-prioritised. Our point of departure is that any such transition will have to take into account and depart from the institutional structures of existing
economies and societies. Since knowledge on the degrees to which existing societies promote
‘prosperity without growth’ may facilitate institutional learning processes, we aim to empiri6
cally identify present ‘regimes of prosperity’. For this purpose, we operationalise ‘prosperity’
in terms of three dimensions: social inclusion, ecological sustainability and quality of life. We
also measure the degree to which these dimensions correspond with the level of the economic
development of a country.
We measure the economic development of a country in terms of GDP and unemployment.
GDP includes all goods and services that are annually produced in a country.2 We make two
adjustments to improve the comparability of material living standards across countries: First,
we use GDP per capita to account for different population sizes; second, to adjust for currency exchanges rates, we use GDP per capita as purchasing power parity calculations (PPP),
calculated by the World Bank for 2010. We also use the average GDP per capita growth of
the period 2005-2010, which is likewise provided by the World Bank. Another dimension of
economic development – and an explicit goal of European economic governance – is the
avoidance of (mass) unemployment. Gainful employment not only ensures the subsistence of
people it is also an important source of recognition and social integration (Fritz 2013). By
using World Bank data from 2010, we explore how unemployment is related to the three dimensions of prosperity.
Following the theoretical discussion above, we operationalise ‘prosperity’ as ecological sustainability, social inclusion and quality of life. Similar approaches include efforts to measure
social progress or happiness combining different indicators and dimensions in order to build
an index which provides useful information about the levels of ‘prosperity’ for each indicator
and as a total score for each country (Porter et al, 2013; Abdallah et al 2012). In contrast, we
particularly stress the interdependencies between indicators from different dimensions, thus
focussing more on relations rather than on absolute scores. Ecological sustainability is a complex issue including climate change, resource depletion, biodiversity, environmental degradation through air and water pollution, and deforestation (Lafferty and Hovden 2013). We focus
on two main indicators that cover crucial aspects of ecology: First, we include CO2 emissions
per capita in our analyses by using World Bank data for 2010. Since most production and
consumption activities cause CO2 emissions, we expect that, all other things being equal,
countries with an advanced degree of economic development and a correspondingly high ma2
As a corollary, various informal economic activities but also a range of unpaid care services provided by family
members are excluded.
7
terial living standard emit more CO2 per capita than less developed economies. Conversely,
we regard a country, which provides a comparatively high living standard with comparatively
low CO2 emissions, as a relatively sustainable country.3 Second, we use the ‘Ecological
Footprint’ of a country as an additional indicator for its ecological performance in 2008
(WWF, 2012; Borucke et al., 2013).
Social inclusion, the second dimension of prosperity, is operationalised in terms of cohesion
and civic participation. ‘Cohesion’ is measured by two components, the distribution of incomes and crime rates. We understand a society, where incomes are distributed relatively
equally and crime rates are low, to be relatively cohesive. As indicator for income (in)equality
we use the Gini Index.4 Crime rates are measured at the example of homicide rates.5 ‘Civic
participation’ is also measured by two components. First, we consider the ‘actual’ participation at the example of voter turnout in the last national election by using OECD data for the
period 2008-2012. Second, we include an indicator that estimates the impact of the general
public on state regulations and government action (‘consultation’) by using OECD data from
2008.
The third dimension of prosperity is the quality of life. Many scholars distinguish between
objective and subjective factors in the assessment of the quality of life. Both factors are
doubtless relevant: objective living conditions are constantly seen as in need of improvement,
since individual satisfaction with these conditions is relative and often the result of psychological adaption processes. Subjective satisfaction is likewise important, since increases in material living standards can be accompanied by growing subjective dissatisfaction, especially in
unequal societies characterised by advanced status competition (Kasser, 2011). In the following analysis, we measure both objective and subjective factors. As an indicator for the objective quality of life we use ‘life expectancy’ as provided by the OECD for the period 2009-
3
This does not mean that countries with relative low carbon emissions and Ecological Footprint are necessarily
‘sustainable’ in the absolute sense as defined by the WWF (2006: 19). According to this definition, only a ‘footprint lower than 1.8 global hectares per person, the average biocapacity available per person on the planet’, denotes sustainability at global level.
4
Different organisations provide data on the GINI, including the OECD, EUROSTAT and the World Bank.
5
For this indicator, we use OECD data for the period 2008-2011.
8
2012, and for the subjectively perceived quality of life we consider ‘subjective health’ and
‘general life satisfaction’, both measured using OECD data from the period 2006-2012.
Data analyses
We collected data for 35 countries, most of which are member states of the EU and the
OECD: Australia, Austria, Belgium, Brazil, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Japan, South Korea,
Luxembourg, Mexico, The Netherlands, New Zealand, Norway, Poland, Portugal, Russia,
Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, and the
USA.
Clustering countries to regimes
As a first step, we carried out cluster analyses to test whether countries can be grouped into
‘prosperity regimes’ in terms of three dimensions: social inclusion, sustainability and quality
of life plus economic development.6 A hierarchical cluster analysis, using the Ward criterion
and squared Euclidean distances, led to a solution of three clusters. We then tested the stability of this solution by running several other cluster analyses with different criteria (single
linkage, average linkage etc.). Finally, we ran a k-means cluster analysis as optimisation
method using the cluster means of the first Ward cluster analysis as starting points. Since
cross validation of these two cluster analyses shows little divergence (Table 1), we use the
results of this last k-means cluster analysis as the basis for our interpretation.
Table 1: Cross-validation of clustering countries
K-means Method
Ward
Method
Total
6
Total
Cluster 1
Cluster 2
Cluster 3
Cluster 1
13
0
1
14
Cluster 2
0
6
0
6
Cluster 3
1
3
10
14
14
9
11
34
Luxembourg was omitted from the cluster analyses; due to its extreme values on many indicators it statistically
doesn’t fit into any cluster.
9
The five countries that changed their cluster according to Table 1 were Germany and New
Zealand, which interchanged their positions, and three countries from Eastern Europe, which
shifted from cluster 3 to cluster 2: Hungary, Poland and the Slovak Republic. Overall, the 34
countries were distributed across the three following clusters:
Cluster 1: Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, the
Netherlands, Norway, Sweden, Switzerland, United Kingdom, and the USA.
Cluster 2: Brazil, Chile, Estonia, Hungary, Mexico, Poland, Russia, Slovak Republic, and
Turkey.
Cluster 3: Czech Republic, France, Greece, Israel, Italy, Japan, Korea, New Zealand, Portugal, Slovenia, and Spain.
10
Table 2: Mean values of the three clusters
Indicator
Cluster
1
2
3
CO2
10,44
6,69
7,82
GDP
41627,58
18342,77
29489,78
GINI
29,34
39,28
31,35
UNEMPLOYMENT
7,24
10,23
8,85
CONSULTATION
8,24
5,73
6,95
74,57
67,44
69,36
SATISFACTION
7,28
5,92
6,14
HOMICIDE
1,39
7,89
1,26
FOOTPRINT
6,04
3,70
4,61
HEALTH
77,00
58,11
62,55
LIFEEXPECTANCY
80,98
74,97
81,25
0,69
2,92
1,05
VOTERS
GROWTH
Figure 1: Differences between prosperity clusters (z-scores)
1,5
1
0,5
0
-0,5
-1
-1,5
11
Cluster 1
Cluster 2
Cluster 3
Table 2 (in numbers) and Figure 1 (graphically) contain information about the characteristics
of the three clusters in terms of their mean values for the indicators analysed. The first cluster
assembles the richest countries in terms of GDP per capita. At the same time, these are characterised by the highest values of general life satisfaction and the lowest degrees of income
inequality and unemployment. While economic development is to some extent complemented
by social equity, this group of countries features the highest CO2 emissions and Ecological
Footprints among the three clusters. In other words, countries such as USA, Germany, Sweden or Belgium are united by the coincidence of a high level of economic development, social
standards and perceived life satisfaction. Yet this comes at the price of an extremely unsustainable ecological performance.
The second cluster marks the opposite end of the spectrum. The countries assembled here
perform relatively well in terms of sustainability but much worse in all other respects. Economic development continues to be at the comparatively lowest level despite the highest
growth rates in the ‘emerging markets’ of Brazil, Russia or Mexico. However, this growth is
not accompanied by full employment, since this group of countries suffers from the comparatively highest unemployment rates. Social inclusion and quality of life indicators are far below the first group of countries with examples including a six years shorter life expectancy
and six times higher homicide rates. While these countries fail to achieve socio-economic
minimum standards that can be regarded as absolutely necessary for prosperity, CO2 emissions and Ecological Footprints are the lowest among the clusters and countries analysed.
While the first two clusters indicate the difficulties of combining a decent socio-economic and
material living standard with ecological sustainability, the third cluster provides some evidence that production and consumption practices that spare the environment to a certain extent can be reconciled with comparatively high material living standards and principles of
social equity. This cluster brings together Mediterranean countries such as France7, Italy,
Greece and Spain, East European countries such as the Czech Republic and Slovenia, East
Asian countries such as Japan and South Korea as well as New Zealand. This rather diverse
mix of countries is united by medium-level degrees of economic development. Yet, the ecological stress caused by this development is significantly lower than in the economically lead7
The environmental performance of France is co-determined by its massive use of nuclear energy.
12
ing countries and only slightly higher than in the second group of ‘emerging markets’. Of
special interest is the consideration of the social inclusion and quality of life indicators.
Whereas income inequality is only marginally higher than in the first cluster, homicide rates
are somewhat lower. Also life expectancy is slightly higher in the third cluster than in the
first.
Whereas these ‘objectively’ measurable indicators confirm earlier studies (Wilkinson and
Pickett 2010)8, we arrive at a somewhat different picture when also considering ‘subjectively’
perceived indicators for political participation and the quality of life. Here, the first cluster
scores significantly higher, featuring higher voter turnout and more possibilities for the general public to influence governmental decisions (‘consultation’). Especially striking are the
differences with respect to subjective health and life satisfaction, where the third cluster is
close to the second and the economically most developed countries have a solid lead. Hence,
not objective distances but individually perceived differences in political participation and life
quality characterise the division between the economically leading but ecologically most
harmful countries and the economically fairly well developed countries that display greater
social inclusion and objective quality of life scores as well as greater sustainability.
It is a theoretical and empirical challenge to explain the difference between objectively measured and subjectively perceived indicators of prosperity in the third cluster of countries. Theoretically, we would have expected a greater degree of accordance, since previous studies suggested that more egalitarian countries tend to also display higher ‘happiness’ scores (Layard
2011; Wilkinson and Pickett 2010), for example. One could hypothesise that the ‘economic
success’ and the general way of life in the countries of the first cluster functions as the
benchmark for citizens of countries in the second and third cluster who then are less satisfied
with their lower standard of living and thus somewhat underestimate the socio-ecological performances in their own countries9. There might also be a link between the degree of activity
and perceived political influence of citizens and their general life satisfaction.
8
This study indicates that countries such as Cuba, Costa Rica or Greece achieve the same life expectancy as the
USA, Germany or the UK – with considerably less GDP growth and resource depletion.
9
Similar to what Bourdieu (1984) has described for social classes, the cycle of keeping up with the avant-garde
may also occur at country level: Here, the advanced Western countries of cluster 1 serve as the upper-class,
cluster 2 as the underclass and cluster 3 would be the middle-class.
13
One way to empirically shed light on these issues is to investigate how strong the effect of the
various single indicators are for the generation of the three clusters, and how all indicators
relate to each other. Table 3 displays the impact of the indicators for the separation of clusters.
GDP has the highest F-value and thus separates the cluster the most. Other indicators with
strong effects are life expectancy, the Ecological Footprint and life satisfaction. Yet the fact
that the effect of GDP is by far the strongest indicates the amount of the challenge any political approach will face when attempting to deprioritise GDP growth and complement/replace it
with social and ecological parameters.
Table 3: F-values of indicators from ANOVA statistics of the k-means cluster analysis
Indicator
F-value
CO2
3,758
GDP
69,998
GINI
7,179
UNEMPLOYMENT
1,913
CONSULTATION
2,599
VOTERS
1,217
SATISFACTION
17,327
HOMICIDE
7,082
FOOTPRINT
22,202
HEALTH
7,316
LIFEEXPECTANCY
48,834
GROWTH
10,905
Relationships between indicators
In a second step, we apply correspondence analysis to empirically explore the relations between the three prosperity dimensions and the economic performance of the 35 countries.
This method allows for visually depicting the latent structures and correlations of all interdependent variables within maps (Bourdieu, 1984; Blasius and Greenacre, 2006; Greenacre,
2007). To give every indicator and every country the same weight the macro data is standardized through the use of the two-step procedure of ranking and doubling (Greenacre, 2007;
Blasius and Graeff, 2009). In total, we compiled and analyzed data for twelve indicators in or
near 2010, which we collected from EUROSTAT, the World Bank, the OECD and the Global
Footprint Network. We interpret the resulting maps as follows (Blasius and Graeff, 2009):
14
• The greater the distance of a variable or country from the centroid, which depicts the
overall average of all 35 countries, the stronger is its contribution to the respective axis within
the two-dimensional map. If, for example, the indicator GDP is on the first dimension furthest
from the centroid, this dimension is mostly determined by differences in the level of economic
development between the countries;
• The correlation between two indicators is expressed by the angle of their trajectories in
the map, whereby a 90° angle reflects complete independence, that is, the absence of a correlation between variables (0° represents a perfect positive correlation and 180° a perfect negative);
• The doubling and ranking procedure results in two endpoints for each variable/indicator, a positive and a negative one (indicated as _hi and _lo), which are both depicted
in the maps and which are perfectly mirrored by the centroid, or in other words: they are
negatively correlated; the angle of their trajectory is 180°, a straight line passing the centroid.
We inserted these lines for all indicators, so that bundles of indicators emerge.
Together, the two dimensions of the map explain 51.5 per cent of variation in the data (Figure
2). The indicators with the highest loads on their respective dimensions are GDP, Ecological
Footprint, satisfaction and life expectancy on the x-axis, and homicide rates and CO2 emissions on the y-axis. Overall, the indicators take the form of two broad bundles. The first one
stretches from the upper left to lower right and the other from the upper right to lower left.
The dotted lines through these bundles represent the substantial latent dimensions whose
meaning is determined by the interdependency of the indicators in the bundles. The first of
these latent dimensions stands for the material living standard and general life satisfaction in a
broad sense. It captures GDP and unemployment as economic indicators, the GINI coefficient
for income inequality, subjective health and life satisfaction as well as the two ecological indicators CO2 emissions and Ecological Footprint.
The associations between these indicators largely confirm the results from the cluster analyses. The upper left quadrant of the map is characterised by a concentration of indicators
measuring the dimensions ‘material living standard’ and ‘satisfaction’. A relative high level of
GDP per capita is associated with relative high values for subjective health, life satisfaction
and a relative low value of the GINI coefficient. Further from GDP yet still correlated we find
comparatively high Ecological Footprints, low unemployment rates and high voter turnouts.
15
Interestingly, the fact that relatively high CO2 emissions per capita mark the most distant indicator within this bundle suggests that the link between economic development and CO2
emissions is weaker than expected in most ‘degrowth’ approaches. This link could be further
loosened through adequate policies, for example public subsidies and support of renewable
energy use. Yet an adequate reduction of the Ecological Footprints appears to be a far greater
challenge as the lower right quadrant of the eco-social field indicates. Relatively low footprints, especially, and, to a lesser degree, comparatively low CO2 emissions – our indicators
for ecological sustainability – are associated with relatively low material living standards and
relatively low values of perceived life satisfaction.
The second bundle and its latent dimension are constituted by four indicators: homicide rates,
economic growth, life expectancy and ‘consultation’ (our indicator to measure the impact of
civil society on government decisions). On the basis of previous studies and the above cluster
analyses we expected the latter indicator to be closer to ‘voter turnout’, since ‘consultation’
likewise measures the degree of citizens’ socio-political participation. At the same time, the
statistical connection of two of our four social inclusion indicators – homicide and consultation – and also life expectancy to the level of economic development is very weak. In contrast, these indicators correlate positively with low growth rates. This suggests that at least
some aspects of social inclusion and the quality of life in particular may be reached with
slower GDP growth rates and less environmental stress than is the case in countries of the first
cluster.
16
Figure 2: Correspondence analysis; map of variables 2010
λ2=0.046
(13.0%)
Low inclusion and low
quality of life
CO2_hi
HOMICIDES_hi
Environmental
stress
High material living
standard and high
satisfaction
GROWTH_hi
LIFEEXPECTANCY_lo
0.5
FOOTPRINT_hi
UNEMPLOYMENT_lo VOTERS_hi
CONSULTATION_lo
SATISFACTION_hi
GINI_lo
λ1=0.136
(38.5%)
HEALTH_lo
GDP_hi
0.5
HEALTH_hi
GINI_hi
GDP_lo
SATISFACTION_lo
CONSULTATION_hi
UNEMPLOYMENT_hi
VOTERS_lo
FOOTPRINT_lo
LIFEEXPECTANCY_hi
GROWTH_lo
HOMICIDES_lo
CO2_lo
High inclusion and high
quality of life
17
Low material living
standard and low
satisfaction
In a last step, we plotted the positions of the 35 countries onto the map (Figure 3). In this way,
the overall ‘prosperity performance’ of each country becomes identifiable. For example,
countries can be located in positions that combine relative high values for ‘inclusion’ and
‘quality of life’ with lower values for ‘material living standard’ and overall ‘satisfaction’. This
applies to the cases in the lower left quadrant, particularly to Switzerland, New Zealand, the
UK, Italy and Spain. Most economically advanced are the Nordic states, but also countries
with a liberal welfare tradition such as the USA, Australia and Canada. These all figure in the
upper left quadrant. The higher their position within this quadrant the less socially inclusive
these countries, since they move on the second dimension towards the negative spectrum,
characterised by relatively weak inclusion and low quality of life. This is exemplified by the
respective positions of the USA and Norway. The most prosperous country in respect to all
dimensions including sustainability is located at the extreme lower left of the map: Switzerland.10
Figure 3 also displays the positions of the three clusters as the mean scores of their respective
countries. As might be expected from the results of the cluster analysis, cluster 1 emerges on
the left side of the spectrum, the most economically advanced but unsustainable part of the
eco-social field. Cluster 2 is on the opposite side and surrounded by less economically developed and more ecologically sustainable countries. It is also much less associated with social
inclusion and quality of life than cluster 1. Cluster 3 takes a middle position regarding the
material standard of living and life satisfaction, while it is equally advanced in terms of social
inclusion and the quality of life as cluster 1. Hence, in the correspondence analysis, cluster 3
has caught up with cluster 1 on this dimension without simultaneously moving towards the
area of environmental stress.
10
According to our cluster analysis, Switzerland is part of the largely unsustainable first cluster. This is mainly
due to its huge GDP per capita, which is the most important indicator for separating the clusters (Table 3).
18
Figure 3: Map of countries and prosperity regimes
λ2=0.046
(13.0%)
Low inclusion and low
quality of life
LU
RU
Enivronmental
Stress
EE
US
High material living
standard and high
satisfaction
BE
CZ
0.5
NL
KR
FI
AU
IL
social-democratic welfare regime
CL
CA
DE
DK
AT
SK
cluster1
NO
MX
SI
IE
cluster3
PL
conservative welfare regime
FR
EL
UK
CH
TR
0.5
liberal welfare regime
SE
BR
cluster2
JP
HU
NZ
IT
PT
ES
High inclusion and high
quality of life
19
Low material living
standard and low
satisfaction
λ1=0.136
(38.5%)
Following Esping-Anderson (1990), we finally included the positions of his three welfare
regimes in the map. In contradiction to hopes that ‘social-democratic’ welfare regimes are
best placed to build the green dimension of the state (Dryzek in Gough et al., 2008; see Koch
and Fritz forthcoming), these countries are positioned in the lower section of the upper left
quadrant. Hence, social-democratic countries combine high levels of economic prosperity
with social equity but also with high Ecological Footprints and environmental stress. In terms
of prosperity regimes these countries are in fact closer to the ‘liberal’ welfare world than one
would expect on the basis of Gough et al. (2008). Far from displaying sufficiently low environmental footprints and CO2 emissions the conservative welfare regime family scores best in
terms of environmental performance. It is also closest located to high life expectancy and
‘consultation’ as a measurement of the impact the general public is able to make on state
regulation and government action. Switzerland might indeed serve as a good example in this
regard.
Conclusions and challenges for policy-makers
Building on the growing academic literature in favour of a de-prioritisation of GDP growth as
socio-economic policy goal and of conceptualising prosperity without growth, this paper set
out to comparatively identify the potentials of 35 advanced capitalist countries of achieving
such prosperity. It operationalised prosperity in terms of three dimensions (ecological sustainability, social inclusion and the quality of life) and empirically analysed these in relation to
economic development. First of all, we would like to clarify that no country of our sample
meets the absolute sustainability standards identified in the WWF’s Living Planet Report
(WWF 2006). Our empirical results largely confirm previous studies that question the feasibility of absolutely decoupling GDP growth from resource intensity and economic stress.
However, this applies more to the Ecological Footprint than to carbon emissions, since the
latter are less associated with GDP. Policy strategies that support the investment in and the
use of renewable energies could assist this trend towards dissociation between economic development and carbon emissions further.11
11
Current ‘market-oriented’ climate policies including the EU Emissions Trading System have opened up additional investment area for financial capital but have contributed next to nothing to climate change abatement.
Much evidence points to the conclusion that direct state action and/or climate taxes would be a more effective
policy means (Lohman, 2010; Koch, 2012: 155-66).
20
The cluster analyses led to three groups of countries with corresponding prosperity regimes.
The first cluster assembled countries with such different welfare traditions and institutional
structures as the US, Sweden and Germany. These countries are united by their relative success in economic development and social equity. Yet the fact that this cluster is also the least
ecologically sustainable again supports authors who doubt the possibility of absolutely decoupling GDP growth and resource intensity. Indeed, any transformation to global sustainability
is significantly undermined by the Western ‘way of life’, and by the fact that it continues to be
the role model for the rest of the world. Not accidentally, the second cluster of the ‘emerging
markets’ of Brazil, Russia or Mexico reflects the growth model of the industrialised countries
of the first clusters in many ways. Similar to earlier development phases of the latter countries, these countries are characterised by quickly developing markets and rapid GDP growth,
social disintegration and anomie as well as relatively low carbon emissions and Ecological
Footprints. However, to the extent that these countries continue to copy the previous development path of the Atlantic space, their ecological performance is likely to deteriorate (Koch
2012: 122-136). The third cluster brings together countries as diverse as Italy, Slovenia, South
Korea and New Zealand and comes closest to provide evidence for the feasibility of policy
strategies to simultaneously foster economic development, social cohesion and ecological
sustainability. This applies much more for objectively measurable than to subjectively perceived prosperity indicators. A final result of our correspondence analyses is that there are
significant prosperity potentials for most countries that do not lie in the further expansion of
material standards and needs but in the provision of increased possibilities of political codetermination, especially at local levels, and which might in turn also enhance subjective life
satisfaction of the citizens.
Future research should empirically and theoretically focus on the difference between objectively measured and subjectively perceived indicators of prosperity, particularly in the countries of our third cluster. From the perspective of institutional learning, a comparative in-depth
analysis of these countries’ institutional structures – for example in relation to degrees and
kinds of corporatism and environmental regulation (Liefferink et al. 2009) – highlighting
commonalities and differences appears likewise promising A significant issue for both research and policy-making that arises from the present paper, which should be explored further, is how subjectively perceived quality of life (well-being) and democratic participation
can be achieved and increased under conditions of economically stable and increasingly eco21
logically sustainable economies. Empirically, future studies should include more countries,
particularly from non-OECD countries, as well as alternative indicators that more precisely
focus on the contrast between objective and subjective indicators of welfare, well-being and
the quality of life.
References
Abdallah S, Michaelson J, Shah S, Stoll L, Marks N (2012) The Happy Planet Index: 2012 Report. A global
index of sustainable well-being (nef: London)
Barry, J. (2012) ‘Towards a political economy of sustainability’, in M. Pelling, D. Manuel-Navarrete and M.
Redclifft (eds) Climate Change and the Crisis of Capitalism, London: Routledge.
Blasius, J. and Graeff, P. (2009), ‘Economic freedom, wealth and corruption. Analyzing their empirical connection by means of correspondence analysis’, in P. Graeff and G. Mehlkop (eds.), Capitalism, democracy and the
prevention of war and poverty, London: Routledge.
Blasius, J. and Greenacre, M. (2006), ‘Multiple correspondence analysis and related methods in practice’, in M.
Greenacre and J. Blasius (eds.), Multiple correspondence analysis and related methods. Boca Raton, FL: Chapman and Hall.
Borucke, M., Moore, D., Cranston, G., Gracey, K., Iha, K., Larson, J., Lazarus, E., Morales, J.C., Wackernagel,
M. and Galli, A. (2013), ‘Accounting for demand and supply of the biosphere’s regenerative capacity: The National Footprint Accounts’ underlying methodology and framework’, Ecological Indicators, 24, 518-533.
Bourdieu, P. (1984), ‘Distinction: A Social Critique of the Judgement of Taste’, Harvard: Harvard University
Press.
Daly, H. (1977) Steady State Economics, San Francisco, CA: W.H. Freeman.
Daly, H. and J. Farley (2009) Ecological Economics. Principles and Applications. Washington, DC: Island Press.
De Gleria, S. (1999) ‘Nicholas Georgescu-Roegen’s Approach to Economic Value: A Theory Based on Nature
with Man as its Core’ in K. Mayumi and J.M. Gowdy (eds) Bioeconomics and Sustainability. Essays in Honor of
Georgescu-Roegen, Cheltenham: Edward Elgar.
Esping-Andersen, G. (1990) The Three Worlds of Welfare Capitalism, Cambridge: Polity.
Fritz, M. (2013) ‘Non-Standard Employment and Anomie in the EU, in Koch, M. and Fritz, M. (eds) NonStandard Employment in Europe: Paradigms, Prevalence and Policy Responses, Basingstoke: Palgrave Macmillan.
Gough, I. (2011) Climate Change and Public Policy Futures, London: British Academy.
Gough, I., Dryzek, J., Gerhards, J., Lengfield, H., Markandya, A. and Ortiz, R. (2008) ‘JESP Symposium: Climate Change and Social Policy’, Journal of European Social Policy 18 (4): 325-344.
Greenacre, M. (2007) Correspondence analysis in practice, 2nd edition, Boca Raton, FL: Chapman and Hall.
Hick, R. (2012) ‘The Capability Approach: Insights for a New Poverty Focus’, Journal of Social Policy 41 (2):
291–308.
Hirsch, F. 1976. The Social Limits to Growth. Cambridge, MA: Harvard University Press.
22
Intergovernmental Panel on Climate Change (IPCC) (2013) Climate Change 2013: The Physical Science Basis.
Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate
Change. Summary for Policymakers, available online at
http://www.climatechange2013.org/images/uploads/WGI_AR5_SPM_brochure.pdf.
Jackson, T. (2009) Prosperity without Growth? Economics for a Future Planet, London: Earthscan.
Kallis, G. (2011) ‘In Defence of Degrowth’, Ecological Economics No. 70, 873-80.
Kasser, T. (2009) ‘Psychological Need Satisfaction, Personal Wellbeing, and Ecological Sustainability’, Ecopsychology 1 (4): 175–180.
Kasser, T. (2011) ‘Capitalism and Autonomy’ in V.I. Chirkov et al. (eds) Human Autonomy in Cross-Cultural
Context, New York: Springer.
Keynes, J. M. (1963) ‘Economic Possibilities for Our Grandchildren’ in J .M. Keynes (ed) Essays in Persuasion,
New York: W.W. Norton.
Koch, M. (2012) Capitalism and Climate Change. Theoretical Analysis, Historical Development and Policy
Responses, Basingstoke: Palgrave Macmillan.
Koch, M. (2013) ‘Welfare after Growth: Theoretical Discussion and Policy Implications’, International Journal
of Social Quality 3 (1): 4-20.
Koch, M. and Fritz, M. (2013) ‘Conclusion: Non-Standard Employment: Concept, Empirical Results and Policy
Implications’, in Koch, M. and Fritz, M. (eds) Non-Standard Employment in Europe: Paradigms, Prevalence
and Policy Responses, Basingstoke: Palgrave Macmillan.
Koch, M. Fritz, M. (forthcoming) ‘Building the Eco-social State: Do Welfare Regimes Matter? Forthcoming in
Journal of Social Policy.
Lafferty, W. and Hovden, E. (2003) ‘Environmental policy integration: Towards an analytical framework’, Environmental Politics 12 (3) 1-22.
Layard, R. 2011. Happiness: Lessons from a New Science. London: Penguin Books.
Liefferink, D., Arts, B., Kamstra, J. and Ooijevaar, J. (2009) ‘Leaders and laggards in environmental policy: A
quantitative analysis of domestic policy inputs’, Journal of European Public Policies 16 (5), 677-700.
Lohmann, L. (2012) ‘Uncertainty markets and carbon markets: Variations on Polanyian Themes’, New Political
Economy 15 (2): 225-54.
Martinez-Alier, J., U. Pascual, F.D. Vivien, and E. Zaccai (2010) ‘Sustainable De-growth: Mapping the Context, Criticism and Future Prospects of an Emergent Paradigm’, Ecological Economics 69: 1741–1747.
Marx, K. (1961) Capital: A Critique of Political Economy. Vol. 1. Moscow: Foreign Languages Publishing
House.
Mill, J. S. (1848) Principles of Political Economy. Book IV. London: Longmans, Green and Co.
Nussbaum, M. C. (2006) Frontiers of Justice. Disability, Nationality, Species Membership. Cambridge: The
Belknap Press.
Nussbaum. M. and Sen, A. (1993) The Quality of Life, Oxford: Oxford University Press.
Porter, M.E, Stern, S, Artavia Loria, R (2013) Social Progress Index 2013, The Social Progress Imperative.
Sekulova, F, Kallis, G., Rodriguez-Labajos, B. and Schneider, F. (2013) ‘Degrowth: From Theory to Practice’,
Journal of Cleaner Production 38: 1-6.
23
Sen, A. (1993) ‘Capability and Wellbeing’ in M.C. Nussbaum and A. Sen (eds) The Quality of Life, Oxford:
Oxford University Press.
Soper, K., Ryle, M.H. and Thomas, L. (2009) The Politics and Pleasures of Consuming Differently, Basingstoke:
Palgrave Macmillan.
Stiglitz, J., Sen, A. and Fitoussi, J. (2009) ‘Report by the Commission on the Measurement of Economic Performance and Social Progress’, available online at http://www.stiglitz-senfitoussi.fr/documents/rapport_anglais.pdf.
Sustainable Development Commission (2007) ‘Living Well – Within Limits’, SDS Discussion Document on
Wellbeing Indicators for Sustainable Development.
The Royal Society (2012) ‘People and the Planet’, The Royal Society Science Policy Centre, Report 01/12, London.
Veblen, T. (1970) The Theory of the Leisure Class. London: Unwin Books.
Victor, P. A. (2008) Managing without Growth: Slower by Design, not Disaster, Cheltenham: Edward Elgar.
Wilkinson, R. and Pickett, K. (2010) The Spirit Level. Why Equality is Better for Everyone. London: Penguin.
WWF (2006) Living Planet Report 2006, London and Oakland: Gland.
WWF (2012) Living Planet Report 2012, WWF International, Gland, Switzerland.
24