A Metaindex of Development Morosini 1 Nov 2008

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A Metaindex of Development (MoD)
Marco Morosini*
To be submitted to Social Indicators Research
http://www.springer.com/chl/home?SGWID=2-102-70-35672185-
detailsPage=journal|editorialBoard&changeHeader=true&SHORTCUT=www.springer.com/journal/11205/edboard
Abstract
A Metaindex of Development (MoD) for the 30 OECD countries was obtained through the country
average rank in ten established international indices covering themes associated with development in
industrialized countries: people and ecosystem wellbeing, human development, economic
competitiveness, economic freedom, economic equality, information technology, environmental
sustainability, gender gap, press freedom, corruption perception. The Metaindex answers the question:
when development or relevant elements of it are measured, which OECD countries are more often in
the top, in the middle or in the bottom ranks?
Iceland, Finland, Sweden, Denmark, Norway, Switzerland, Canada, Netherlands, Australia and Ireland
are the top ten countries in the Metaindex ranking in 2006. These countries have a small population (10
millions in average) and seven of them are thinly populated. Compared with the next twenty countries,
they have in average the lowest worldwide levels of corruption and the highest levels of press freedom,
taxation, environmental stewardship and diffusion of information technology. Eight of the top ten
countries rank in the top ten positions in the OECD ranking of satisfaction with life. G8 countries are in
the middle of the Metaindex ranking, with Canada best placed (8) and Italy worst (25). The two best
correlating rankings with the Metaindex ranking are those of the Corruption Perception Index (0.931),
which appears to be the best proxy for development in the OECD countries, and of satisfaction with life
(0.866).
Key words: development, metaindex, composite indicators, indices, OECD
*Swiss Federal Institute of Technology (ETH),
CHN E24, Universitaet-Str. 16,
CH-8092 Zurich, Switzerland.
E-mail: marco.morosini@env.ethz.ch

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In all but the most exceptional cases, national prosperity is not about physical
objects or natural resources. Rather, it is about institutions - the framework
within which human beings think, interact, and carry on business.
W. Bernstein, The Birth of Plenty
1 Introduction
When in the international community relevant elements of development are measured and reported,
which industrialized countries are more often in the top, in the middle or in the bottom ranks? Which
societal features are more often associated with top development performance and could offer
inspiration for development policies? To answer these questions, this study proposes a Metaindex of
Development (MoD), which ranks the 30 OECD countries according to the average of their rank in ten
established international indices that measure development or relevant aspects of it.
The term development is most often used in association with the so-called developing countries and
with their need for progress in nutrition, health care, education, infrastructure, economy and institutions.
The most urgent progress needed in these countries is resumed by the United Nations in the Millennium
Development Goalsi
(UN 2008). Yet this study deals only with the OECD countries for three reasons.
First: driven by human ingenuity, development is a never-ending process and concerns all countries.
Many reckon impossible to extend the present level of resource use per person to the entire human
population; prosperous countries have hence the major responsibility for profound transformations of
their own societies and for progressing towards forms of living that could be sustained in the long term
by the global population; to do this, a great deal of development towards sustainability in needed in the
so-called ”developed countries”; they have also much knowledge and personnel to do this. Second:
many less industrialized countries are likely to adopt some technological, economic and societal
arrangements of the leading OECD countries. To that extent, much of what is done by several OECD
countries influences the patterns of development of the rest of humanity. Third: the availability and the
reliability of the data on development are higher for the OECD countries than for other nations.
None of the variables proposed for ranking countries on a development scale is satisfactory. The most
used proxy measure of development is the gross domestic product per capita (GDP pc); the
conventional distinction between developed and developing countries is still based on it. Its creator
Simon Kuznets himself warned against its misuse as measure of development or welfareii
(Kuznets
1962); criticism to measuring income in order to assess welfare is as old as the fortune of GDP (Boulding
1949). In spite of its enduring dominance as beacon of progress, many consider GDP inadequate or
misleading as a measure of welfare because it cannot account for important social benefits and social
costs caused by monetized and by not monetized human activitiesiii
.
As better measure of economic or societal progress some other indices were proposed: Measure of
Economic Welfare (MEW) (Nordhaus and Tobin 1973), Index of Sustainable Economic Welfare (ISEW)
(Cobb and Daly 1989), Human Development Index (HDI) (UNDP 1990), Wellbeing Index (WI) (Prescott-
Allen 2001), Genuine Progress Indicator (GPI) (Cobb and Venetoulis 2004), Happy Planet Index (HPI)
(Marks et al., 2006). Among these the Human Development Index (HDI) obtained a relative high
visibility; its scope is more comprehensive than that of the GDP pc, yet incomplete: only three domains
are considered: income, longevity and education; the focus of the HDI is on few basic conditions that
foster the free agency of the individuals, but the structural elements of a country are not covered; the
only endpoint is longevity, while for the other two domains (income and education) their instrumental
function is dominant; environmental sustainability is not considered. The most comprehensive attempt
to measure sustainable development and to rank all countries is the Wellbeing Index (Prescott-Allen
2001) but it was not adopted by leading international institutions and was criticized for different reasonsiv
.
The search for comprehensive measurements of development gained momentum in the last years,
supported by international organizations (OECD 2008)v
, European institutions (European Parliament
and European Commission, 2007) and governments, e.g. of France (Fox 2008) and Buthan (Revkin
2005).
In spite of its empirical approach the present study refers to a theoretical definition of development, that
of Amartya Sen: “Development consists of the removal of various types of unfreedoms that leave people
with little choice and little opportunity of exercising their reasoned agency.“ (Sen, 1999, p. xii). Sen’s
conception of “development as freedom“ encompasses several elements that go beyond income and
also beyond the scope of the Human Development Index itself, which he helped to create. Most of the
societal features considered important for development are both means and ends; they have an
instrumental and a constitutive character (Sen 1999, chapter 2). More specifically, according to a means-
ends pyramid (Daly 1973, Meadows 1998) the most frequently measured societal features are
intermediate means (e.g. man-made capital) or intermediate ends (e.g. education, health, longevity),
whereas the ultimate means are the natural resources and the ultimate end is the satisfaction with life.

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In fact many of the indices collected by the Metaindex of Development describe realities that are both
signs of achieved development and means for fostering progress at an upper level of the means-ends
pyramid. Sen (1999, chapter 2) specifies five types of instrumental freedoms: political freedom,
economic facilities, social opportunities, transparency guarantees and protective security. A future
development index should try to cover at least these domains. Each of the indices collected by the
Metaindex can be attributed to one or more of these types of instrumental freedomsvi
. However we do
not claim completeness or balance because the approach of the Metaindex is bottom-up and builds only
on those indices that have been established in the last decades.
Ranking nations according to an index has become common practice (Freudenberg 2003, The
Economist 2005, 2008, Nardo et al. 2008). In the last two decades a number of international indices that
rank nations on different aspects of development have often become reference for information media,
citizens and decision makers. The extent of the resources invested in conceiving and establishing an
international index and the public attention gained by it are evidence of its publicly perceived relevance,
although no guarantee for its quality. In the scientific community some of the established indices have
been considered with skepticism and were criticized (Lall 2001, Gregoir and Manuel 2002,
Freundenberg 2003, Saltelli 2007, Nardo 2008), e.g. for: weak theoretical foundation; choice, weighting
and aggregation of the variables; reliance on surveys more than on hard data; incomplete data basis
and recourse to imputation; the same benchmarking for high industrialized and least industrialized
countries. The relevance for development of the issues described by some indices, e.g. “national
competitiveness”, was questioned (Krugman 1994, Lall 2001, Turner 2001,). Altogether the most
established international indices do not compose a balanced picture of all relevant aspects of
development and even less of sustainable development. For example, worldviews of the business
community are more represented than those of the environmental community; those of rich countries
more than those of less industrialized countries, monetized economic performance more than ecological
sustainability. Freedom of press, economic competitiveness, economic freedom and diffusion of
information technology are covered by established indices, but the same is not true for health and
healthcare, efficacy of public institutions, citizens’ empowerment, diffusion of culture. The ensemble of
the most established indices is less comprehensive than some systems of indicators of sustainable
development, e.g. that of the UN Commission on Sustainable Development or that of “The Wellbeing of
Nations” (Prescott-Allen 2001). Yet even severe critics of composite indicators point out that “some
pragmatism in approaching the use of composites is desirable. Empirical and policy analyses often
benefit from the use of measures and indicators that are less the ideal and to rule out the use of
composites altogether would be going too far.” (Freudenberg 2003). The Metaindex of Development
was built on the judgment that, albeit incomplete and debatable, the established indices are worth to be
highlighted because they reflect the state of the international discourse on measuring relevant aspects
of development, including imbalances and biases of this discourse. This approach is parallel but not
alternative to the construction of a comprehensive index of sustainable development through a theory-
driven choice of the variables.
This paper proceeds as follows: the methodology of the Metaindex of Development is explained, the ten
selected indices are presented, the resulting values and rankings of the Metaindex as well as the
correlation between the rankings of all indices are presented and discussed; finally, conclusions are
drawn.
2 Methodology
2.1 Collection of the indices
Although this study is not devoid of theoretical basis, the ten indices of the Metaindex are not the result
of a top-down selection covering all domains described by a development theory. Instead the Metaindex
results from a bottom-up compilation of ten established indices. The term Metaindex intends to reflect
this approach: the purpose is not to build an index based on the variables and weights preferred by the
author, but rather to mirror the state of the discourse on measuring development in the OECD countries.
The criteria used for the collection of the ten MoD indices are:
- Relatedness of the issue covered by an index to and its significance for development in industrialized
countries
- Aggregation of the variables covering an issue into an index and ranking of countries
- Coverage of the 30 OECD countries
- Methodological consistency
- Authoritativeness of the issuing institution
- Reception of the index by media, institutions, private actors and the scientific community.
The indices responding to these criteria are very few. In most cases only one exists for a given issue.
Consequently the compilation of the ten indices was relatively straightforward. Of course in the selection
of issues and indices the room for arbitrariness and for implicit value judgments is not zeroed.

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Worldviews, value judgments and assumptions lay behind each of the ten indices. Furthermore, trade-
offs between the pursuing of the optimal conditions targeted by each index are inescapable, e.g.:
between economic freedom and economic equality, or between economic performance and
environmental conservation. In this respect the author exerted himself in making allowance for balance
among different worldviews and indices.
Most of the established indices were developed in the industrialized countries and reflect issues that are
perceived as more relevant by them. This is a further reason for limiting the scope of this study to the
OECD countries. According to an ends-means hierarchy, indices that focus on intermediate means were
deliberately chosen. One purpose of this study is to draw attention upon those countries that excel in
some of the societal features that favour development.
The following indices or variables were not included in the Metaindex for these reasons:
- The Gross Domestic Product per caput (GDP pc) was not included as single variable because it is
already included in the Wellbeing Index, in the Human Development Index and in the Global
Competitiveness Index, and because its role as indicator for development or for welfare, especially in
the industrialized countries, is questioned (Matthews 2006, OECD 2007 and 2008, European
Parliament and European Commission 2007).
- An index of globalization was not included, since the desirable and the undesirable effects of the
present globalization process are controversial. The rankings and underlying index structure of the two
existing indices for globalization, the Globalization Index (A.T. Kearney/Foreing Policy Magazine 2006)
and the Index of Globalization (KOF 2007), are quite different, the latter being more completevii
.
- The index of satisfaction with life (SWL)(Mark et al., 2006) was not included, because the focus of the
Metaindex is on the intermediate means leading to development, not on the ultimate ends.
- The Ecological Footprint (EF) was not included because it is an index of intensity of resource use, not
of development. Major reasons for having a low EF are low levels of industrialization, of use of fossil
fuels, of income and of development. E.g. in 2003, the best OECD performers in the EF ranking were
Turkey, Mexico, Slovak Republic, Poland, and the world best Afghanistan, Somalia, Bangladesh,
Malawi. Also geographic factors, e.g. climate or being an island can strongly influence the EF. Finally,
only if a group of countries have very similar industrialization level, consumption and trade patterns as
well as geographical and climatic conditions, then a lower ecological footprint of one country can
signalize a more sustainable economy and lifestyle.
Since income (GDP pc), globalization and satisfaction with life are important issues in the discourse on
development, the rankings of the three indices describing these issues were compared with the rankings
of the ten MoD indices and of the Metaindex (Table 3 and 7).
2.2 The ten indices (MoD Indices)
Ten indices where collected for the Metaindex of Development (the “MoD indices”): eight of them cover
either one dimension of development or single aspects of the social, economic and institutional
dimension; the Human Development Index covers the socio-economic dimension; the Wellbeing Index
covers the socio-economic and the environmental dimension. The ten MoD indices are described in the
following and in Table 1; all indicators aggregated in each of the ten indices and their aggregation
methods are listed in the Appendix. For each index the last available data were taken in January 2007viii
.
1) Wellbeing (WBeing) - Wellbeing Index (WI)
The Wellbeing of Nations, 2001 (Prescott-Allen 2001)
Robert Prescott-Allen, in collaboration with: International Development Research Centre (IDRC), IUCN
- The World Conservation Union, the International Institute for Environment and Development (IIED),
Map Maker, the Food and Agriculture Organization of the United Nations (FAO), and the World
Conservation Monitoring Centre (WCMC) of the United Nations Environment Programme (UNEP).
The Wellbeing Index ranks countries according to 87 variables, aggregated in two indices, the Human
Wellbeing Index (HWI) and the Ecosystem Wellbeing Index (EWI). The Human Wellbeing Index (HWI)
is divided in five elements (Health and Population, Wealth, Knowledge and Culture, Community, Equity)
with 31 indicators; the Ecosystem Wellbeing Index (EWI) is divided in five elements (Land, Water, Air,
Species and Populations, Resource use) with 56 indicators. First report in 2001.
2) Human development (HumDev) - Human Development Index (HDI)
Human Development Report 2006 (UNDP 2006)
United Nations Development Programme, UNDP, New York, USA
The Human Development Index is the average of three dimension indices, which include six variables:
the life expectancy index (life expectancy at birth), the education index (adult literacy and combined
primary, secondary and tertiary gross enrollment ratio) and the GDP index (gross domestic product pro
capita, in $PPP). Published yearly since 1990.

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3) Economic competitiveness (EcComp) - Global Competitiveness Index (GCI)
Global Competitiveness Report 2006-2007 (Lopez-Claros et al. 2006)
World Economic Forum, Cologny/Geneva, Switzerland
The Global Competitiveness Index, based on an adjustment of the Growth Competitiveness Index
developed by Jeffrey Sachs and John McArthur (WEF 2001), ranks countries according to a score given
by the aggregation of 89 variables, distributed (as in brackets) in nine pillars: Institutions (15),
infrastructure (6), macroeconomy (6), health and primary education (9), higher education and training
(7), market efficiency (23), technological readiness (7), business sophistication (8), innovation (8).
Published yearly since 2001.
4) Economic freedom (EcFree) - Index of Economic Freedom (IEF)
2006 Index of Economic Freedom (Miles et al 2006)
Heritage Foundation, Washington, USA; Wall Street Journal, New York, USA
The Index of Economic Freedom ranks countries according to the aggregation of 50 independent
variables. Countries receive a 1-5 rating - with 1 being the best - on 10 broad measures of economic
freedom: trade policy, fiscal burden of government, government intervention in the economy, monetary
policy, capital flows and foreign investment, banking and finance, wages and prices, property rights,
regulation and informal (or black) market activity. These scores are averaged to create an overall score.
The top finishers are classified as free economies, followed by mostly free, mostly unfree and repressed
economies. Published yearly since 1995.
5) Economic equality (EcEqua) - Gini Index (GI)
Reported in: OECD Factbook 2006 (OECD 2006)
OECD - Organisation for Economic Co-operation and Development, Paris
Issued with different periodicity by the national statistics offices, the Gini coefficient measures the
distribution of the income in one country with a value between zero and one, one being totally even
distribution and zero the entire national income going to a single citizen. The Gini Index is the Gini
coefficient expressed as a percentage, and is equal to the Gini coefficient multiplied by 100. Gini Index
values for most nations are reported by the yearly Human Development Reports, but methodologies
used and reference years can vary from nation to nation, so that a comparison among nations could be
imperfect or misleading; for this reason this study uses data from the OECD Factbook 2006, first
published in 2006.
6) Information Technology (InfTec); Networked Readiness Index (NRI)
Global Information Technology Report 2005-2006 (Dutta et al 2006)
World Economic Forum, Cologny/Geneva, Switzerland, in collaboration with INSEAD, Fointainbleau,
France
The Networked Readiness Index measures the degree of preparation of a nation or community to
participate in and benefit from information and communication technology (ICT) developments. It is
composed of 66 variables, divided into three component indexes which assess: the environment for
ICT offered by a given country or community; the readiness of the community’s key stakeholders -
individuals, business and governments; the usage of ICT among these stakeholders. Published yearly
since 2001.
7) Environmental sustainability (EnvSus) - Environmental Sustainability Index (ESI)
2005 Environmental Sustainability Index - Benchmarking National Environmental Stewardship (Esty et
al 2005)
Yale Center for Environmental Law and Policy, Yale University, New Haven, CT, USA; Center for
International Earth Science Information Network, Columbia University, Palisades, NY, USA, in
collaboration with: World Economic Forum, Cologny/Geneva, Switzerland and Joint Research Center
of the European Commission, Ispra, Italy
The 2005 Environment Sustainability Index ranks countries according to their ability to protect the
environment over the next several decades. It does so by integrating 76 data sets into 21 indicators of
environmental sustainability. The ESI uses equal weights at both the indicator and the variable level.
The indicators permit comparison across a range of issues that fall into the following five broad
categories:
• Environmental Systems
• Reducing Environmental Stresses
• Reducing Human Vulnerability to Environmental Stresses
• Societal and Institutional Capacity to Respond to Environmental Challenges
• Global Stewardship
Data for some variables are for years previous to 1990; the MRYA criterium (Most Recent Year
Available) was applied. Published in 2000, 2001, 2002 and 2005.

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8) Gender gap (Gender) - GGG, Global Gender Gap (GGG)
The Global Gender Gap Report 2006 (Hausmann et al. 2006)
World Economic Forum, Cologny/Geneva, Switzerland
The Global Gender Gap measures the size of the gender gap between men and women in four critical
areas: 1) economic participation and opportunity – outcomes on salaries, participation levels and access
to high-skilled employment, 2) educational attainment – outcomes on access to basic and higher level
education, 3) political empowerment – outcomes on representation in decision-making structures, 4)
health and survival – outcomes on life expectancy and sex ratio. The index mainly uses publicly available
"hard data" indicators drawn from international organizations and some qualitative information from the
Forum’s own Executive Opinion Survey The index is composed of 14 indicators. Published in 2005 and
2006.
9) Press freedom (PressF) - Global Press Freedom Ranking (GPFR)
Freedom of the Press 2006 (Freedom House 2006)
Freedom House, Washington D.C., USA
The Global Press Freedom Ranking orders countries on the basis of a set of 23 methodology questions
divided into three subcategories: legal environment, political environment and economic environment.
By assigning numerical points a comparative analysis can be made of the countries surveyed and trends
over time examined. The degree to which each country permits the free flow of news and information
determines the classification of its media as “free,“ “partly free,“ or “not free.“ Countries scoring 0 to 30
are regarded as having “free“ media; 31 to 60, “partly free“ media; and 61 to 100, “not free“ media.
Published yearly since 1980.
10) Corruption perception (Corrup) - Corruption Perception Index (CPI)
Global Corruption Report 2006 (Kotalik and Rodriguez 2006)
Transparency International, Berlin, Germany
The Corruption Perceptions Index ranks countries in terms of the degree to which corruption is perceived
to exist among public officials and politicians. It is a composite index, a poll of polls, drawing on
corruption-related data from expert and business surveys carried out by a variety of independent and
reputable institutions. The CPI 2006 draws on 12 different polls and surveys from 9 independent
institutions. The CPI focuses on corruption in the public sector and defines corruption as the abuse of
public office for private gain. The surveys used in compiling the CPI ask questions that relate to the
misuse of public power for private benefit, for example bribery of public officials, kickbacks in public
procurement, embezzlement of public funds or questions that probe the strength of anti-corruption
policies, thereby encompassing both administrative and political corruption. Published yearly since
1995.
The Corruption Perception Index and the Global Gender Gap, describe undesirable phenomena; a top
position in their rankings stands for a low level of corruption or of gender gap.
2.3 Ranking of the countries and correlation between the indices
The Metaindex of Development (MoD) is not an aggregation of the collected ten indices, but instead a
measure of the frequency with which each country is ranked high or low in the rankings of ten
established indices that cover different and not comparable domains of development. The value of the
Metaindex of a country is the average of its OECD ranks in the rankings of the ten MoD indices. The
Metaindex ranking orders the OECD countries with growing Metaindex value (Table 2). A sensitivity
analysis show little change when nine instead of ten indices were usedix
. In the original reports and
rankings, all indices consider more nations than the 30 OECD countries, thus each original ranking was
adjusted to an OECD ranking between 1 and 30.
The broadness of the themes covered by each MoD index is different, going from the comprehensive
scope of the Wellbeing Index (human and ecosystem wellbeing) until the narrow focus of the Networked
Readiness Index. Different is also the importance for development of the societal aspects described by
each index. The ten MoD indices include 421 variables (all listed in the Appendix); few of them are
present in two or three indices, e.g. GDP pc, economic equality, gender gap, corruption, press freedom.
Some indices give different weights to different variables or subindices, others give the same weight to
all variables. Would it be a plain aggregation, the final MoD ranking could be seen as being based on
implicit ex post calculable weights of each of the 421 variables. Yet a deliberate weighting of the indices
and a claim of completeness are not the intent and the rationale of the Metaindex and would be in any
case controversial. Finally the correlations between the rankings of the Metaindex, of the ten MoD
indices and of income, satisfaction with life and globalization are presented.

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3 Results and discussion
3.1 Ranking of the Metaindex of Development (MoD)
The Metaindex value of each OECD country and its rank in the Metaindex and in the ten MoD indices
are reported in table 2. Tables 3 and 4 report respectively rankings and values of six relevant variables
not included in the Metaindex: population, population density, income (GDP per caput), total tax
revenue, satisfaction with life and globalization. The reasons for choosing these variables are explained
further on. Table 5 reports a partition of the 30 OECD countries in three groups of ten, according to their
Metaindex rank; for each group the average values and ranks of the six considered variables are
presented.
A causal analysis of the correlation between the Metaindex rank of a country and some of its relevant
socio-economic features go beyond the scope of this article and would be in any case speculative.
Nevertheless we explored the association between the ranking of the Metaindex and those of some
societal parameters that we consider relevant, albeit not exhaustively, for development. We present first
a group analysis, then a cograduation analysis.
3.2 Group analysis
While there is no natural cut point in the ranking, a partition of the 30 OECD countries in three groupsx
with respectively high, medium and low Metaindex rank helps to analyze peculiarities that are more
evident within a group than within the ensemble of 30 countries and that would be less evident in the
overall cograduation analysis.xi
The data of the group analysis are presented in table 5 and commented
in the following.
3.2.1 Population size and density – The question if a certain range of population size and density can
favour development was already raised (Kose and Prasad 2002; Alesina and Spolaore 2003); we
explored how the values of these two parameters are distributed along the Metaindex ranking.
3.2.1.a Population size – Each of the top ten countries has a lower population size than in OECD
average (38.8 millions) and their average population is ¼ (10.4 millions) of the OECD average; seven
of them have less than 10 millions inhabitants. The top five countries have an even smaller average
population (4.9 million), i.e. 1/8 of the OECD average. The first country with a more than average
population (Germany, 82.6 millions) ranks 12.5. Group B and C include each five countries with more
than average population size.
3.2.1.b Population density – Most low populated OECD countries are concentrated in the top ranks.
The eight countries with less than ¼ (33 p/km2
) of the OECD average density (133 p/km2
) are all in the
top half of the Metaindex ranking. Group A shows a much lower average rank (10.4) for low population
density than group B and C (19 and 17.1). The average population density in group A (81 p/km2
) is lower
than in OECD average (133 p/km2
) and than in group B (171 p/km2
) and C (146 p/km2
). The top five
countries have an even lower average density (35 p/km2
).
A relatively small population size and a low population density characterize most of the top Metaindex
performers. Without pretence of causal explanation we advance the hypothesis that a small population
can favour development through a facilitated knowledge of decisive people and of opportunities and
through more community consciousness and citizen engagement. A small population size can favour
also more transparency, control and accountability. Some of these peculiarities of countries with a small
population could be one reason for the significantly better performance of the islands states, (most of
them with small populations) in the ranking of the Happy Planet Index (Marks et al. 2006).
From a low population density is mostly to expect a lower pressure on the local environment and a better
performance in the two MoD indices that consider environmental performance (Wellbeing Index and
Environmental Sustainability Index). Furthermore, low population density can in some cases lower the
potential for conflictxii
.
3.2.2 Income – GDP per caput is the most frequently used proxy for development, thus we compared
the Metaindex ranking with the GDP pc ranking. Although in a global context GDP pc and development
are mostly correlated, in all Human Development Reports a number of countries show much discrepancy
between their ranks for GDP pc and for human development. The same is true for the Metaindex
ranking, where 1/3 of the OECD countries show a difference of 5 positions or more with the GDP pc
ranking (Table 6). More developed than rich are Finland and Sweden (12 positions), New Zealand (9)
and Germany (5), whereas more rich than developed are Luxembourg (-15), the USA (-12), Ireland and
Belgium (-7), Italy (-6) and Greece (-5). Group A shows a higher GDP pc than group B in the rank
average (respectively 8.7 and 12.9) and a slightly lower average value (respectively 32 816 and 33 373
PPP$), but no significant association between income values and the MoD rank appears within the top
twenty countries because GDP pc values are quite dispersedxiii
. Group C countries show instead a
general association between low income and low development, having an average GDP pc rank of 24.9

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and an average GDP pc of 17 731 PPP$, well below the OECD average (27 973 PPP$). Finland and
Sweden prove that top income is not necessary for top development, whereas Italy and Greece prove
that a relatively high GDP pc is no guarantee for a more than average development.
3.2.3 Taxation (Total tax revenue - TTR) - Through evolutions, revolutions and wars the controversy
on the role of the state in the economy determined much of the history of the last century and yet
dominates the public debate. In the last decades the investigation of the relationship between the state
activity in the economy and the progress of societies flourished (Tanzi and Schuknecht 2000, Lindert
2004, Nijkamp and Poot 2004, Tanzi 2004). Rarely such an extensive effort came to such controversial
results, showing the limits of economics as evidence based science when the entanglement between
methodology and ideology is irresolvablexiv
. No satisfying measure for the role of the state in the
economy existsxv
(Peacock and Scott 2000). Although it is an incomplete measure of the economic
activity of the state, we considered the total tax revenue as percent of GDP, because it is the most used
and debated parameter. Both the average position of the groups A, B and C in the ranking for taxation
(12.8, 14.6, 19.1) and their average level of taxation (39.0, 36.7 and 33.2 per cent of GDP) show that
high development is more frequently associated with high taxationxvi
.
Six high-tax and four low-tax countries compose group A: Iceland, Finland, Sweden, Denmark, Norway
and Netherlands have an average taxation of 44.3 per cent of GDP (8 per cent of GDP more than the
OECD average of 36.3 per cent) and consequently a top average rank in taxation (5.5). Switzerlandxvii
,
Canada, Australia and Ireland have instead an average taxation of 31.2 per cent of GDP (5.1 per cent
of GDP less than the OECD average) and a bottom average rank in taxation (23.8). Taxation ranks and
levels of group B (rank: 14.6; level: 36.7 per cent of GDP) and C (rank: 19.1; level: 33.2 per cent of
GDP) show an inverse association between the rankings of the Metaindex and of taxation. These results
indicate that neither high nor low taxation are incompatible with high development levels. The five top
Metaindex performers have in average the higher taxes in the OECD, ranking in average 4.4
(respectively 10, 4, 1, 2, and 5). High taxation is neither incompatible with high or very high economic
competitiveness: in the Global Competitiveness Index the six high-tax countries in the group A rank in
average 6.3 (respectively 11, 2, 3, 4, 10 and 8), whereas the four low-tax countries rank in average 11.2
(respectively 1, 12, 15, 17). Positive and negative champions in transforming taxes in development are
Switzerland (taxation rank minus Metaindex rank = 20) and Italy (taxation rank minus Metaindex rank =
- 17).
3.2.4 Satisfaction with life – The possible connection between satisfaction with life and the socio-
economic conditions in a country is an emerging theme in social research. Thus we compared the
Metaindex ranking with the ranking for satisfaction with life (Marks et al. 2006). The average ranks and
values of satisfaction with life of group A, B and C (6.7, 15.0, 24.2 and respectively 7.7, 7.1, 6.2) show
a strong association between the rankings of satisfaction with life and of the Metaindex; the same is true
also for the average values of satisfaction. Also splitting each group in two subgroups of five countries
(e.g. with MoD rank 1-5 and 6-10), the average satisfaction rank of the first subgroup is lower than that
of the second subgroup, respectively 5.4 and 8.3 in group A, 11.7 and 18.3 in group B, 23.3 and 25.1 in
group C. The association between the ranking of the Metaindex and that of satisfaction is very high
along the whole ranking, as shown also in the cograduation analysis.
3.2.5 Globalization – Globalization and the several changes associated with it are prominent themes
in the public debate. Several authors consider a high level of globalization favorable or necessary for
the development of a country. Others warn on some negative aspects of the present globalization
process. Therefore we compared the Metaindex rank of the three groups of countries A, B and C with
their average globalization rank. In the top twenty countries no significative association appears between
the rankings of the MoD and of globalization, whereas countries of group C show in average a much
lower globalization level, with an average globalization rank of 21.2. The moderate average globalization
rank (14) of the top five countries and especially the very low globalization rank of the top Metaindex
performers Iceland (26) and Norway (21) indicate that moderate or low globalization are not incompatible
with the highest levels of development.
3.2.6 Further considerations
3.2.6.a Nordic model - The top five countries, Iceland, Finland, Sweden, Denmark and Norway,
cooperate in common institutions (e.g. the Nordic Council) and have some common societal traits, often
defined “Nordic model“ (Schubert and Martens 2005, Sederberg-Olsen 2006). Their top position in the
Metaindex ranking shows that the highest levels of development are compatible with high levels of
taxation, social spending, public employment and economic equality. These traits are sometimes
considered prejudicial for economic competitiveness, but this seems not to be the case for the Nordic
countries, which rank good also in the Global Competitivenes Index (respectively 11, 2, 3, 4 and 10).
Bergh (2006a, b) considers the success of the Nordic countries in the last decade in part due to recent
reforms intended to reduce social spending and to enhance economic freedom and globalization level,

9
whereas Lindert (2006a, b) opposes this view. According to Pestel and Radermacher (2003), some of
the traits of the Nordic countries, especially high economic equality and high levels of social security
and spending on education and health care are the most effective premises for stimulating development
and competitiveness in industrial mature societies.
3.2.6.b - Group B and G8 – Most G8 countries rank in the middle of the Metaindex ranking (position 12
to 19 for Germany, USA, UK, Japan and France), while Canada has position 8 and Italy 25. Insofar the
dominant role of most G8 countries on the international scene seems not to run parallel with the
authoritativeness to guide by example.
3.2.6.c - Group C - To group C belong four transition countries (Czech Republic, Slovak Republic,
Hungary and Poland), three southern EU-15 countries (Spain, Italy and Greece) and three other
countries (Korea Republic, Turkey and Mexico), peripheral to the economic regions of Japan and China,
Europe and North America. The 25th place of the G8 member Italy shows that high material prosperity
and international political status are not incompatible with a low level of development in OECD
comparison.
3.3 Analysis of co-graduation
Table 7 shows the correlation coefficient (cograduation coefficient of Spearman) among the ranks of the
30 OECD countries for 14 variables: the Metaindex, the ten MoD indices and three further variables
describing income, satisfaction with life and globalization. Figure 2 visualizes the correlation between
the Metaindex ranking and those of the other 13 variables. 13 other graphics, which visualize the data
in table 7, are presented in the Appendix.
We present the correlation between the ranks of the countries, not between the scores. This procedure
entails some loss of information but reduces unbalance and dispersion due to outlaying values of some
atypical countries (e.g. Luxembourg, Turkey, Mexico). However also the values of most indices, sub-
indices and variables reported in the original sources are not absolute; generally they are scores on a
relative scale of 0 to 1. Insofar they express a relative, ordinal gap between the best and the worst
country, which also leads to compression and loss of information. The rank approach adopted in this
study is legitimated through a relative socio-economic homogeneity of most OECD countries, if
compared with the rest of the world.
The main results of the correlation analysis are as follows.
a) The ten rankings are fairly homogeneous
All ten indices aggregated in the Metaindex show a high correlation with it, in the range 0.931-0.724.
For each of the ten MoD indices the Metaindex shows the highest or the second highest correlation.
This is due to a great extent to lack of strong inhomogeneities among the rankings of the ten MoD
indicesxviii
.
b) Low corruption is the best proxy for high development
The Corruption Perception Index shows by far the highest correlation with the Metaindex (0.931). This
is one of the most valuable results of this study: the Corruption Perception Index is the best proxy for
development in the OECD countries.
c) Satisfaction with life runs parallel to development
After corruption, satisfaction with life is the second best correlated index (0.866) with the Metaindex; the
association between these two parameters is fairly distributed along the whole ranking, as shown in the
group analysis. If satisfaction with life is taken as a good measure of success of a society, it is worth to
observe that development as described by the Metaindex is strongly associated with it. This finding is
all the more remarkable because this subjective variable is completely independent from the other
variables considered in this study.
d) Social factors and emerging issues are highly correlated
Among the four best correlating indices with the Metaindex, two describe social factors like corruption
(0.931) and press freedom (0.859) and two describe emerging issues like environmental sustainability
(0.864) and information technology (0.861).
e) Traditional economic indices are less correlated
The rankings of traditional economic indices like income (0.760), economic freedom (0.765) and
economic equality (0.724) show a fair correlation with the Metaindex ranking, but are the least correlated
among the ten MoD indices.

10
f) Globalization is poorly correlated
The Index of Globalization is by far the least correlated (0.454) of all indices with the Metaindex ranking
and with each of the 13 considered variables. Within the OECD countries a high level of globalization
and a high level of development are not necessarily associated. For example Iceland and Norway, two
of the best performers in the Metaindex ranking (1st
and 5th
), are among the worst performers (26th
and
21st
) in the globalization ranking in OECD context.
3.4 Future developments
The Metaindex of Development focuses on the most industrialized countries, assuming that – whether
desirable or not - many of their technological, economical, societal and environmental traits will have a
major influence on the world and that they will influence development policies in other countries. The
composition of the Metaindex of Development intends to reflect the discourse in the heterogenic
community of persons and institutions, which try to measure development or substantial parts of it.
Insofar the Metaindex should evolve together with the evolution of the work of this community. A
broadening of the scope of the indices related to development is desirable in order to fill some reporting
deficits, for example those in the following fields:
- Health and health care
- Equality of opportunities
- Citizens’ empowerment
- Diffusion of culture
- Environment conditions and resource use
4 Conclusions
Composing a Metaindex of development on the basis of the country rankings in ten established indices
of development showed that most of the ten top ranking countries (Iceland, Finland, Sweden, Denmark,
Norway, Switzerland, Canada, Netherlands, Australia and Ireland) have following common features:
small population, low population density, highest income and taxes, highest satisfaction with life and
lowest corruption. The following three major results stick out.
Population – Top performance in the Metaindex ranking is very frequently associated with a small
population, and in no case with a large one. A small country population can favour development thanks
to a higher level of following attributes: accessibility and knowledge of decisive persons, of opportunities,
of infrastructures and of institutions; community consciousness, personal engagement, participation in
public decisions; transparency, accountability, and control.
Taxation - The taxation level in the top performing countries indicates that high development is more
frequently associated with high taxation: the average total tax revenue of the top five and of the top ten
countries (45.4% and 39.0% of GDP) is higher than in OECD average (36.3% of GDP). Three high tax
countries rank also in the lower half of the Metaindex ranking (Belgium, 18th
; France 19th
; Italy 25th
)
showing that high taxation is by no means a sufficient condition for top development performance.
Conversely, the good Metaindex performance of Switzerlandxix
and Canada (6th
and 7th
) indicates that
high development is attainable also with moderate taxation (respectively 29.5% and 33.8% of GDP).
The distribution of the taxation levels along the Metaindex ranking indicates that high taxation is no
hindrance to high development, neither to high economic competitiveness as it results by the ranking of
the Global Competitiveness Index.
Corruption and Satisfaction – The two best correlating indices with the Metaindex are those for low
corruption (0.931) and for satisfaction with life (0.866). The Corruption Perception Index is then the best
proxy for development in OECD context. This is remarkable, because corruption is a “soft” factor, dealing
with the cultural sphere, not with hard economic features. A low level of corruption facilitates trust and
cooperation between partners and is probably the best lubricant for every social machine. Remarkable
is also the high correlation with satisfaction, because this variable is completely independent from the
other variables considered in this study
Some of the characteristic of the top Metaindex performers, e.g. population size and density, can not be
easily imitated, but some others are worth to be considered for orienting public policy: when
administered with equity and efficacy and when associated with low corruption, taxation and public
spending guarantee to the widest population some key factors for success such as high levels of
education and of health care, which in turn favour economic performance, development and
satisfactions with life.
Aknowledgements
The author thanks Bruno Cheli and Lucio Masserini for their assistance in the statistical elaboration, as
well as the same colleagues and Mauro Gallegati, Jochen Jesinghaus, Johann Graf Lambsdorff, Luisa

11
Merlini, Ulrich Müller-Herold, Roberta Rabellotti and Thomas Wiedmann for helpful suggestions.

12
Tables and Figures
Table 1 – The ten indices of the Metaindex of Development (MoD indices)
Theme
acronym
Index
acronym
Index name Release Reference years
First
published
Periodicity Countries
Aggregated
variables
Score -
OECD
range
Score -
World
range
Score
possible
1 WBeing WI Wellbeing Index 11.10.01 1996- 1999 2001 - 180 87 33.0-64.0 25.0-64.0 0-100
2 HumDev HDI Human Development Index 09.11.06 2004 1990 yearly 177 6 0.757-0.965 0.311-0.965 0-1
3 EcComp GCI Global Competitiveness Index 26.9.06 1995-2005 2001 yearly 125 89 4.14-5.81 2.50-5.81 1-7
4 EcFree IEF Index of economic freedom 4.1.06 2004 -2005 1995 yearly 161 50 1.28-3.11 1.28-5.00 1-5
5 EcEqua GI Gini Index 28.3.06 1999-2004 2006 yearly 30 1 24.7-49.5 19.03-74.3 0-100
6 InfTec NRI Networked Readiness Index 28.3.06 2003-2005 2001 yearly 115 66 - 0.14-2.02 -1.39-2.02 No limits
7 EnvSus ESI Environmental Sustainability Index 26.1.05 1990-2004 2000 irregular 146 76 43.0-75.1 29.5-75.1 0-100
8 Gender GGG Global Gender Gap 21.11.06 2000-2005 2005 yearly 115 14 0.5850-0.8133 0.4762-0.8133 0-1
9 PressF GPFR Global Press Freedom Ranking 27.4.06 2005 1980 yearly 194 23 9-48 9-97 0-100
10 Corrup CPI Corruption Perception Index 1.2.06 2003-2005 1995 yearly 163 9 3.3-9.6 1.8-9.6 0-10

13
Table 2 – Rankings* of the 30 OECD countries in the Metaindex of Development and in the ten MoD indices.
MoD
rank
Country MoD
value WBeing HumDev EcComp EcFree EcEqua InfTec EnvSus Gender PressF Corrup
1 Iceland 3.70 4 2 11 3.5 2 3 4 4 1.5 2
2 Finland 4.50 2 11 2 9.5 9 4 1 3 1.5 2
3 Sweden 4.55 1 5 3 14.5 3 6 3 1 4 5
4 Denmark 6.20 9 15 4 5 1 2 11 7 4 4
5 Norway 6.75 3 1 10 19.5 9 10 2 2 4 7
6 Switzerland 8.00 6.5 9 1 11 11 7 6 15 7.5 6
7 Canada 9.90 6.5 6 12 9.5 15 5 5 12 15 13
8 Netherlands 11.00 24 10 8 12 4 9 16 11 7.5 8.5
9 Australia 11.20 12 3 15 7 17 12 8 13 16.5 8.5
10 Ireland 11.25 11 4 17 1 16 16 10 9 12 16.5
11 Austria 12.20 5 14 13 13 5 15 7 16 23 11
12.5 Germany 12.30 8 21 7 14.5 13 14 13 5 13.5 14
12.5 New Zealand 12.30 10 20 19 7 23 17 9 6 10 2
14 USA 12.50 14 8 5 7 27 1 17 14 13.5 18.5
15 UK 13.40 20 18 9 3.5 20 8 20 8 16.5 11
16 Luxembourg 14.85 23 12 18 2 9 20 23 23 7.5 11
17 Japan 14.90 13 7 6 18 18 13 12 28 19 15
18 Belgium 16.55 21 13 16 17 6.5 19 29 18 7.5 18.5
19 France 18.05 16 16 14 26 12 18 14 25 23 16.5
20 Portugal 19.65 19 24 23 19.5 26 21 15 17 11 21
21 Czech Rep 20.10 17.5 25 22 16 6.5 23 26 21 19 25
22 Spain 20.90 28 19 21 21 21 22 24 10 23 20
23 Hungary 22.30 25 26 25 23 14 24 19 22 23 22
24 Slovak Rep 22.60 22 28 24 22 22 25 18 20 19 26
25 Italy 23.50 15 17 26 25 25 26 22 27 28 24
26 Korea Rep 23.60 27 23 20 27 19 11 30 29 27 23
27 Greece 24.35 17.5 22 27 28 24 27 21 24 26 27
28 Poland 26.10 26 27 28 24 28 29 28 19 23 29
29 Turkey 28.85 29 30 30 30 29 28 25 30 29.5 28
30 Mexico 28.95 30 29 29 29 30 30 27 26 29.5 30
* When more countries have the same rank, they get the value obtained meaning the available rank positions for them.

14
Table 3 – Rankings of the OECD countries for six relevant variables
MoD
Rank
Country
Smaller
population
2004, a
Lower popul.
density
2005, b
GDP pc,
PPP$
2004, a
Total tax
revenue
% GDP
2003, c
Satisfaction
with life
2000-2005, d
Globalization
2004, e
1 Iceland 1 2 5 10 3.5 26
2 Finland 5 6 14 4 5.5 9
3 Sweden 6 7 15 1 5.5 3
4 Denmark 7 20 8 2 1.5 11
5 Norway 10 4 4 5 11 21
6 Switzerland 8 22 6 26 1.5 8
7 Canada 19 2 10 21 7 7
8 Netherlands 17 29 9 11 10 5
9 Australia 18 2 13 23 14.5 17
10 Ireland 3 10 3 25 7 12
11 Austria 11 14 7 7 3.5 2
12.5 New Zealand 2 5 21 18 11 15
12.5 Germany 27 25 18 17 16 24
14 USA 30 8 2 27 11 18
15 UK 25 26 12 16 17 4
16 Luxembourg 4 23 1 9 7 23
17 Japan 29 27 17 29 24 28
18 Belgium 15 28 11 3 14.5 1
19 France 24 16 16 6 21 6
20 Portugal 16 18 24 14 25 13
21 Czech Rep 12.5 21 25 13 22 10
22 Spain 21 12 20 19 18 14
23 Hungary 12.5 15 26 12 28 16
24 Slovak Rep 9 17 27 24 29 25
25 Italy 23 24 19 8 19.5 19
26 Korea Rep 22 30 23 28 27 27
27 Greece 14 11 22 15 23 22
28 Poland 20 19 28 20 26 20
29 Turkey 26 13 30 22 30 29
30 Mexico 28 9 29 30 19.5 30
Data refer to the years indicated in the table. a: UNDP 2006; b: UN 2006; c: OECD 2006; d: Marks et al. 2006; e: KOF 2006.

15
Table 4 – Values of six relevant variables for the OECD countries
MoD
Rank
Country Population
size
x 106
p
2004, a
Population
density
p /km2
2005, b
GDP pc,
PPP$
2004, a
Total tax
revenue
% GDP
2003, c
Satisfaction
with life
2000-2005, d
Globalization
2004, e
1 Iceland 0.3 3 33 051 39.8 7.8 67.75
2 Finland 5.2 16 29 951 44.8 7.7 84.84
3 Sweden 9.0 20 29 541 50.6 7.7 89.89
4 Denmark 5.4 126 31 914 48.3 8.2 84.27
5 Norway 4.6 12 38 454 43.4 7.4 77.75
6 Switzerland 7.2 176 33 040 29.5 8.2 85.53
7 Canada 32.0 3 31 263 33.8 7.6 87.49
8 Netherlands 16.2 392 31 789 38.8 7.5 89.15
9 Australia 19.9 3 30 331 31.6 7.3 80.91
10 Ireland 4.1 59 38 827 29.7 7.6 83.09
11 Austria 8.2 98 32 276 43.1 7.8 91.60
12.5 New Zealand 4.0 15 23 413 34.9 7.4 73.46
12.5 Germany 82.6 232 28 303 35.5 7.2 82.48
14 USA 295.4 31 39 676 25.6 7.4 80.83
15 UK 59.5 246 30 821 35.6 7.1 89.29
16 Luxembourg 0.5 180 69 961 41.3 7.6 74.18
17 Japan 127.9 339 29 251 25.3 6.2 64.22
18 Belgium 10.4 341 31 096 45.4 7.3 91.96
19 France 60.3 110 29 300 43.4 6.6 87.71
20 Portugal 10.4 114 19 629 37.1 6.1 83.06
21 Czech Rep 10.2 130 19 408 37.7 6.4 84.46
22 Spain 42.6 85 25 047 34.9 7.0 82.52
23 Hungary 10.1 109 16 814 38.5 5.7 81.15
24 Slovak Rep 5.4 110 14 623 31.1 5.4 72.58
25 Italy 58.0 193 28 180 43.1 6.9 80.61
26 Korea Rep 47.6 480 20 499 25.3 5.8 64.82
27 Greece 11.1 84 22 205 35.7 6.3 74.94
28 Poland 38.6 123 12 974 34.2 5.9 78.22
29 Turkey 72.2 93 7 753 32.8 5.3 63.45
30 Mexico 105.7 55 9 803 19.0 6.9 55.49
Data refer to the years indicated in the table. a: UNDP 2006; b: UN 2006; c: OECD 2006; d: Marks et al. 2006; e: KOF 2006.

16
Table 5 – Population size, population density, GDP pc, total tax revenue, satisfaction with life and globalization: mean ranks and
mean values for the 30 OECD countries, divided in three groups (A: MoD rank 1 to 10; B: MoD rank 11 to 20; C: MoD rank 21 to
30).
MoD rank
Population
size
(106
p )
2004, a
Population
density
(p/km2
)
2005, b
GDP pc
PPP$
2004, a
Total tax revenue
as % of GDP
2003, c
Satisfaction
with life
2000-2005, d
Globalization
2004, e
A 1-10
Mean rank 9.4
Range 1-18
SD 6.4
-------------------------
Mean value 10.4
Range 0.3-32.0
SD 9.6
Mean rank 10.4
Range 2-22
SD 9.8
---------------------
Mean value 81
Range 3-392
SD 124
Mean rank 8.7
Range 5-15
SD 4.3
-----------------------------
Mean value 32 816
Range 29 541-38 827
SD 3 290
Mean rank 12.8§
Range 1-26
SD 10.0
------------------------
Mean value 39.0
Range 29.5-50.6
SD 7.7
Mean rank 6.7
Range 1.5-14.5
SD 4.2
------------------------
Mean value 7.7
Range 7.3-8.2
SD 0.3
Mean rank 11.9
Range 3-26
SD 7.5
------------------------
Mean value 83.1
Range 67.75-89.89
SD 6.5
B 11-20
Mean rank 18.3
Range 2-29
SD 10.2
-----------------------
Mean value 80.9
Range 0.5-295.4
SD 91
Mean rank 19
Range 5-28
SD 8.2
----------------------
Mean value 171
Range 15-341
SD 117
Mean rank 12.9
Range 1-24
SD 7.8
-----------------------------
Mean value 33 373
Range 19 629-69 961
SD 13 899
Mean rank 14.6
Range 3-27
SD 8.7
-----------------------
Mean value 36.7
Range 25.3-45.4
SD 7.0
Mean rank 15.0
Range 3.5-25
SD 7.1
------------------------
Mean value 7.1
Range 6.1-7.8
SD 0.6
Mean rank 13.4
Range 1-28
SD 9.8
------------------------
Mean value 82.0
Range 64.22-91.96
9.0
C 21-30
Mean rank 18.8
Range 9-28
SD 6.4
------------------------
Mean value 40.2
Range 10.1-105.7
SD 33
Mean rank 17.1
Range 9-30
SD 6.5
----------------------
Mean value 146
Range 55-480
SD 123
Mean rank 24.9
Range 19-30
SD 3.8
---------------------------
Mean value 17 731
Range 7 753-28 180
SD 6 572
Mean rank 19.1
Range 8-30
SD 7.1
-----------------------
Mean value 33.2
Range 19.0-43.1
SD 6.9
Mean rank 24.2
Range 18-30
SD 4.4
------------------------
Mean value 6.2
Range 5.3-7.0
SD 0.6
Mean rank 21.2
Range 10-30
SD 6.6
------------------------
Mean value 73.8
Range 55.49-84.46
SD 9.6
1-30
Mean value 38.8
Range 0.3-295.4
SD 59
Mean value 133
Range 3-480
SD 123
Mean value 27 973
Range 7 753-69 961
SD 27 973
Mean value 36.3
Range 19.0-50.6
SD 7.4
Mean value 7.0
Range 5.3-8.2
SD 0.8
Mean value 79.6
Range 55.5-92.0
SD 9.2
§ TTR average rank of countries with MoD rank 1 to 5: 3.5; with MoD rank 6 to 10: 21.2
a: UNDP 2006; b: UN 2006; c: OECD 2006; d: Marks et al. 2006; e: KOF 2006

17
Table 6 – Difference between the ranking for the Metaindex of development and that for GDP pc
MoD rank GDP pc rank GDP pc
minus MoD rank
Iceland 1 5 4
Finland 2 14 12
Sweden 3 15 12
Denmark 4 8 4
Norway 5 4 -1
Switzerland 6 6 0
Canada 7 10 3
Netherlands 8 9 1
Australia 9 13 4
Ireland 10 3 -7
Austria 11 7 -4
New Zealand 12 21 9
Germany 13 18 5
USA 14 2 -12
UK 15 12 -3
Luxembourg 16 1 -15
Japan 17 17 0
Belgium 18 11 -7
France 19 16 -3
Portugal 20 24 4
Czech Rep 21 25 4
Spain 22 20 -2
Hungary 23 26 3
Slovak Rep 24 27 3
Italy 25 19 -6
Korea Rep 26 23 -3
Greece 27 22 -5
Poland 28 28 0
Turkey 29 30 1
Mexico 30 29 -1

18
Table 7 – Correlation coefficients among the rankings of the MoD, the ten MoD indices, income, satisfaction and globalization.
WBeing HumDev EcComp EcFree EcEqua InfTec EnvSus Gender PressF Corrup MoD Income Satisf Global
WBeing 1 0.705 0.712 0.529 0.541 0.677 0.898 0.667 0.634 0.749 0.837 0.575 0.718 0.342
HumDev 0.705 1 0.717 0.64 0.543 0.739 0.707 0.545 0.653 0.725 0.820 0.852 0.726 0.302
EcComp 0.712 0.717 1 0.626 0.622 0.906 0.687 0.63 0.719 0.804 0.853 0.705 0.744 0.483
EcFree 0.529 0.64 0.626 1 0.478 0.683 0.523 0.647 0.719 0.744 0.765 0.763 0.743 0.340
EcEquali 0.541 0.543 0.622 0.478 1 0.559 0.475 0.48 0.659 0.672 0.724 0.575 0.677 0.547
InfTec 0.677 0.739 0.906 0.683 0.559 1 0.672 0.647 0.701 0.799 0.861 0.720 0.721 0.371
EnvSus 0.898 0.707 0.687 0.523 0.475 0.672 1 0.691 0.636 0.8 0.864 0.536 0.663 0.274
Gender 0.667 0.545 0.63 0.647 0.48 0.647 0.691 1 0.771 0.755 0.815 0.501 0.684 0.412
PressF 0.634 0.653 0.719 0.719 0.659 0.701 0.636 0.771 1 0.816 0.859 0.662 0.721 0.354
Corrup 0.749 0.725 0.804 0.744 0.672 0.799 0.800 0.755 0.816 1 0.931 0.688 0.797 0.360
MoD 0.837 0.820 0.853 0.765 0.724 0.861 0.864 0.815 0.859 0.931 1 0.760 0.866 0.454
Income 0.575 0.852 0.705 0.763 0.575 0.720 0.536 0.501 0.662 0.688 0.760 1 0.824 0.384
Satisf 0.718 0.726 0.744 0.743 0.677 0.721 0.663 0.684 0.721 0.797 0.866 0.824 1 0.481
Global 0.342 0.302 0.483 0.340 0.547 0.371 0.274 0.412 0.354 0.360 0.454 0.384 0.481 1
Bold figures are the highest correlation coefficient on a row

19
Figure 1 – Average rank of the three groups of countries (A: MoD rank 1 to 10; B: MoD rank 11
to 20; C: MoD rank 21 to 30) for population size, population density, income (GDP pc), total tax
revenue, satisfaction with life and globalization.
Fig. 2 – Correlation between the ranking of the Metaindex of Development and of those of the
ten MoD indices (grey bars) and of the indices for income, satisfaction with life and globalization
(white bars)
0 10 20 30
Globalization
Satisfaction
Taxes
Income
Low density
Small popul.
Rank
1-10
11-20
21-30
Correlation with the Metaindex of Development
0 0,2 0,4 0,6 0,8 1
Global
EcEqua
Income
EcFree
Gender
HumDev
WBeing
EcComp
PressF
InfTec
EnvSus
Satisf
Corrup

20
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24
Notes
i
The eight Millennium Development Goals of the United Nations are: 1. Eradicate extreme poverty and hunger. 2.
Achieve universal primary education. 3. Promote gender equality and empower women. 4. Reduce child mortality.
5. Improve maternal health. 6. Combat HIV/AIDS, malaria and other diseases. 7. Ensure environmental
sustainability. 8. Develop a global partnership for development. Most Millennium Development Goals regard basic
elements of human wellbeing. Although progress in some of these fields is needed also in industrialized countries
(e.g. poverty, gender gap), most issues covered by the MDG regard a large part of the population only in less rich
or less industrialized countries. The issues covered by the MoD indices do not regard basic human needs but
rather the socio-economic structures of a country. Most of them are important also for developing countries (e.g.
environmental sustainability, gender gap, corruption, freedom of press); insofar the MoD indices are not alternative
to the MDG and their goals are relevant both for more and for less industrialized countries.
ii
“…in using it (the growth of GDP) to judge economic problems and policies, distinctions must be kept in mind
between quantity and quality of growth, between its costs and return, and between the short and the long run.”
“…given the variety of qualitative content in the over-all quantitative rate of economic growth, objectives should
be explicit: goals for "more" growth should specify more growth of what and for what. It is scarcely helpful to urge
that the over-all growth rate be raised to x percent a year, without specifying the components of the product that
should grow at increased rates to yield this acceleration, the needs and priorities that are thus to be satisfied,
and the costs that may have to be incurred to assure such returns. If economic growth is to be more deliberately
geared to what is wanted, effort must be exerted to formulate a consensus; or, still better, continuously to
formulate and reformulate it in response to changing conditions, and with sufficient flexibility to allow for deviant
innovators.” (Kuznets 1962)
iii
Furthermore a surprising confusion in handling GDP as a beacon of progress regards international comparisons:
when comparing countries, most information media and often some scholars use the GDP pc either in US $ or in
PPP $, regardless of the different theoretical foundations on which these two yardsticks are based and of the great
differences in the rank positions when using PPP $ instead of US $, especially when comparing high-income and
low-income countries. E.g. the economic scenarios of the International Panel on Climate Change are based, also
for less rich countries, on US $ and not on PPP $; this can be source of distortion.
iv
“Unlike the ESI, the Wellbeing of Nations does not include measures of social capacity and it is not updated.
The Wellbeing Index has also been criticized for its lack of transparency in the determination of the underlying
weighting scheme.“ (Esty et al., 2005)
v
In 2004 the OECD started the global project “Measuring the progress of societies“ to encourage the search for
and the use of new comprehensive measurements of development, welfare and wellbeing (OECD 2008); this
global project organized two World Fora on “Measuring the Progress of Societies” in Palermo (10-13 November
2004) and Istanbul (27-30 June 2007). According to the “Istanbul declaration” there is “an emerging consensus on
the need to undertake the measurement of societal progress in every country, going beyond conventional
economic measures such as GDP per capita” (OECD 2007). Within this OECD global project several measures
of development or wellbeing were reviewed (Matthews 2006).
vi
The ten indices collected in the Metaindex of Development can be assigned to the five instrumental freedoms
defined by Sen (1999) as follows:
Political freedom Press freedom
Economic facilities Human development, economic freedom, economic competitiveness, economic
equality, information technology
Social opportunities Human development, gender gap, economic equality
Transparency guarantees Press freedom, information technology
Protective security -
None of the ten MoD indices covers protective security. The Wellbeing Index (human and ecosystem wellbeing)
covers social, economic and environmental issues that are distributed over the five instrumental freedoms.
Environmental rights and environmental sustainability are not directly covered by the five instrumental freedoms.
vii
Whereas the KOF Index of Globalization (KOF 2007) covers 123 countries, including all OECD countries, the
A.T. Kearney/Foreing Policy Magazine (2006) Globalization Index covers 62 countries, including only 27 OECD
countries. In order to compare the two indices, we took the two rankings of the 27 OECD countries considered in
the latter index and we standardized them in a OECD scale from 1 to 27; both data sets refer to 2004. The two
indices show remarkable differences for 14 out of the 27 considered OECD countries, featuring a difference of 5
to 9 rank positions for each of 12 countries, of 12 positions for France and New Zealand and of 15 positions for
the USA. If the rank differences of Australia, Canada, New Zealand and the USA are summed and compared with
the summed rank differences of the 9 considered EU-15 countries, the A.T. Kearney/FP Globalization Index
overranks Australia, Canada, New Zealand and the USA for 37 rank positions and underranks the 9 EU-15
countries for 25 rank positions. This can be due to a higher conformity of the structure and weighting of this index
(variables and weights) with the features of US-like societies.

25
viii
The data in each index refer to the decade 1995-2005, most of them to the years 2000-2005. We assume that
most of the changes accounted for in most indices have a relatively slow pace, so that their spreading over few
years does not cause unacceptable distortions.
ix
A sensitivity analysis was done, calculating ten times the average Metaindex value of nine instead of ten MoD
indices, leaving away each time a different index. The obtained ten new rankings show little difference from the
Metaindex ranking based on ten indices. The sum of the absolute position differences between the Metaindex
ranking (R10) and each of the ten rankings based on nine indices (R9) is in average 18, going from 11 when
economic competitiveness is excluded, up to 25 and 26 when environmental sustainability or economic equality
are excluded. Among 300 possible rank positions (30 countries x 10 different rankings) only 10 show a rank shift
of 3 to 4.5 positions. Most affected are Austria (3 times +4), the USA (3 times -3), Netherlands (+3 and +4.5),
Australia (+4) and Germany (-3,5).
R9
Δ
(R10 minus R9) Australia Austria Germany Netherlands USA
no EcEqua 26 4 4.5
no EnvSus 25 4 -3
no Corrup 19 -3
no HumDev 18 4 -3.5
no PressF 18 3
no WBeing 17 4 -3
no EcFree 15
no InfTec 15
no Gender 12
no EcComp 11
Average 17.6
x
A partition of all countries into three groups with high, medium and low human development according to their
rank in the Human Development Index (HDI) is practiced also by the UNDP in its Human Development Reports
(UNDP 2006). Also UNICEF (2007) makes a similar tripartion of the OECD countries according to their position in
the ranking of its index of children wellbeing.
xi
Statistical analysis of countries as if they were independent monadic entities with the same chances to be
anywhere in the variance curve of a parameter should be considered with caution. Variance analysis of relevant
parameters of say 100 trees in a forest or 100 pills produced in a pharmaceutical manufacture assume that each
individual should be almost identical to the others, but for some variance of given parameters. About countries,
we do know that many of them are very different. Population size as well as geographic, environmental, cultural
and historical conditions can vary enormously and reduce the meaningfulness of a comparison. Think for example
at Luxembourg versus China. Furthermore, when comparing development parameters of countries it should be
remembered that in a given year different countries are at different historical stages of development and that
industrialization or building of infrastructures and institutions occurring now, happens in very different conditions
than analogous steps occurred in other countries many decades before. Even within the small ensemble of the 30
OECD countries, we must be aware that homogeneity and comparability is rather high only among circa two third
of them; the remaining OECD countries have special features and history due either to being transition countries
(Czech Republic, Slovak Republic, Hungary and Poland) or peripheral countries of late industrialization (Korea
Republic, Mexico, Turkey) or European Mediterranean countries (Greece, Italy, Spain). If country comparison aims
to see who is performing better and to highlight some practices that are worth to be considered as possible model
for other countries, this comparison is most useful when focused on countries that are similar in many respects
and that would all really have the same chances to be top performers.
xii
Average population density is a coarse parameter that would need further differentiation: the proportion of
inhospitable or inhabited land should be considered as well as different distribution patterns of the population, e.g.
a great dispersion of many small dwelling units (e.g. Scandinavian countries) or a high concentration in one or few
urban agglomerations in a country with large inhospitable territories (e.g. Island, Australia).
xiii
Two outliers, Luxembourg and Belgium, enhance the dispersion of the GDP pc data in group B; the winsorized
averages of group B without Luxembourg and Belgium are 13.0 (instead of 12.9) for the rank and 30 517 PPP$
(instead of 33 373) for the value.
xiv
The range of the results of the investigations on the effects of the economic activity of the state in market
economies goes from comparing it to “a leaking bucket” until considering it “an irrigation system” (Korpi 1985).
Surprisingly enough these opposite conclusions are drawn not only in historical studies (Tanzi 2000, Lindert 2004)
but also by empirical investigations. In most of the latter the use of “the heavy machinery of econometrics” and the
“necessity of displaying econometrical virility” (Peacock and Scott 2000) do not compensate for a series of
shortcomings. The investigated relationship is in most cases that between only some parts of the economic activity
of the state and the growth (very rarely, the level) of GDP or GDP pc. Although not considered identical to the

26
progress of societies, growth of GDP is still considered as if it was the best proxi for progress, just as it was more
than three decades ago (Nordhaus and Tobin 1973). Many of the empirical investigations mix countries with very
high and very low income as well as with very different levels and phases of economic and institutional
development; this mixing is an implicit assumption that the relationship between progress and the economic activity
of the state is comparable in low and in high industrialized societies, in low monetized and in high monetized
societies, in agriculture-based and in service-based societies. Furthermore, most studies are not able to explore
the causation direction between the size of state activity and economic growth. Although some studies mean to
have proven that there is or there is not a negative or a positive relationship between economic growth and the
size of the economic activity of the state, more convincing studies (Slemrod 1995) and more recent ones (Nijkamp
and Poot 2004; Frick et al. 2006) reckons that proof for the one or the other conclusion are weak or inconclusive.
xv
The role of the state in the economy is at least of four types: regulation, redistribution of income, provision of
basic services (e.g. police, defence, justice, tax collection), production of goods and other services. Most research
on the relationship between the state activity in the economy and the progress of societies measure what the state
collects, mainly through tax revenues, or what it spends, but disregard some of the goods and services produced
by enterprises owned or dominated by the state. Peacok and Scott (2000) reviewed fifteen papers that tried to
check empirically the “Wagner’s Law” of increasing state activity (more wealth, more state); they observe that in
all paper the “Wagner’s Law” is misspecified and that, in spite of the clear definition of Wagner himself, “the major
misreading of Wagner is reflected in the omission from all the studies of public utilities as part of the public sector”.
As an alternative measure of the public sector Peacok and Scott suggest public employment as a share of total
employment; but also this measure has shortcomings.
xvi
This finding in respect to development is parallel with what is stated by the so called “Wagner’s Law” in respect
to national income: as national income grows, also the proportion of the activity of the state in the economy grows
(Wagner 1911; Timm 1961; Peacock and Scott 2000).
xvii
As “low-tax” country Switzerland is a special case. The taxation level and the role of the state in the economy
are not as low as told by reported statistics. Switzerland is characterized by dynamic capitalism and entrepreneur
friendly policy and institutions but also by a deep spirit of community and a major role and reputation of the public
service. The economic activities in which public institutions are dominant or important players are more numerous
and larger than in most capitalistic countries; these include railway and road transport, public urban transport,
health care, production and distribution of electricity, telecommunication, tv and radio broadcasting, schools,
universities, local banks, housing, waste and recycling treatment, production of arms, military equipment and
alcohol. A part of the pension system and the basic health care insurance is private but contribution of employees
and employers to them is obligatory and strongly regulated by the state. Should these two contributions be
computed as taxation, because obligatory, the taxation level in Switzerland would be 5 to 10 per cent of GDP
higher than the reported figure (29.5% of GDP in 2003).
xviii
When the inhomogeneity between rankings is high, the cograduation coefficient is much lower, e.g. 0.454 for
the Metaindex and the Globalization Index.
xix
Switzerland should be considered a special case. See endnote nr. 17.

A Metaindex of Development Morosini 1 Nov 2008

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