1. Art and Diseño

The Global Competitiveness
Index 1
XAVIER SALA-I-MARTIN, Columbia University,
Universitat Pompeu Fabra, and NBER
ELSA V. ARTADI, Harvard University
Competitiveness has become a constant fixation among
political leaders, popular press, corporations, and national
and international institutions. Even plain citizens worry
about the “competitiveness” of a nation when they
observe, puzzled, how outsourcing or manufacturing relocation takes jobs from their home country.
This chapter presents a new index of competitiveness:
the Global Competitiveness Index.We designed this new
index with the goal of unifying the two indexes currently
produced by the World Economic Forum (the Growth
Competitiveness Index [McArthur and Sachs (2001)] and
the Business Competitiveness Index [Porter (2001)]), and
it is meant eventually to replace them in the Global
Competitiveness Report.
Competitiveness is defined as the set of institutions,
policies, and factors that determine the level of productivity of a country.2 The level of productivity, in turn, sets the
sustainable level of prosperity that can be earned by an
economy. In other words, more competitive economies
tend to be able to produce higher levels of income for
their citizens.The productivity level also determines the
rates of return obtained by investments in an economy.
Given that the rates of return are the fundamental determinants of the aggregate growth rates of the economy, a
more competitive economy is one that is likely to grow at
larger rates over the medium to long run.
The World Economic Forum has been publishing two
indexes of competitiveness that are supposed to describe
two aspects of the same phenomenon.While the Growth
Competitiveness Index (GCI) refers to the aggregate or
macroeconomic determinants of productivity, the Business
Competitiveness Index (BCI) captures the microeconomic
components of productivity (in fact, in 2002, the BCI was
called the “Microeconomic Competitiveness Index”).We
believe that the macroeconomic and microeconomic
determinants of competitiveness cannot and should not be
separated.The ability of firms to prosper depends, among
other things, on the efficiency of the public institutions,
the excellence of the education system, and the overall
macroeconomic stability of the country in which they
operate. But an excellent macro environment does not
guarantee national prosperity unless firms create valuable
goods and services using efficient methods and processes
at the microeconomic level. Only by reinforcing each
other can the micro and macroeconomic characteristics of
an economy jointly determine its level of productivity and
competitiveness.Thus, it is not surprising that the correlation between the GCI and BCI has always been very high
(for example, last year the rank correlation between the
two indexes was 95.4 percent).
Another difference between the BCI and GCI is supposed to be that, while the BCI captures the “static” or
“level” determinants of productivity of a country, the GCI
is supposed to capture its “dynamic” or “growth”
1.3: The Global Competitiveness Index
CHAPTER 1.3
51
1.3: The Global Competitiveness Index
52
prospects. As mentioned above, we think that the concept
of competitiveness involves static and dynamic components: although the productivity of a country clearly
determines its ability to sustain a high level of income, it is
also one of the central determinants of the returns to
investment, which is one of the central factors explaining
an economy’s growth potential.Thus, given that productivity
has both static and dynamic implications for a country’s
standard of living, an alternative (although almost identical) definition of competitiveness would be the set of institutions, policies, and factors that set the sustainable current
and medium-term levels of economic prosperity.3
In this chapter we propose a unified approach that
captures both the microeconomic and macroeconomic
foundations of competitiveness as well as its static and
dynamic consequences in a single index that we call the
Global Competitiveness Index.We call it “Global” because
the index is destined to become the flagship index of the
Global Competitiveness Report, and because it is meant to
capture the entirety of factors that help determine the
productivity of nations.
The new index is based on three principles.
Principle 1. Productivity is complex: Twelve pillars of
competitiveness
The first principle is that the determinants of competitiveness are many and complex. Some of the best economic
minds of the last two hundred years have asked what
determines the wealth of nations. Adam Smith argued that
specialization and the division of labor was key.Thomas
Malthus and David Ricardo, two of the best economists of
the 19th century, thought that natural resources imposed a
binding limit on the level of prosperity.The law of diminishing returns meant that population growth would eventually require the use of low-quality land, and this would
reduce production per capita and cap the potential for
economic growth.
The neoclassical economists of the 20th century
emphasized investment in physical capital and infrastructures.This belief underlay many plans that governed the
economy of the Soviet Union and the countries under its
political influence. It was also the foundation upon which
institutions such as the World Bank operated for decades.4
The failure of many developing countries to grow despite
the aid of the donors proved that investing in physical
capital was not enough to generate aggregate wealth.
Economists, then, looked for other mechanisms. Education
and training (or human capital, as modern economists call
it) became the center of economic research. Developing
countries were advised to educate their children and to
invest in the expansion of their human capital.They
did...but economic growth failed to materialize in most
of them.
Technological progress (whether created by the country or copied from the leading economies) was then
thought to be a central determinant of economic growth.5
Few people today disagree with this idea, although this
merely shifts the question from “what determines the
growth rate of GDP?” to “what determines the rate of
technological progress?”This is why economists have kept
searching. Many answers have been proposed: openness,
macroeconomic stability, governance, the rule of law,
institutions, lack of corruption, market orientation, government waste, firm sophistication, demand conditions,
market size, and many others.
Each of these conjectures rests on solid theoretical
foundations and makes economic sense; some even have
strong empirical support.The central point, however, is
that they could all be true at the same time because they
are not mutually exclusive.The main lesson from two
centuries of economic thinking should be that the process
of economic development is rather complex and many
factors are needed for a country to succeed. As William
Easterly (2002) famously put it: “there is no such a thing
as a Holy Grail of economic success.”
We capture this complexity by assigning the many
factors that underlie competitiveness to 12 areas that we
call the 12 pillars of economic competitiveness.These pillars are:
First pillar: Institutions
The institutional environment forms the framework within which private individuals, firms, and governments interact to generate income and wealth. In 1776, Adam Smith
argued that wealth could not be created in a world where
property rights are not well defined and guaranteed. De
Soto (2000) also defends the importance of the system of
property rights. Owners of land, corporate shares, and
even intellectual property are unwilling to invest in the
improvement and upkeep of their property if their rights
as owners are insecure. Equally importantly, if property
cannot be bought and sold with the confidence that the
authorities will endorse the transaction, the market itself
will fail to generate dynamic growth.The absence of
property rights also drives people out of formal markets
into the informal sector. De Soto estimates that people
the developing and former communist countries hold
more than US$9 trillion in what he calls “dead capital”—
property that is owned informally, but not legally, and is
thus incapable of forming the basis of robust economic
development. More recently, an important and voluminous
strand of empirical research confirms the importance of
public institutions as key determinants of the current level
of GDP per capita.6
The importance of institutions is not restricted to the
legal framework. Government attitudes toward markets
and freedoms and the efficiency of its operations are also
very important: excessive bureaucracy and red tape,7
Second pillar: Physical infrastructures
A second important determinant of competitiveness is the
physical infrastructure environment. For many years, economic
development economists,9 practitioners, international institutions, and donors10 have emphasized investment in physical infrastructures as a required ingredient in the process
of economic growth. Private firms cannot operate satisfactorily in a economy where it is hard to transport factors of
production, final goods, or services; where it is hard to
communicate or transmit information (because telephone
lines are down a substantial fraction of the time or internet connections are hard and expensive); or where the
electrical supply is unreliable.
Third pillar: Macro stability
The stability of the macroeconomic environment is
important for business and, therefore, is important for the
overall competitiveness of a country. Although it is certainly true that macroeconomic stability alone cannot
increase the productivity of a nation, it is not less true that
macroeconomic disarray harms the economy. Firms cannot make informed decisions when the inflation rate is in
the hundreds (typically as a result of public finances being
out of control).The financial sector cannot function if the
government runs gigantic deficits (especially if, as a result,
it represses banks and it forces them to lend it money at
below-market interest rates).The government cannot provide services efficiently if it has to make enormous interest
payments on its past debts. In sum, the economy cannot
grow unless the macro environment is stable or favorable.
This is why the macroeconomic environment is the third
pillar of economic competitiveness.11
Fourth pillar: Security
Although not much attention is given in the economic
development literature to the problem of personal security,
and although neither the GCI nor the BCI (the two
indexes published by the World Economic Forum) include
it, wealth and prosperity can hardly be created if the safety
of managers, administrators, employees, or even customers
cannot be guaranteed because of military conflicts, terrorism, organized crime, or political and economic kidnappings. A country that cannot guarantee the personal safety
of its citizens is a country that cannot be competitive.12
Fifth pillar: Human capital
Human capital is the factor of production associated with
the human body.We think of it as having two important
components.The first one is what we could call basic
human capital, which consists of the basic requirements for
a human body to function and be productive. Chief
among these requirements is health.The productivity of
an unhealthy human body is less than that of a healthy
counterpart.The recent AIDS and malaria pandemics in
large regions of the world makes it clear that business
conditions deteriorate when the health of the population
declines.13 Another component of basic human capital is
basic education: literacy and primary schooling have nowadays become essential requirements for competitiveness.
In more advanced economies, good health and basic
education are not enough for citizens to earn a decent living. Advanced education (secondary and tertiary schooling) and flexible skills need to be acquired in high-quality
schools or in the firm through sophisticated on-the-job
training.The quality of the education system, therefore,
not only its enrollment rates and the quantity of scientists
and engineers, plays an essential role in the process of
wealth creation for these more advanced forms of human
capital.14
Sixth pillar: Goods market efficiency
The efficiency of the products and services markets is also
an important factor in a nations’ productivity. Goods market efficiency is needed in at least three levels. First, efficient markets require non-disruptive public interventions
(that is, policies and regulations need to cause as little disruption as possible). Excessive or inefficient taxes, burdensome subsidy policies, or nontransparent legal systems are
some ways in which government actions distort the markets for goods and services. Second, market efficiency is
driven by business competition. Competition imposes the
necessary discipline and readiness on firms so that they
operate in the most efficient manner. Market dominance
by one or a few firms tends to generate market inefficiencies, as do restrictions to competition from foreign rivals.
Third, market efficiency depends on demand conditions
such as customer sophistication: customers who accept
poor treatment by firms tend not to impose the necessary
discipline on companies for efficiency to be achieved in
the market.
1.3: The Global Competitiveness Index
overregulation, corruption, dishonesty in dealing with
public contracts, lack of transparency and trustworthiness,
or the political dependence of the judiciary system impose
significant economic costs to businesses and slows down
the process of economic development.
Although the economic literature has mainly focused
on public institutions, “private institutions” are also important ingredients in the process of creation of wealth.
Corporate governance, transparency, and accountability, for
example, are seen as important by economists who focus
on the theory of the firm: bargaining over the ex-post
rents of a firm become important in a world in which is
impossible to write contracts that fully specify the division
of rents under all possible contingencies.8
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1.3: The Global Competitiveness Index
Seventh pillar: Labor market efficiency
Many economic analysts (especially in Europe) emphasize
the flexibility of the labor market as a leading determinant
of competitiveness.The usual complaint is that tax and
transfer systems tend to reduce incentives to work and that
regulations impeding the hiring and firing of workers tend
to impose heavy costs on business. Although we agree
with this view, we think of efficiency of the labor market
in a broader sense that includes not only public actions
(taxes, transfers, regulations, and so on), but also private
practices. For example, labor-employer relations that are
very confrontational tend to generate an adverse business
environment.The systematic promotion of relatives rather
than workers with superior qualification, or the payment
of wages that are not related to productivity, tend to have
perverse effects on the productivity of the economy.
Another labor practice that is harmful to competitiveness is discrimination. Discrimination consists of not allocating jobs based on the talent of the candidates but based
instead on their race, religion, gender, or some such similar
consideration. One of the most widespread discriminatory
practices is the one that affects women’s labor participation: countries that exclude half of their populations from
the best jobs are countries that misallocate half of their
talent.This has important consequences for a country’s
ability to generate prosperity.
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Eighth pillar: Financial market efficiency
An efficient financial sector is needed to allocate the
resources saved by a nation’s citizens to its most productive
uses. A proficient financial sector channels resources to the
best entrepreneurs rather than to the politically connected.
A modern financial sector develops products and methods
so that small innovators with good ideas can implement
them. A well-functioning financial sector needs to provide
risk capital and loans and be trustworthy and transparent.
In a globalized world, the role of foreign financing is also
important, especially for economies with less developed
financial systems.Thus, we include the foreign financing
(in the form of foreign direct investment) in our analysis
of financial market efficiency.
Ninth pillar: Technological readiness
One of the central differences between rich and poor
countries is that rich countries tend to use more advanced
and complex production processes and tend to produce
more sophisticated products and services. In other words,
they tend to have a superior technological background.
Whether the technology used has or has not been invented within its borders is immaterial for our purposes.The
central point is that the firms operating in the country
have access to these advanced products and blueprints.
That is, it does not matter whether a country has invented
electricity, the Internet, or the airplane.What is important
is that these inventions are available to the business
community.
This does not mean that the process of innovation is
irrelevant. However, the level of technology available to
firms in a country needs to be distinguished from the
country’s ability to innovate and expand the frontiers of
knowledge.That is why we separate technological readiness from innovation, which is the 12th pillar below.
Tenth pillar: Openness and market size
The size of the market affects productivity because large
markets allow firms to better exploit economies of scale.
Traditionally, the markets available to firms have been constrained by the borders of the nation. In the era of globalization, exports have become a substitute for domestic
markets, especially for small countries.
The empirical evidence on the relation between
international trade and growth is highly controversial.
There is a lot of evidence showing that trade is positively
associated with growth.15 There is some evidence suggesting that these results are not as strong and convincing as
one would like, but there is no evidence suggesting that
trade and growth are negatively associated. Our reading of
the literature is that the relation between openness and
growth is likely to be positive and robust, especially for
small countries with small domestic markets. For larger
economies, the domestic market may be large enough that
no extra gains are achieved by further opening borders to
trade.Thus, we think of international trade as a substitute
for domestic demand in determining the size of the market for the firms of the country.This is particularly important in a world in which economic borders are not as
clearly delineated as political ones. In other words, when
Belgium sells goods to the Netherlands, the national
accounts register the transaction as an export (so the
Netherlands is a foreign market of Belgium), but when
California sells the same kind of output to Nevada, the
national accounts register the transaction as domestic (so
Nevada is a domestic market of California). By adding
domestic and foreign markets in our measure of market
size, we avoid discriminating against geographic areas
(such as the European Union) that are broken into many
countries but have one common market.This is why we
do so when we construct the tenth pillar of economic
competitiveness: the market size.
Eleventh pillar: Business sophistication
Economic development usually requires increasing degrees
of business sophistication. One form of sophistication is
the formation of clusters. As defined by Porter (2003),
“clusters are geographically proximate groups of interconnected companies, suppliers, service providers, and
associated institutions in a particular field, linked by
commonalities and complementarities.” Clusters affect
Twelfth pillar: Innovation
The last pillar of competitiveness is technological innovation. One of the central tenets of neoclassical growth theory is that, in the long run, the only sustainable source of
economic prosperity is technological progress.16 Although
substantial gains can be obtained by improving institutions, building infrastructures, reducing macroeconomic
instability, or increasing the human capital of the population, all these factors seem to run into eventual diminishing returns.The same is true for the efficiency of the
labor, financial, or goods markets. In the long run, standards of living cannot be expanded without technological
innovation. Innovation is particularly important for
economies as they approach the frontiers of knowledge
and the possibility of copy and imitation tend to disappear.The environment that is most inductive to innovation includes modern universities and research institutions
that cooperate with businesses, a legal environment that
protects intellectual property rights, public institutions that
understand the importance of knowledge and act on this
understanding when they make purchasing decisions, and
the availability of scientists and engineers who can participate in the process of technological improvement.
Although we describe the 12 pillars of competitiveness separately, we do so only for expository purposes.
This should not obscure the fact that they are not independent: not only they are related to each other, but they
tend to reinforce each other. For example, innovation
(12th pillar) is not possible in a world without institutions
(1st pillar) that guarantee intellectual property rights, it
cannot be performed in countries with no human capital
(5th pillar), and will never take place in economies with
inefficient markets (6th, 7th, and 8th pillars), without
infrastructures (2nd pillar), or in nations at war (4th pillar).
Although the actual construction of the index will
involve the aggregation of the 12 pillars into a single
index, we report measures of the 12 pillars separately
because offering a more disaggregated analysis can be
more useful to countries and practitioners.This is because
such an analysis gets closer to the actual areas in which a
particular country needs to improve.
Principle 2. Stages of development
The second principle on which the Global Competitiveness
Index is founded is that economic development is a
dynamic process of successive improvement, in which
economies find increasingly sophisticated ways of producing and competing. In other words, the process of economic development evolves in stages.
Many economists in the past have postulated theories
of “stages of development.” Perhaps the most famous of all
these theories was that of American historian W.W.
Rostow.17 Although Rostow’s theory involves five stages,
his was essentially a theory of industrialization through
savings and investment.The various stages were phases
through which the required resources to invest were accumulated, but successive take off occurred only through
physical capital accumulation.
Our view is that the process of growth and development is a lot more complicated than a simple process of
investment in physical capital. It involves the successful
implementation of policies and institutions on many different fronts. How important each factor is depends on
the level of development of a particular country: what
makes the United States competitive may not be the same
as what makes Angola competitive because these two
countries are in different phases of development.Thus, we
adopt the framework of stages of development to organize
the index.This framework is close in spirit to that of
Porter (1990) for a variety of reasons. One reason is that,
since the index presented in this chapter is destined to
eventually substitute for the GCI and BCI, and given that
the BCI is theoretically based on Porter (1990), we prefer
not to break too much with the past and so continue to
use a theoretical framework similar to that of the BCI. But
continuity is not the main reason for adopting a theory of
stages of development close in spirit to Porter’s.The central point is that we do believe that the main factors determining competitiveness for poor countries are essentially
different from those that matter in more advanced
economies. Moreover, some elements of Porter’s view are
useful for both our understanding of those stages and their
implementation as an empirical index.
Although the theory underlying our index is close in
spirit to that of Porter, there are some important discrepancies.
1.3: The Global Competitiveness Index
competitiveness in various ways: first, firms with a cluster
have more efficient access to specialized suppliers, employees, information, and training than isolated firms, and this
increases their productivity. Second, clusters increase the
capacity for productivity growth.This is because opportunities for innovation are often seen more easily within
clusters, and because the skills, assets, and capital required
to innovate tend to be more available around clusters.The
third way in which clusters affect competitiveness is by the
formation of new businesses through the reduction of barriers to entry (for example, the presence of many experienced workers and access to all the needed inputs and
specialized services within a proximity makes it easy to set
up new firms, which reduces barriers to entry).
A second form of business sophistication is through
more complex operations and strategies. For example, the
use of marketing or branding, the utilization of superior
distribution systems, the access to advanced technologies,
and the introduction of modern business organizational
forms are all ingredients in the process of business modernization (see Porter, 2003).
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1.3: The Global Competitiveness Index
56
One difference is that, while he thinks of the process of
development as involving four phases, we will use only
three stages. Porter’s fourth stage of development, which
he calls the Wealth-Driven stage, leads to a decline in
standards of living.The economy is driven by alreadyaccumulated wealth, which shifts incentives away from
efficient investment and innovation. Since we do not
observe declining growth rates for economies with the
highest levels of per capita GDP, we do not include this
fourth stage in our analysis. Another difference is that the
exact elements that are important at each stage are not the
same. A third difference is the way Porter sees the second
stage as driven by the ability and willingness to invest,
while we see it as being driven by efficiency. A fourth
difference is in the way countries are classified.18 But the
most important difference is in the exact translation of
the concepts to a measurable index.19
In the most basic stage, called the factor-driven stage,
firms compete in price.That is, they take advantage of
their cheap factors (including low-cost labor and cheap
unprocessed natural resources). In this phase, firms produce
commodities and simple products originally invented and
designed in other countries. In order to be competitive at
this initial stage, an economy must satisfy some basic
requirements. Chief among them are good institutions,
sufficient infrastructures, basic human capital, macroeconomic stability, and overall personal security. An important
point is that being successful in this stage eventually means
losing competitiveness unless economies prepare for the
next stage.The reason is that successful economies experience positive growth rates, and this means growing wage
rates. For a country whose source of competitiveness is the
low price of its labor, a growing salary implies a loss of
competitiveness.
In the second stage, which we call the efficiency-driven
stage, efficient production practices become the main
source of competitiveness.The quality of an economy’s
products (not only its prices) and the effectiveness of the
production processes determine the productivity of firms
in this phase.To achieve this, nations need to improve the
efficiency of their goods markets, labor markets, and financial markets.They also need to have an improved education and training system and to have access to the best
technologies (even if they need to import them from
abroad). Because competitiveness at this level is founded
on efficiency, access to larger markets allows business to
exploit economies of scale.20
Finally, in the third stage, which we call innovationdriven stage, successful economies can no longer compete
in price or even quality because their own success has
increased prices (especially wages) so much that they can
no longer compete by producing the same goods. It is
time for these economies to produce “different” goods,
innovative products and practices using the most advanced
methods of production and organization. In this phase,
businesses need to increase their sophistication by organizing in clusters and by opting for advanced and superior
operations. Firms compete with unique strategies.
Institutions and incentives supporting innovation become
the central part of economic competitiveness.
Of course, each of the 12 pillars of competitiveness
outlined in the previous section matter for every one of
the stages of development. But different factors matter differently for countries in different stages. For example,
although the ability to innovate matters for all nations, it is
undoubtedly more important for advanced countries than
for economies in the early stages of development.We,
therefore, implement the idea of “stages of development”
by giving different weights to each of the 12 pillars in
each of the three stages.To this end, we group the pillars
that we think are more important in the factor-driven
stage into what we call basic requirements. Basic requirements include institutions (1st pillar), physical infrastructures (2nd pillar), basic human capital (first part of the 5th
pillar), macroeconomic stability (3rd pillar), and personal
security (4th pillar).
We group the pillars that are more important in the
efficiency-driven stage into what we call efficiency enhancers.
The efficiency enhancers include goods market efficiency
(6th pillar), labor market efficiency (7th pillar), financial
market efficiency (8th pillar), advanced human capital
(second part of the 5th pillar), technological readiness (9th
pillar), and openness/market size (10th pillar).
Finally, we group the pillars that are more important
in the innovation-driven stage into what we call innovation
and sophistication factors, which includes business sophistication and innovation, our 11th and 12th pillars respectively.
An important practical advantage of framing the
process of economic development in stages is that it helps
countries prioritize the areas in which they should focus
their attention. By giving more weight to some pillars than
to others, the analysis presented in this chapter can be used
as a tool for countries to pay attention to the pillars that are
more important for their stage of development. Countries
in stage 1 that score low in innovation or in business
sophistication should not worry too much. Countries in
stage 2 that are fast approaching stage 3, on the other hand,
should worry about not doing well in these areas.
The allocation of pillars to each of the three groups is
summarized in Figure 1.
1.3: The Global Competitiveness Index
Figure 1: The twelve pillars of competitiveness
The Twelve Pillars of Competitiveness
Efficiency Enhancers
Key for Efficiency-Driven
Economies
1.
2.
3.
4.
5a.
Institutions
Infrastructures
Macroeconomic Stability
Personal Security
Basic Human Capital
5b.
6.
7.
8.
9.
10.
Advanced Human Capital
Good Market Efficiency
Labor Market Efficiency
Financial Market Efficiency
Technological Readiness
Openness/Market Size
11. Business Sophistication
12. Innovation
Basic Requirements
Key for Factor-Driven
Economies
Innovation and
Sophistication Factors
Key for Innovation-Driven
Economies
Once the three basic groups are defined, the index of
competitiveness is constructed as a weighted average of
the three groups. In other words,
GCI =
␣1 x basic requirements
+ ␣2 x efficiency enhancers
+ ␣3 x innovation factors
Table 1: Weights of the three main groups of pillars at
each stage of development
Weights (␣’s)
(Eq 1)
where ␣1, ␣2, and ␣3 are the weights that each subindex
gets in the overall index.21
The idea behind the concept of stages of development is that all components matter in all stages, but some
matter more than others in different stages. In other
words, the weights (the ␣’s) that each subindex gets in the
overall GCI depend on the stage of a particular country.
The exact weights of each of the three groups are displayed in Table 1. In the factor-driven stage, the basic
requirements have 50 percent, the efficiency enhancers
have a weight of 40 percent, and the innovation and
sophistication factors have small weight of 10 percent.
Factor-Driven Stage
Efficiency-Driven Stage
Innovation-Driven Stage
Basic
Requirements
Efficiency
Enhancers
Innovation and
Sophistication
Factors
50 percent
40 percent
30 percent
40 percent
50 percent
40 percent
10 percent
10 percent
30 percent
In the efficiency-driven stage, the weights of the basic
requirements and the efficiency enhancers are reversed
(that is, 40 percent and 50 percent respectively), while the
weight of the innovation and sophistication factors
remains at 10 percent.
Finally, in the innovation-driven stage, the weight of
the basic requirements falls to 30 percent, the weight of
the efficiency enhancers goes back to 40 percent while
that of the innovation and sophistication factors increases
to 30 percent.22
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1.3: The Global Competitiveness Index
Principle 3. Transitions
The third principle on which the new GCI index is
founded is that, as economies develop, they move from
one stage to the next in a smooth fashion rather than in
abrupt jumps.23 Thus, the weights of each of the subindexes (the ␣’s in equation 1), change smoothly as a country
develops.This means that we have five groups of countries:
the three groups that belong to the three stages described
above, plus the countries that are moving from stage 1 to
stage 2 plus those that are moving from stage 2 to 3.
In practice, the allocation of countries to each group
is done as follows:
1.
A country belongs to the factor-driven stage (stage 1)
if its GDP per capita is below US$2,000 or the fraction of its exports in the form of primary goods is
above 70 percent.24 A total of 41 countries are in this
stage (see Table 2 for a list of countries).
2.
A country with a per capita income between
US$3,000 and $9,000 that does not export more than
70 percent in primary goods belongs to the second
stage. A total of 21 countries are in this stage.
3.
A country with more than US$17,000 per capita
income and less than 70 percent of the exports in
primary goods belongs to the third stage. A total of
24 countries are in this stage.
4.
Countries with income per capita between US$2,000
and $3,000 are said to be in transition from stage 1 to
stage 2.The shares of basic requirements for these
countries decline continuously from 50 percent to 40
percent and the share of efficiency enhancers continuously increase from 40 percent to 50 percent as the
level of income increases from $2,000 to $3,000.
Notice that, because the share of the innovation factors is 10 percent in both stage 1 and stage 2,
economies in transition between these two stages do
not suffer changes in the share of innovation factors.
The precise formula for the change in these shares is
given in the next section.25 A total of 10 countries are
in this transitional phase.
5.
Countries with income per capita between US$9,000
and $17,000 are said to be in transition between
stages 2 and 3. For these countries, the shares of basic
requirements continuously decline from 40 percent to
30 percent, the share of efficiency enhancers declines
from 50 percent to 40 percent and the share of innovation factors increases from 10 percent to 30 percent. A total of 8 countries move along this transition.
58
The list of countries in each stage is given in Table 2.
The stages of development theory suggests that the
three basic subindexes get different weights for countries
at different stages of development. For example, the basic
requirements get a 50 percent weight for countries that
are unambiguously in stage 1 and a 40 percent for countries that are in stage two. For countries in between, the
weight smoothly declines from 50 percent to 40 percent
as their level of income increases. Similarly, for countries
in the third stage of development, the basic requirements
subindex weight is 30 percent.Thus, for countries that
move along the transition between the second and third
stages, the weight of this subindex smoothly declines from
40 percent to 30 percent.The relation between the weight
of the basic factors and the level of development is depicted in Figure 2.
Similarly, the weights of the efficiency enhancers
component gets a 40 percent weight for countries in stage
1, a 50 percent weight for countries in stage 2, and
smoothly increases from 40 percent to 50 percent as the
country grows between these two stages.The weight then
smoothly declines back to 40 percent as countries move
between stages 2 and 3.The evolution of the importance
of efficiency factors as the economy develops is depicted
in Figure 3.
Finally, the weight of the innovation factors remains
constant at 10 percent between stages 1 and 2, and it then
smoothly increases to 30 percent as countries move
between stages 2 and 3.The evolution of the weight of
innovation factors in the overall global competitiveness
index is depicted in Figure 4.
One advantage of allowing for the weights of each
subcomponent to change smoothly along the transition is
that countries that do not prepare for more advanced
phases of development as they grow out of stage 1 into
stage 2 get penalized.We think that countries that do not
adapt their economic environments to the new stages tend
to lose competitiveness.The reason is that wages tend to
increase in economies that grow.Thus, countries that grow
from the factor-driven stage to the efficiency-driven stage
tend to lose their ability to compete in prices and low
costs. In other words, as economies in stage 1 grow, they
slowly lose their competitiveness. A good index of competitiveness, therefore, must capture this phenomenon and
must therefore partly penalize economies that, while
approaching stage 2, do not prepare for the challenges
involved in this more sophisticated phase of economic
development. Our index has this property because, for
countries that do not adapt to the more advanced phases,
the values of the efficiency enhancers tend to be lower
than the values of the basic requirements. By smoothly
reducing the weights of the basic requirements and
increasing those of the efficiency enhancers, we tend to
lower the overall value of the index for those countries as
their economy grows.
We do a similar thing for economies that move along
the transition from stage 2 to stage 3.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Stage 1
Transition from 1 to 2
Stage 2
Transition from 2 to 3
Stage 3
Income of less than US$2,000
or more than 70% primary exports
Income between
US$2,000 and $3,000
Income of more than US$3,000
and less than $9,000
Income between
US$9,000 and $17,000
Income of more
than US$17,000
Algeria**
Angola*
Bahrain**
Bangladesh
Bolivia
Bosnia and Hercegovina
Chad*
China
Colombia
Dominican Republic
Egypt
Ethiopia
Gambia
Georgia
Ghana
Guatemala
Honduras
India
Indonesia
Jordan
Kenya
Madagascar
Malawi
Mali*
Morocco
Mozambique
Namibia
Nicaragua
Nigeria*
Pakistan
Paraguay
Philippines
Serbia and Montenegro
Sri Lanka
Tanzania
Uganda
Ukraine
Venezuela**
Vietnam
Zambia
Zimbabwe
Brazil
Bulgaria
Ecuador
El Salvador
Jamaica
Macedonia
Peru
Romania
Thailand
Tunisia
Argentina
Botswana
Chile
Costa Rica
Croatia
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Malaysia
Mauritius
Mexico
Panama
Poland
Russian Federation
Slovak Republic
South Africa
Trinidad and Tobago
Turkey
Uruguay
Cyprus
Greece
Israel
Korea
Malta
Portugal
Slovenia
Taiwan
Australia
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Hong Kong SAR
Iceland
Ireland
Italy
Japan
Luxembourg
Netherlands
New Zealand
Norway
Singapore
Spain
Sweden
Switzerland
United Arab Emirates
United Kingdom
United States
* Countries that satisfy both requirements for being in stage 1.
** Countries with income per capita above US$2,000 but with primary exports as a fraction of total exports higher than 70 percent.
1.3: The Global Competitiveness Index
Table 2: List of countries in each stage
59
Weight of basic requirements (␣1)
1.3: The Global Competitiveness Index
Figure 2: The importance of basic requirements at various stages of development
50%
40%
30%
Stage 1
Transition
from 1 to 2
$2,000
Transition
from 2 to 3
Stage 2
$3,000
$9,000
Stage 3
$17,000
Income per capita (not to scale)
Figure 3: The importance of efficiency enhancers at various stages of development
Weight of efficiency enhancers (␣2)
60
50%
40%
30%
Stage 1
Transition
from 1 to 2
$2,000
$3,000
Transition
from 2 to 3
Stage 2
$9,000
Income per capita (not to scale)
Stage 3
$17,000
1.3: The Global Competitiveness Index
Weight of innovation factors (␣3)
Figure 4: The importance of innovation factors at various stages of development
30%
20%
10%
Stage 1
Transition
from 1 to 2
$2,000
Transition
from 2 to 3
Stage 2
$3,000
$9,000
Stage 3
$17,000
Income per capita (not to scale)
Summary of the methodology: Building the Global
Competitiveness Index
Step 1: Construct the twelve pillars
Following the tradition of both our predecessors (the
Growth Competitive Index and the Business Competitive
Index), our index combines hard data and Survey data
collected by the World Economic Forum through its
Executive Opinion Survey.
These data are combined to estimate the 12 pillars of
economic development described in Section 1.The exact
allocation of Survey questions and hard data to each of the
pillars is described in Appendix 1. All questions get the
same weight within subsections of the pillar.26
Step 2: Build the three subindexes
Each pillar is allocated to a subindex as follows:
Subindex 1: Basic Requirements:
1st Pillar: Institutions
2nd Pillar: Infrastructures
3rd Pillar: Macroeconomic Stability
4th Pillar: Security
5th Pillar: Basic Human Capital
Subindex 2: Efficiency Enhancers:
5th Pillar: Advanced Human Capital
6th Pillar: Goods Market Efficiency
7th Pillar: Labor Market Efficiency
8th Pillar: Financial Market Efficiency
9th Pillar:Technological Readiness
10th Pillar: Openness and Market Size
Subindex 3: Innovation Factors:
11th Pillar: Business Sophistication
12th Pillar: Innovation
Step 3: Allocate countries to stages of development
We then allocate each of the 104 countries to one of the
three stages of development (or the transitional stages) as
described in Section 3.The results are displayed in Table 2.
Step 4: Estimate the shares that each subindex gets for each
country
Once a country is assigned to a stage of development, we
assign the weights that each of the three subindexes gets
for each country. Remember that the theory of stages of
development suggests that, for less advanced economies,
the basic requirements are more important; for intermediate economies, the efficiency enhancers are key; and for
advanced countries, the innovation factors are central.The
exact weights are depicted in Table 1.
61
1.3: The Global Competitiveness Index
62
Step 5: Estimate the Global Competitiveness Index
The Global Competitive Index is then estimated as the
weighted average of the three subindexes (see Equation 1).
How to interpret the Index
When observing the index, some analysts might be puzzled by the low value of the Global Competitive Index for
countries that have experienced high growth rates in the
past, or the high values obtained by countries with poor
recent economic growth performances.
First of all, we should remember that the Index is not
meant to capture anything to do with short-term business
cycles. In other words, highly competitive economies are
as subject to short-term booms and recessions as noncompetitive ones. Having experienced high or low growth rates
in the recent past has little to do with the competitiveness
of a nation because competitiveness is not a vaccine
against business cycles.This is rightly captured by our
Index.
Second, and perhaps more importantly, low current
competitiveness is consistent with elevated growth rates in
the past because the process of economic growth is determined both by the level of productivity and by the “convergence” components of a country. Convergence growth is
the growth that economies experience as various types of
investment react to changes in the medium- to long-term
economic environment. As an example, imagine that a
country, which in 1980 had very low levels of productivity
and efficiency, increased those levels dramatically between
1980 and 2004.The new levels of competitiveness may
still not be the best in the world, but they are much larger
than they were 24 years ago. Under those circumstances,
we expect the growth rate of this country to have been
very large over the last 24 years, yet our index will probably give this nation a middle ranking in the world.
Similarly, a country with a high level of productivity may
have experienced very low growth rates of GDP per capita over a period of 20 years if this level of competitiveness
has not improved much in the past.
In other words, the values of the Global
Competitiveness Index should not necessarily be correlated with the past growth performance of a country.
Changes in the value of the index over the medium to
long term, on the other hand, should be correlated with
the rate of economic growth.
Results
Table 3 displays the results of computing the Global
Competitiveness Index for 2004.The countries are ranked
in decreasing order.The second column contains the value
of the index and the third column the rank number.The
following six columns contain the information (value and
rank) for each of the three subindexes: the basic requirements subindex, the efficiency enhancers subindex, and
the innovation factors subindex respectively.The next
three tables decompose the index into its 12 pillars.
The most competitive country in the world is the
United States, with an overall score of 5.21, followed by
Finland (5.04), and Denmark (4.95), Switzerland (4.93),
and Sweden (4.92), which conclude the top five.The
United States does not score particularly well in basic
requirements (rank 18: the main cause is its dismal macroeconomic stability—rank 83—and its not-so-great performance in security—rank 37), but it is the world’s leader
in both efficiency enhancers and innovation factors. Since
the United States is in the third stage of development (the
innovation stage), the weight of the basic requirements is
relatively minor, so the other two subindexes put this
country in the leading position. Finland leads the world in
basic requirements, but it only ranks 6th in efficiency
enhancers (it is interesting to notice its 18th place in labor
market efficiency) and 4th in innovation factors. Denmark
is 2nd, 5th, and 8th respectively.
The next five are Germany (4.86), Singapore (4.85),
Hong Kong (4.81), United Kingdom (4.80), and Japan
(4.79). Of particular interest is the extremely low score of
Germany in labor market efficiency (82nd in the world).
Sweden is ranked quite low in that same pillar (25th),
which is led by Hong Kong (1st) and Singapore (2nd).
At the other end of the spectrum, the least competitive
country in the world is Angola (2.55), closely followed
by Chad (2.64). Angola ranks 104th in basic requirements
and innovation factors and 103rd in efficiency enhancers.
Chad’s scores are 103rd and 104th respectively. The rest
of the bottom five are also African countries: Ethiopia
(102nd with 2.88), Zimbabwe (101st with 2.96), and
Mozambique (100th with 2.98).These countries score
dismally almost across the board in the pillars that are
most important for their level of development (the exception is the relatively good macroeconomic performance
experienced by Mozambique—rank 42nd in the world).
The next five countries at the bottom of the competitiveness rankings are not all African, and they include two
European countries: the former republics of Yugoslavia
Bosnia-Hercegovina (3.13) and Serbia-Montenegro (3.16),
two African countries Mali (3.13) and Tanzania (3.14), and
one Latin American, Bolivia (3.19).
Averaging out the value of the index by region (see
Figure 5), we see that the most competitive region in the
world is North America.The values of the second and
third regions (Western Europe and East Asia) are quite
close to each other.The fourth position is for the Middle
East and North Africa.The next three regions (Eastern
Europe, South and Central America, and South and
Central Asia respectively) are also quite close. Sub-Saharan
Africa closes the ranking in the last position.
1.3: The Global Competitiveness Index
Figure 5: Global competitiveness by region
5.0
4.8
4.6
4.4
Score
4.2
4.0
3.8
3.6
3.4
3.2
3.0
North
America
Western
Europe
East AsiaPacific
MENA*
Eastern Europe
Central and
South America
South-Central
Asia
Sub-Saharan
Africa
* Middle East and North Africa
63
1.3: The Global Competitiveness Index
64
Table 3: The Global Competitiveness Index
Three main components
Overall Index
Country
United States
Finland
Denmark
Switzerland
Sweden
Germany
Singapore
Hong Kong SAR
United Kingdom
Japan
Taiwan
Netherlands
Iceland
Norway
Canada
Australia
France
Austria
Belgium
New Zealand
Luxembourg
Israel
Malaysia
Estonia
Bahrain
Korea
Ireland
Jordan
Chile
Tunisia
United Arab Emirates
China
Thailand
Spain
Slovenia
South Africa
India
Czech Republic
Lithuania
Portugal
Slovak Republic
Malta
Namibia
Latvia
Morocco
Hungary
Egypt
Indonesia
Brazil
Mauritius
Greece
Cyprus
Costa Rica
Panama
El Salvador
Italy
Romania
Botswana
Dominican Republic
Mexico
Vietnam
Algeria
Trinidad and Tobago
Russian Federation
BASIC REQUIREMENTS
EFFICIENCY ENHANCERS
INNOVATION FACTORS
Score
Rank
Score
Rank
Score
Rank
Score
Rank
5.21
5.04
4.95
4.93
4.92
4.86
4.85
4.81
4.80
4.79
4.72
4.72
4.70
4.69
4.66
4.63
4.60
4.57
4.54
4.54
4.52
4.48
4.47
4.46
4.39
4.38
4.38
4.32
4.29
4.25
4.21
4.20
4.17
4.10
4.09
4.08
4.07
4.06
4.06
4.05
4.03
4.01
3.98
3.97
3.97
3.96
3.95
3.92
3.88
3.86
3.84
3.83
3.83
3.81
3.80
3.80
3.75
3.75
3.71
3.70
3.68
3.68
3.68
3.67
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
5.50
6.03
5.99
5.88
5.76
5.75
5.89
5.95
5.48
5.35
5.31
5.59
5.80
5.96
5.58
5.70
5.49
5.61
5.51
5.60
5.76
5.06
5.36
5.31
5.20
5.30
5.23
5.25
5.20
5.17
5.55
4.85
4.90
5.08
5.13
4.76
4.53
4.83
4.80
5.21
4.78
5.01
4.80
4.86
4.70
4.75
4.67
4.56
4.39
4.86
4.94
5.02
4.57
4.65
4.51
4.56
4.48
4.62
4.42
4.47
4.48
4.71
4.50
4.42
18
1
2
6
8
10
5
4
20
22
23
14
7
3
15
11
19
12
17
13
9
34
21
24
29
25
27
26
30
31
16
41
38
33
32
46
56
42
43
28
45
36
44
40
49
47
50
55
67
39
37
35
53
51
58
54
61
52
64
62
60
48
59
65
5.02
4.54
4.55
4.45
4.45
4.27
4.60
4.65
4.61
4.26
4.38
4.36
4.42
4.25
4.30
4.28
4.15
4.13
4.12
4.25
4.16
4.18
3.91
4.03
3.71
3.87
4.11
3.49
3.76
3.55
3.81
3.59
3.57
3.79
3.63
3.63
3.60
3.60
3.61
3.64
3.61
3.52
3.24
3.47
3.27
3.51
3.23
3.28
3.51
3.24
3.47
3.53
3.36
3.32
3.21
3.48
3.19
3.25
3.07
3.21
2.95
2.70
3.16
3.18
1
6
5
8
7
14
4
2
3
15
10
11
9
16
12
13
20
21
22
17
19
18
25
24
30
26
23
45
29
40
27
38
39
28
32
33
37
36
34
31
35
42
56
47
53
44
57
52
43
55
48
41
49
51
59
46
60
54
69
58
79
92
62
61
5.18
4.70
4.42
4.61
4.69
4.74
4.15
3.90
4.38
4.94
4.44
4.32
3.97
4.01
4.23
4.04
4.30
4.11
4.14
3.87
3.75
4.28
3.69
3.26
3.01
3.87
3.88
3.04
3.27
3.32
3.40
3.43
3.31
3.53
3.41
3.60
3.69
3.35
3.30
3.20
3.16
2.78
2.83
2.93
3.14
3.08
3.18
3.27
3.55
2.98
3.13
2.93
3.18
2.89
2.69
3.48
2.88
2.79
2.70
3.02
2.63
2.50
2.96
3.14
1
4
8
6
5
3
14
20
9
2
7
10
19
18
13
17
11
16
15
23
24
12
26
40
55
22
21
51
38
35
33
31
36
29
32
27
25
34
37
41
44
74
68
63
45
48
43
39
28
59
47
62
42
64
80
30
65
73
79
54
87
91
60
46
(cont’d)
Three main components
Overall Index
Country
Jamaica
Sri Lanka
Turkey
Ghana
Colombia
Bulgaria
Uruguay
Poland
Ukraine
Philippines
Argentina
Peru
Nigeria
Uganda
Croatia
Venezuela
Gambia
Macedonia, FYR
Guatemala
Kenya
Madagascar
Georgia
Pakistan
Ecuador
Honduras
Paraguay
Zambia
Nicaragua
Malawi
Bangladesh
Bolivia
Serbia and Montenegro
Tanzania
Bosnia and Hercegovina
Mali
Mozambique
Zimbabwe
Ethiopia
Chad
Angola
BASIC REQUIREMENTS
EFFICIENCY ENHANCERS
INNOVATION FACTORS
Score
Rank
Score
Rank
Score
Rank
Score
Rank
3.66
3.65
3.62
3.62
3.61
3.60
3.57
3.57
3.55
3.55
3.54
3.53
3.53
3.50
3.46
3.45
3.45
3.40
3.37
3.37
3.36
3.35
3.35
3.34
3.29
3.26
3.25
3.24
3.22
3.20
3.19
3.16
3.14
3.13
3.13
2.98
2.96
2.88
2.64
2.55
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
4.23
4.31
4.41
4.18
4.15
4.24
4.52
4.25
4.18
4.03
4.44
4.19
4.08
4.02
4.21
4.16
3.94
4.08
4.02
3.72
3.97
3.94
3.78
4.18
4.13
3.99
3.61
3.98
3.70
3.81
3.90
3.55
3.47
3.66
3.60
3.53
3.41
3.42
3.09
2.92
71
68
66
75
78
70
57
69
74
82
63
73
80
83
72
77
89
81
84
93
87
88
92
76
79
85
96
86
94
91
90
98
100
95
97
99
102
101
103
104
3.33
3.03
3.10
3.11
3.10
3.08
2.98
3.13
2.90
3.11
2.96
3.00
2.97
3.01
3.00
2.77
3.01
2.83
2.75
3.01
2.76
2.85
2.91
2.55
2.49
2.60
2.93
2.58
2.80
2.63
2.55
2.80
2.84
2.67
2.70
2.48
2.48
2.35
2.23
2.26
50
70
66
65
67
68
76
63
82
64
78
74
77
73
75
88
72
85
90
71
89
83
81
98
99
95
80
96
87
94
97
86
84
93
91
101
100
102
104
103
3.00
2.81
3.08
2.82
3.00
2.68
2.66
2.99
3.03
2.84
2.81
2.64
3.07
2.87
2.80
2.64
2.77
2.57
2.60
3.03
2.71
2.36
2.94
2.44
2.30
2.25
2.76
2.16
2.57
2.41
2.18
2.64
2.73
2.35
2.48
2.26
2.65
2.23
2.04
1.88
56
71
49
69
57
81
82
58
53
67
70
85
50
66
72
86
75
89
88
52
78
95
61
93
97
99
76
102
90
94
101
84
77
96
92
98
83
100
103
104
1.3: The Global Competitiveness Index
Table 3: The Global Competitiveness Index (cont’d.)
65
1.3: The Global Competitiveness Index
66
Table 4: Global Competitiveness Index: Basic requirements
Country
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
United States
Finland
Denmark
Switzerland
Sweden
Germany
Singapore
Hong Kong SAR
United Kingdom
Japan
Taiwan
Netherlands
Iceland
Norway
Canada
Australia
France
Austria
Belgium
New Zealand
Luxembourg
Israel
Malaysia
Estonia
Bahrain
Korea
Ireland
Jordan
Chile
Tunisia
United Arab Emirates
China
Thailand
Spain
Slovenia
South Africa
India
Czech Republic
Lithuania
Portugal
Slovak Republic
Malta
Namibia
Latvia
Morocco
Hungary
Egypt
Indonesia
Brazil
Mauritius
Greece
Cyprus
Costa Rica
Panama
El Salvador
Italy
Romania
Botswana
Dominican Republic
Mexico
Vietnam
Algeria
Trinidad and Tobago
Russian Federation
1. Institutions
2. Physical
infrastructures
Score
Rank
Score
Rank
Score
Rank
Score
Rank
Score
Rank
5.22
5.50
5.37
5.16
5.13
5.15
5.53
5.18
5.43
4.73
4.65
5.18
5.45
5.13
5.05
5.26
4.60
4.99
4.62
5.31
4.98
4.53
4.74
4.50
4.60
3.87
4.78
4.48
4.53
4.61
4.69
3.91
4.01
4.10
3.97
4.59
3.92
3.44
3.89
4.16
3.75
4.24
4.46
3.57
4.08
3.80
3.97
3.87
3.80
3.80
3.94
4.19
3.96
3.51
3.90
3.38
3.24
4.15
3.13
3.50
3.67
3.50
3.62
2.99
8
2
5
11
13
12
1
9
4
20
22
10
3
14
15
7
26
16
23
6
17
28
19
30
25
50
18
31
29
24
21
47
41
39
43
27
46
72
49
36
56
33
32
65
40
54
42
51
55
53
45
35
44
68
48
77
80
38
84
69
61
70
64
93
6.12
6.28
6.61
6.43
6.16
6.44
6.34
6.48
5.45
6.12
5.36
6.02
5.77
5.85
5.87
5.83
6.37
5.72
6.09
4.96
5.85
4.87
5.30
4.74
4.76
5.19
4.11
4.33
4.62
4.34
5.52
3.49
4.30
4.80
4.55
4.87
3.35
4.66
4.17
4.68
3.86
3.86
5.04
4.02
3.74
3.75
3.84
3.93
3.53
4.17
4.33
4.78
3.14
3.94
3.86
3.87
3.31
3.81
3.15
3.39
2.45
3.20
3.60
3.59
9
7
1
4
8
3
6
2
20
10
21
12
17
15
13
16
5
18
11
25
14
26
22
31
30
23
42
37
34
36
19
60
39
28
35
27
63
33
40
32
48
47
24
43
53
52
50
45
58
41
38
29
70
44
49
46
64
51
69
62
91
67
55
56
4.79
5.71
5.55
5.52
5.43
5.02
5.79
5.75
5.10
4.60
5.47
5.31
5.19
6.41
5.41
5.49
5.04
5.32
5.22
5.53
5.81
4.64
5.53
5.77
5.22
6.06
5.54
5.43
5.59
5.29
5.53
6.06
5.74
5.48
5.49
5.21
4.68
5.14
5.29
5.14
5.24
4.83
5.25
5.64
5.04
4.97
4.81
5.08
4.32
5.36
4.95
4.85
4.84
5.09
4.96
4.86
5.15
5.67
5.10
5.31
5.48
6.31
5.58
5.72
83
12
17
22
31
65
6
9
54
90
29
35
47
1
32
23
62
34
44
21
5
89
19
7
43
4
18
30
15
37
20
3
10
27
24
45
87
51
38
52
41
77
40
14
60
68
81
58
96
33
70
75
76
57
69
74
50
13
56
36
26
2
16
11
4.44
5.74
5.52
5.34
5.13
5.19
5.29
5.38
4.56
4.33
4.54
4.49
5.64
5.47
4.61
4.95
4.51
5.08
4.66
5.23
5.23
4.32
4.59
4.73
4.63
4.54
4.84
5.22
4.39
4.85
5.27
4.14
4.15
4.08
4.71
3.41
4.33
4.00
3.87
5.19
4.19
5.20
3.77
4.31
4.48
4.38
4.10
3.49
3.65
4.19
4.65
4.58
4.04
3.91
3.11
3.74
4.07
4.38
4.11
3.40
4.20
3.90
2.94
3.14
37
1
3
6
15
13
7
5
30
42
31
34
2
4
26
17
33
16
23
9
10
44
27
20
25
32
19
11
39
18
8
53
52
56
22
82
43
59
65
14
49
12
69
45
35
40
55
80
75
48
24
29
58
62
92
70
57
40
54
83
47
63
96
90
6.91
6.94
6.92
6.97
6.98
6.94
6.49
6.93
6.86
6.99
6.52
6.94
6.97
6.95
6.96
6.96
6.96
6.95
6.94
6.94
6.94
6.95
6.63
6.80
6.81
6.86
6.92
6.76
6.88
6.76
6.74
6.64
6.28
6.95
6.91
5.73
6.35
6.90
6.80
6.90
6.86
6.94
5.50
6.75
6.16
6.83
6.62
6.42
6.64
6.78
6.85
6.68
6.90
6.80
6.70
6.96
6.62
5.06
6.60
6.77
6.58
6.62
6.75
6.64
23
18
21
4
2
13
74
20
31
1
72
15
3
9
6
5
8
10
16
17
14
11
62
41
36
29
22
47
28
46
50
60
80
12
24
86
79
26
37
25
30
19
88
49
81
35
65
75
61
44
33
55
27
40
54
7
64
90
68
45
70
63
48
59
3. Macro stability
5. Basic
human capital
4. Security
(cont’d)
Country
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
Jamaica
Sri Lanka
Turkey
Ghana
Colombia
Bulgaria
Uruguay
Poland
Ukraine
Philippines
Argentina
Peru
Nigeria
Uganda
Croatia
Venezuela
Gambia
Macedonia, FYR
Guatemala
Kenya
Madagascar
Georgia
Pakistan
Ecuador
Honduras
Paraguay
Zambia
Nicaragua
Malawi
Bangladesh
Bolivia
Serbia and Montenegro
Tanzania
Bosnia and Hercegovina
Mali
Mozambique
Zimbabwe
Ethiopia
Chad
Angola
1. Institutions
2. Physical
infrastructures
Score
Rank
Score
Rank
Score
Rank
Score
Rank
Score
Rank
3.72
3.70
3.48
4.20
3.54
3.07
3.74
3.17
2.75
3.39
3.15
3.23
3.32
3.56
3.10
2.89
4.15
3.04
3.03
3.64
3.25
3.03
2.96
2.91
3.01
2.69
3.67
3.08
3.84
2.80
2.74
3.07
3.44
2.95
3.68
2.95
3.39
3.42
2.69
2.47
58
59
71
34
67
88
57
82
100
75
83
81
78
66
85
98
37
89
90
63
79
91
94
97
92
103
62
86
52
99
101
87
73
96
60
95
76
74
102
104
3.55
2.79
3.21
2.88
3.06
3.18
3.63
3.07
3.48
2.55
3.52
2.72
2.35
2.47
3.30
3.08
2.90
2.83
2.64
2.42
2.33
2.47
2.81
2.60
2.83
2.23
2.68
2.19
2.55
2.31
2.17
2.46
2.63
2.18
2.16
2.14
2.80
2.22
1.36
1.73
57
80
66
75
73
68
54
72
61
87
59
81
93
88
65
71
74
77
83
92
94
89
78
85
76
96
82
98
86
95
100
90
84
99
101
102
79
97
104
103
4.35
4.66
4.54
4.75
4.98
5.18
3.95
5.07
5.49
5.04
5.26
5.10
5.76
4.82
4.90
5.02
3.70
5.10
5.16
4.74
4.53
4.57
5.03
5.47
5.01
4.83
4.72
4.07
3.38
5.20
4.54
4.07
4.82
4.80
4.87
5.23
2.45
4.23
4.91
3.52
95
88
92
84
67
48
100
59
25
61
39
55
8
79
72
64
101
53
49
85
94
91
63
28
66
78
86
99
103
46
93
98
80
82
73
42
104
97
71
102
2.72
3.66
4.18
4.73
2.43
3.00
4.43
3.07
3.28
2.67
3.50
3.34
3.32
3.42
3.82
3.02
4.45
2.69
2.70
2.56
3.71
3.29
3.78
3.30
3.21
3.53
4.16
3.90
3.92
2.37
3.70
3.93
3.70
3.57
4.58
3.14
3.87
4.28
2.93
3.55
98
74
50
21
103
95
38
93
88
101
79
84
85
81
67
94
36
100
99
102
71
87
68
86
89
78
51
64
61
104
72
60
73
76
28
91
66
46
97
77
6.79
6.73
6.66
4.32
6.73
6.79
6.85
6.86
5.92
6.51
6.80
6.59
5.65
5.83
5.94
6.80
4.48
6.71
6.56
5.23
6.04
6.36
4.31
6.60
6.61
6.68
2.80
6.66
4.79
6.35
6.37
4.19
2.78
4.80
2.72
4.20
4.53
2.96
3.58
3.35
43
51
57
95
52
42
34
32
84
73
38
69
87
85
83
39
94
53
71
89
82
77
96
67
66
56
102
58
92
78
76
98
103
91
104
97
93
101
99
100
3. Macro stability
4. Security
5. Basic
human capital
1.3: The Global Competitiveness Index
Table 4: Global Competitiveness Index: Basic requirements (cont’d.)
67
1.3: The Global Competitiveness Index
68
Table 5: Global Competitiveness Index: Efficiency enhancers
5. Advanced
human capital
Country
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
United States
Finland
Denmark
Switzerland
Sweden
Germany
Singapore
Hong Kong SAR
United Kingdom
Japan
Taiwan
Netherlands
Iceland
Norway
Canada
Australia
France
Austria
Belgium
New Zealand
Luxembourg
Israel
Malaysia
Estonia
Bahrain
Korea
Ireland
Jordan
Chile
Tunisia
United Arab Emirates
China
Thailand
Spain
Slovenia
South Africa
India
Czech Republic
Lithuania
Portugal
Slovak Republic
Malta
Namibia
Latvia
Morocco
Hungary
Egypt
Indonesia
Brazil
Mauritius
Greece
Cyprus
Costa Rica
Panama
El Salvador
Italy
Romania
Botswana
Dominican Republic
Mexico
Vietnam
Algeria
Trinidad and Tobago
Russian Federation
6. Goods market
efficiency
7. Labor market
efficiency
8. Financial
market efficiency
Score
Rank
Score
Rank
Score
Rank
Score
5.01
5.36
5.06
4.95
5.10
4.62
4.81
4.24
4.72
4.75
4.96
4.84
4.73
4.79
4.83
4.89
4.82
4.81
4.88
4.66
3.89
4.51
3.90
4.34
3.56
4.49
4.50
3.68
3.70
3.97
3.52
3.23
3.65
4.30
4.35
3.57
3.67
4.00
4.12
3.78
3.90
3.73
2.84
4.00
3.14
3.96
3.44
3.27
3.61
3.19
4.04
3.69
3.52
3.09
2.80
3.85
3.68
3.03
2.78
3.14
2.85
2.77
3.17
3.75
4
1
3
6
2
19
12
26
17
15
5
9
16
14
10
7
11
13
8
18
35
20
34
24
51
22
21
43
41
31
53
61
46
25
23
50
45
30
27
38
33
40
78
29
67
32
56
60
48
63
28
42
54
69
79
36
44
71
80
66
77
81
65
39
4.59
4.29
4.33
4.36
4.14
4.22
4.80
4.90
4.53
4.02
4.50
4.35
4.27
4.11
4.32
4.38
4.06
4.19
3.97
4.49
4.39
3.88
4.18
4.12
4.14
3.92
4.25
3.72
3.92
3.89
4.38
3.58
3.87
3.72
3.72
3.99
3.67
3.43
3.51
3.65
3.63
3.44
3.59
3.33
3.64
3.40
3.42
3.74
3.48
3.58
3.50
3.86
3.38
3.20
3.25
3.30
3.04
3.50
3.04
3.05
3.32
3.02
3.34
3.22
3
14
12
10
21
17
2
1
4
25
5
11
15
23
13
8
24
18
27
6
7
31
19
22
20
28
16
37
29
30
9
43
32
36
35
26
38
50
45
39
41
49
42
58
40
52
51
34
48
44
46
33
56
71
66
61
77
47
79
76
59
80
57
70
5.05
4.33
4.64
4.79
4.13
3.51
5.11
5.37
4.67
4.35
4.72
4.11
4.91
4.43
4.48
4.19
3.57
3.81
3.81
4.33
4.46
4.17
4.56
4.55
4.32
3.47
4.00
3.99
4.12
4.11
4.77
3.98
4.48
3.64
3.70
3.77
3.78
4.12
3.88
3.86
4.23
3.66
3.91
4.03
4.12
3.92
3.91
3.66
3.82
3.46
3.57
3.79
4.11
3.82
3.98
3.14
3.73
4.20
4.09
3.69
4.08
3.57
3.82
4.03
3
18
9
5
25
82
2
1
8
16
7
31
4
15
13
23
78
56
57
17
14
24
10
11
19
85
37
38
26
32
6
40
12
75
66
61
60
27
46
47
20
72
45
36
28
43
44
74
52
87
77
58
29
54
39
102
65
22
33
69
34
76
53
35
5.93
5.88
5.88
5.59
5.77
5.25
5.61
6.00
6.27
4.43
4.89
5.77
5.27
5.48
5.61
5.76
5.43
5.14
5.33
5.77
5.84
5.43
4.93
5.23
5.22
4.13
5.71
4.65
5.32
4.42
4.68
3.77
4.30
5.05
4.16
5.29
4.85
4.16
4.86
5.17
4.63
4.69
4.76
4.47
4.32
4.55
3.97
4.28
4.76
4.53
4.67
4.49
4.63
5.08
4.76
4.08
4.07
4.50
4.06
4.39
3.72
3.32
4.56
3.61
Rank
3
4
5
14
8
22
12
2
1
52
30
9
21
15
13
10
17
26
18
7
6
16
29
23
24
67
11
40
19
53
38
82
59
28
65
20
32
66
31
25
42
36
34
49
58
44
72
60
33
45
39
47
41
27
35
68
69
46
70
56
85
100
43
91
9. Technological
readiness
10. Openess and
market size
Score
Rank
Score
Rank
5.32
5.34
5.31
4.86
5.50
5.09
5.22
5.27
5.03
5.16
5.10
4.86
5.66
5.06
4.69
4.92
4.60
4.86
4.59
4.71
4.52
5.04
4.13
4.59
3.72
5.06
4.34
3.48
4.08
3.47
4.02
3.24
3.48
4.12
4.22
3.71
3.44
4.27
3.78
3.95
3.87
4.11
3.07
3.69
2.91
3.73
3.15
2.99
3.69
3.18
3.56
3.87
2.94
3.40
3.04
4.11
3.24
2.94
3.19
3.25
2.46
2.31
2.84
2.81
4
3
5
17
2
10
7
6
14
8
9
16
1
12
20
15
21
18
22
19
24
13
28
23
39
11
25
45
32
47
33
54
46
29
27
40
48
26
37
34
36
30
60
41
67
38
58
64
42
57
44
35
66
49
61
31
53
65
56
52
88
94
72
73
4.20
2.05
2.12
2.15
2.06
2.93
2.02
2.16
2.47
2.82
2.12
2.21
1.67
1.64
1.88
1.54
2.44
1.99
2.15
1.52
1.83
2.05
1.74
1.34
1.30
2.16
1.86
1.43
1.40
1.46
1.51
3.74
1.65
1.88
1.65
1.44
2.16
1.60
1.48
1.47
1.38
1.48
1.26
1.31
1.48
1.49
1.51
1.75
1.69
1.49
1.47
1.49
1.59
1.34
1.42
2.38
1.40
1.29
1.28
1.74
1.28
1.18
1.24
1.66
1
18
15
12
16
3
19
10
5
4
14
8
29
33
21
37
6
20
13
39
24
17
26
65
68
9
23
56
59
51
41
2
32
22
31
54
11
34
47
50
61
46
76
67
48
43
40
25
28
45
49
44
35
66
58
7
60
71
75
27
74
92
82
30
(cont’d)
5. Advanced
human capital
Country
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
Jamaica
Sri Lanka
Turkey
Ghana
Colombia
Bulgaria
Uruguay
Poland
Ukraine
Philippines
Argentina
Peru
Nigeria
Uganda
Croatia
Venezuela
Gambia
Macedonia, FYR
Guatemala
Kenya
Madagascar
Georgia
Pakistan
Ecuador
Honduras
Paraguay
Zambia
Nicaragua
Malawi
Bangladesh
Bolivia
Serbia and Montenegro
Tanzania
Bosnia and Hercegovina
Mali
Mozambique
Zimbabwe
Ethiopia
Chad
Angola
6. Goods market
efficiency
7. Labor market
efficiency
8. Financial
market efficiency
Score
Rank
Score
Rank
Score
Rank
Score
3.21
2.87
3.18
2.71
3.08
3.63
3.49
3.83
3.55
3.37
3.57
3.03
2.73
2.51
3.39
2.88
2.54
3.31
2.33
2.76
2.26
3.01
2.18
2.53
2.05
2.37
2.54
2.40
2.37
2.21
2.71
3.12
2.20
2.88
2.11
1.99
2.74
1.98
1.62
1.57
62
76
64
86
70
47
55
37
52
58
49
72
84
90
57
75
87
59
94
82
95
73
98
89
100
93
88
91
92
96
85
68
97
74
99
101
83
102
103
104
3.27
3.30
3.26
3.39
3.18
3.23
3.04
2.90
2.88
3.19
2.90
2.92
3.28
3.39
2.92
2.62
3.39
2.82
2.81
3.24
2.94
2.57
3.27
2.47
2.54
2.87
3.11
2.41
2.93
2.97
2.55
2.97
3.25
2.89
3.09
2.66
2.68
2.59
2.33
2.30
63
60
65
54
73
69
78
87
90
72
88
85
62
53
86
96
55
92
93
68
83
98
64
101
100
91
74
102
84
81
99
82
67
89
75
95
94
97
103
104
3.96
3.51
3.68
3.95
3.66
3.66
3.48
3.23
3.78
3.74
3.30
3.57
3.83
3.86
3.41
3.39
4.11
3.69
3.48
3.76
3.85
4.21
3.23
3.22
3.33
3.31
3.82
3.55
3.69
3.42
3.09
3.75
3.84
3.37
3.46
3.28
2.75
3.45
3.30
3.36
41
81
70
42
73
71
84
99
59
64
97
79
51
48
90
91
30
68
83
62
49
21
100
101
94
95
55
80
67
89
103
63
50
92
86
98
104
88
96
93
4.47
4.41
3.68
4.69
4.40
3.75
3.83
3.99
3.25
3.84
3.68
4.47
3.96
4.23
3.69
3.72
4.28
3.70
3.86
4.36
3.82
3.64
4.44
3.39
3.58
3.57
4.27
3.96
4.18
3.81
3.56
3.33
3.97
3.46
3.89
3.61
3.29
3.27
3.28
3.37
Rank
50
54
88
37
55
83
79
71
104
78
89
48
74
63
87
84
61
86
77
57
80
90
51
97
93
94
62
75
64
81
95
99
73
96
76
92
101
103
102
98
9. Technological
readiness
10. Openess and
market size
Score
Rank
Score
Rank
3.63
2.71
3.30
2.72
2.84
3.01
2.88
3.29
2.49
3.00
3.07
2.75
2.62
2.76
3.20
2.87
2.48
2.26
2.71
2.65
2.55
2.42
2.90
2.49
2.20
2.42
2.58
2.08
2.33
2.23
2.22
2.49
2.57
2.21
2.45
2.19
2.38
1.75
1.72
1.83
43
78
50
76
71
62
69
51
84
63
59
75
80
74
55
70
87
95
77
79
83
91
68
85
99
90
81
101
93
96
97
86
82
98
89
100
92
103
104
102
1.45
1.35
1.50
1.22
1.44
1.22
1.20
1.58
1.43
1.54
1.25
1.26
1.38
1.29
1.36
1.16
1.25
1.18
1.29
1.29
1.16
1.25
1.44
1.19
1.21
1.06
1.26
1.08
1.30
1.16
1.16
1.17
1.19
1.20
1.21
1.14
1.04
1.08
1.09
1.12
52
64
42
83
55
84
88
36
57
38
80
77
62
72
63
96
81
91
73
70
94
79
53
89
86
103
78
102
69
95
97
93
90
87
85
98
104
101
100
99
1.3: The Global Competitiveness Index
Table 5: Global Competitiveness Index: Efficiency enhancers (cont’d.)
69
1.3: The Global Competitiveness Index
70
Table 6: Global Competitiveness Index: Innovation factors
Country
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
United States
Finland
Denmark
Switzerland
Sweden
Germany
Singapore
Hong Kong SAR
United Kingdom
Japan
Taiwan
Netherlands
Iceland
Norway
Canada
Australia
France
Austria
Belgium
New Zealand
Luxembourg
Israel
Malaysia
Estonia
Bahrain
Korea
Ireland
Jordan
Chile
Tunisia
United Arab Emirates
China
Thailand
Spain
Slovenia
South Africa
India
Czech Republic
Lithuania
Portugal
Slovak Republic
Malta
Namibia
Latvia
Morocco
Hungary
Egypt
Indonesia
Brazil
Mauritius
Greece
Cyprus
Costa Rica
Panama
El Salvador
Italy
Romania
Botswana
Dominican Republic
Mexico
Vietnam
Algeria
Trinidad and Tobago
Russian Federation
11. Business
sophistication
12. Innovation
Score
Rank
Score
Rank
5.66
5.34
5.23
5.25
5.33
5.49
4.81
4.85
5.24
5.60
5.13
5.18
4.75
4.83
5.08
4.87
5.15
4.99
4.99
4.78
4.58
4.75
4.47
3.96
3.91
4.64
4.74
3.68
4.22
4.06
4.48
4.01
4.21
4.45
4.05
4.47
4.56
4.04
4.07
3.96
3.91
3.46
3.51
3.75
4.00
3.67
4.09
3.93
4.49
3.75
3.86
3.80
3.92
3.72
3.58
4.54
3.47
3.34
3.52
3.82
3.17
3.02
3.75
3.71
1
4
8
6
5
3
18
16
7
2
11
9
21
17
12
15
10
14
13
19
24
20
30
43
48
23
22
62
32
36
28
39
33
31
37
29
25
38
35
42
47
75
69
55
40
63
34
44
27
54
49
52
46
59
67
26
72
80
68
51
87
93
56
60
4.70
4.06
3.61
3.97
4.06
3.98
3.49
2.94
3.52
4.28
3.74
3.46
3.19
3.18
3.38
3.21
3.45
3.24
3.29
2.96
2.93
3.82
2.90
2.56
2.10
3.11
3.01
2.40
2.32
2.58
2.32
2.84
2.41
2.61
2.76
2.73
2.82
2.67
2.53
2.43
2.41
2.10
2.15
2.11
2.28
2.50
2.27
2.60
2.61
2.21
2.40
2.07
2.45
2.06
1.79
2.43
2.28
2.24
1.89
2.23
2.10
1.98
2.18
2.56
1
3
9
6
4
5
11
23
10
2
8
12
18
19
14
17
13
16
15
22
24
7
25
36
73
20
21
44
49
34
50
26
42
31
28
29
27
30
37
40
43
74
67
70
55
38
56
33
32
60
45
77
39
79
95
41
53
57
90
59
75
88
63
35
(cont’d)
Country
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
Jamaica
Sri Lanka
Turkey
Ghana
Colombia
Bulgaria
Uruguay
Poland
Ukraine
Philippines
Argentina
Peru
Nigeria
Uganda
Croatia
Venezuela
Gambia
Macedonia, FYR
Guatemala
Kenya
Madagascar
Georgia
Pakistan
Ecuador
Honduras
Paraguay
Zambia
Nicaragua
Malawi
Bangladesh
Bolivia
Serbia and Montenegro
Tanzania
Bosnia and Hercegovina
Mali
Mozambique
Zimbabwe
Ethiopia
Chad
Angola
11. Business
sophistication
12. Innovation
Score
Rank
Score
Rank
3.66
3.46
3.99
3.40
3.79
3.34
3.22
3.68
3.74
3.60
3.63
3.47
3.85
3.36
3.38
3.24
3.48
3.11
3.32
3.73
3.28
2.73
3.92
3.12
2.95
2.94
3.48
2.68
3.07
3.09
2.74
3.13
3.33
2.89
2.86
2.67
3.31
2.73
2.61
2.35
64
74
41
76
53
79
86
61
57
66
65
73
50
78
77
85
71
90
82
58
84
99
45
89
94
95
70
101
92
91
98
88
81
96
97
102
83
100
103
104
2.33
2.15
2.17
2.23
2.20
2.03
2.11
2.30
2.32
2.08
2.00
1.81
2.28
2.37
2.21
2.04
2.06
2.03
1.88
2.33
2.14
1.98
1.96
1.76
1.64
1.55
2.04
1.64
2.06
1.74
1.61
2.15
2.13
1.81
2.10
1.85
1.99
1.74
1.47
1.41
47
65
64
58
62
84
71
52
51
76
85
94
54
46
61
81
80
83
91
48
68
87
89
96
99
102
82
100
78
97
101
66
69
93
72
92
86
98
103
104
Notes
1 We thank Jennifer Blanke and Augusto Lopez-Claros for their thoughts
and long conversations over the last few months. We also thank
Catherine Vindret for extraordinarily able research assistance and
Michael Porter and Christian Kettels for comments on an earlier
draft.
2 This definition is similar to the one used by Porter (2004).
3 Competitiveness, on the other hand, should NOT be characterized as “a
country’s share of world markets for its products.” As suggested by
Porter (2003), the competitiveness of a nation is not a zero-sum
game in which one country’s gain comes at the expense of others.
It is important to emphasize that this is a flawed definition of competitiveness because it has been widely used to justify intervention
to tilt markets in one’s favor. Countries have engaged in “industrial
policy,” provided subsidies, and devalued their currencies all in the
hope of expanding exports at their neighbors’ expense, all in the
hope of improving a country’s “competitiveness.” Subsidies, however, shift resources away from the most productive activities, and
devaluations (even when they are called “competitive devaluations”)
are nothing but a reduction of the price of one’s products and are a
signal that the firms are not competitive enough. Moreover, devaluations tend to increase the price of imported capital goods, which
tends to make domestic firms even less competitive.
4 The idea was that the growth rate of a country depended only on the
fraction of its GDP that it invested. If the savings generated by its
citizens were not enough to finance the investment required to
achieve the desired growth rate, the World Bank would finance the
difference (this is why this line of thought was, and still is, called the
“financing gap”). See Easterly’s chapter in this volume for more on
the role of investment as an engine of growth.
5 Schumpeter (1942), Solow (1956), and Swan (1956). Recent research
on the importance of R&D for growth includes Romer (1990), Aghion
and Howitt (1992), and Grossman and Helpman (1991). See Aghion
and Howitt (1992) and Barro and Sala-i-Martin (2003) for a technical
exposition of technology-based growth theories.
6 See Acemoglu et al. (2001 and 2002); Rodrik, Subramanian, and Trebi
(2002); Easterly and Levine (1997); and Sala-i-Martin and
Subramanian (2003).
1.3: The Global Competitiveness Index
Concluding Remarks
This chapter presents a new index of competitiveness
based on 12 pillars that capture the complex nature of the
determinants of the productivity of nations.The pillars are
comprised of institutions, physical infrastructures, macroeconomic stability, personal security, human capital, the
efficiency of the goods, labor and financial markets, technological readiness, market size, business sophistication,
and innovation.
The 12 pillars are aggregated into three subindexes
called basic requirements, efficiency enhancers, and innovation
factors.These subindexes are cast in a framework of stages
of development in which different factors matter differently at different stages of economic development. In the
first stage of development, (the factor-driven stage), the
key factors are the basic requirements. In the second stage,
(the efficiency-driven stage), the most important are the
efficiency enhancers. In the last stage, (the innovationdriven stage), the central inputs are the innovation factors.
The index is computed for 104 countries and world
competitiveness rankings are provided.The United States
is the most competitive economy in the world, followed
by Finland, Denmark, Switzerland, Sweden, Germany,
Singapore, Hong Kong, the United Kingdom, and Japan.
At the lower end, Angola is the worst-ranked economy in
the world, followed by Chad, Ethiopia, Zimbabwe,
Mozambique, Mali, Bosnia-Hercegovina,Tanzania, and
Serbia-Montenegro.
The disaggregated nature of the 12 pillars allows us to
pin down the most and least favorable components of
competitiveness for each country.
7 See De Soto (1990) for an illuminating analysis of how bureaucracy
harms growth.
8 See Shleifer and Vishny (1997) for a comprehensive survey of corporate
governance and the firm. See also Zingales (1998).
9 World Bank (1994); Gramlich (1994); Aschauer (1989); and Canning,
Fay, and Perotti (1992).
10 Easterly (2002) explains how important the World Bank has usually
thought physical infrastructures are for the process of economic
development.
11 See Fischer (1993).
12 See World Bank (2004) for research papers on the economic causes
and consequences of crime, violence, and war.
13 See Sachs (2001) for a comprehensive review of how health affects
the economic prosperity of nations.
14 See Schultz (1961), Becker (1993), and Lucas (1988).
15 See Frenkel and Romer (1999), Rodrik and Rodriguez (1999), and
Sachs and Warner (1995).
16 See Solow (1956), Swan (1956), Romer (1991), Aghion and Howitt
(1992), and Grossman and Helpman (1991).
17 See Rostow (1960).
18 Our allocation of countries to stages is described below. We did not
agree with Porter that Canada or Australia belong to the FactorDriven stage.
19 In the papers that accompany the presentation of the BCI (Porter,
2003), the process of development is described as consisting of different “stages.” However, the actual implementation of the index
does not allow for stages since all countries are treated symmetrically, independent of their level of income or the stage in which they
are found. This contrasts with the companion paper to the GCI,
which allows for two types of countries: those that are in the early
stages (called ”non-core economies”) and those that are more
advanced (called “core economies”). The only difference between
core and non-core economies, however, is the way in which technological progress occurs: in the core economies, technological
improvements occur through R&D; in the non-core countries, it
occurs through imitation.
20 In the factor-driven stage, the size of the market is not as important
because basic production processes may not be subject to
economies of scale. In fact, some of these processes (such as the
extraction of natural resources) may exhibit diminishing returns. In
the industrial world, where many processes require large sunk costs
and fixed factors, economies of scale become important. In the
world of technology and innovation, the economies of scale are even
larger because ideas are non-rival (that is, they can be used by many
people at the same time). Non-rivalry means that once an invention
is produced, the larger the market in which it can be sold, the more
profitable it is for the entrepreneur who invented it.
21 Since these are weights, the coefficients ␣1, ␣2, and ␣3 are required
to add up to 1.
71
1.3: The Global Competitiveness Index
22 Technical note: These weights were chosen using a maximum likelihood method of an econometric model that had the growth rate of
per capita GDP between 1960 and 2000 as the explanatory variable,
and various proxies for basic requirements, efficiency enhancers,
and innovation factors as dependant variables. The regression
allowed countries in different stages to have different coefficients.
The coefficients that maximized likelihood, then, were “rounded”
and became the weights for each stage reported in Table 1.
A related and interesting point for future research is that the stages
of development theory suggests that econometric analysis that
forces all countries to have the same regression coefficients is misspecified. Thus, empirical results that suggest that certain variables
are not robustly correlated with economic growth, with competitiveness or with productivity are flawed. See Sala-i-Martin, Doppelhofer,
and Miller (2004) for a paper on robust econometric methods in
cross-country growth regressions.
23 Note that the Growth Competitive Index, the only index of the GCR
that actually allows for two stages of the development, introduces a
discrete jump as countries move from non-core to core economies.
Since the definition of core economy is based exclusively on the
number of patents (core economies are those with more than 15
patents per million population and a non-core country is one that has
fewer than that), as a country increases its innovation effort and
moves across the 15-patent threshold, the weights assigned to each
subindex change discretely. It could, therefore, be the case that a
country that increases its innovation rate ends up suffering a dramatic fall in the ranks. Although this has never happened since the GCI
was first introduced in 2001, this is a potential problem and an additional reason why the GCI needs to be improved.
72
24 Factor-driven economies are those that compete in low prices. We
proxy low wages with low income levels, which is why we assign
countries with 2003 income per capita below US$2000 to this group.
GDP per capita is measured at exchange rates: international firms
competing for low-cost production should look at exchange-rate
comparable costs rather than PPP-adjusted costs. Primary exports
are important factors that usually compete in prices. This is why we
include countries with a high primary goods content in their exports
in this category.
25 See also Figures 2, 3, and 4.
26 We think of each question as addressing slightly different aspects of
the same phenomenon. Since there are no theoretical or empirical
reasons to believe that some aspects are more important than others, we decide to give the same weight to all questions within a pillar. However, seven Survey question variables and one hard-data
variable are used in two sections in the construction of the index. In
order to avoid double counting, we divide their value by 2 before we
include them in the computation.
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1.3: The Global Competitiveness Index
Appendix 1: How Executive Opinion Survey questions and hard data are assigned to each pillar 1
This appendix provides details on how the Global
Competitiveness Index is constructed. All of the Survey
and hard data variables used in this index can be found
in the data tables section of this Report with more
detailed descriptions.
1st Pillar: Institutions
The 1st pillar is an average of two subindexes: public
institutions and private institutions.
Public institutions, in turn, is an average of three
components: property rights, honesty and corruption of
the public sector, and government inefficiencies (which
captures red tape, excess bureaucracy and waste).
Private institutions is an average of four components: honesty of the corporate sector, accountability,
transparency, and social responsibility.
The list of Survey questions we assign to each
component is:
1. Public Institutions
A. Property Rights
74
•
2.10: Effectiveness of bankruptcy law
•
6.03: Property rights
•
6.04: Intellectual property protection (weight = 1/2) 2
•
6.16: Reliability of police services (weight = 1/2)
B. Honesty and Corruption
C. Transparency
•
6.34: Pervasiveness of money laundering through banks
•
6.35: Pervasiveness of money laundering through nonbank channels
D. Charity and Social Responsibility
•
9.25: Charitable causes involvement
•
9.26: Company promotion of volunteerism
2nd Pillar: Physical Infrastructures
The 2nd pillar is again the average of two subindexes:
general infrastructures and specific infrastructures (rail,
ports, air, and electricity).
The Survey questions and hard data we assign to
each subindex are:
1. General Infrastructures
•
5.01: Overall infrastructure quality
2. Rail, Ports, Air, Electricity
•
5.02: Railroad infrastructure development
•
5.03: Port infrastructure quality
•
5.04: Air transport infrastructure quality
•
5.05: Quality of electricity supply
•
5.08: Telephone lines, 2003 (hard data)
3rd Pillar: Macro Stability
The 3rd pillar is an average of five hard-data variables:
•
6.01: Judicial independence
•
6.10: Favoritism in decisions of government officials
•
2.22: Government surplus/deficit, 2003
•
6.28: Business costs of irregular payments
•
2.23: National savings rate, 2003
•
6.29: Diversion of public funds
•
2.25: Inflation, 20033
•
6.31: Public trust of politicians
•
2.26: Interest rate spread, 2003
•
6.32: Prevalence of illegal political donations
•
2.29: Government debt/GDP ratio, 2003
C. Government Inefficiency (red tape, bureaucracy and
waste)
4th Pillar: Personal Security
•
6.06: Wastefulness of government spending
•
6.07: Burden of central government regulation
•
6.08: Burden of local government regulation
•
6.09: Transparency of government policy-making
•
2.02: Business costs of terrorism
•
7.05: Administrative burden for startups
•
6.16: Reliability of police services (weight = 1/2)
•
6.17: Business costs of crime and violence
•
6.18: Organized crime
2. Private Institutions
A. Honesty
•
9.05: Ethical behavior of firms
B. Accountability
•
9.17: Efficacy of corporate boards
•
9.22: Protection of minority shareholders’
interests
•
The 4th pillar has only one component, which consists
of four Survey questions:
9.24: Strength of auditing and reporting standards
5th Pillar: Human Capital
The 5th pillar contains two subindexes: basic human
capital and advanced human capital.
Basic human capital is an average of two components: health and primary education. See Appendix 5 for
a complete description of how we use hard and Survey
data to obtain an estimation of national health.
Advanced human capital is an average of three components: the quantity of education, the quality of the
education system, and on-the-job training.
The Survey questions and hard data used in each
component are:
We again combine survey and hard data in these
components.The list of variables in each of them is the
following:
1. Government-Induced Distortions:
•
2.17: Tax burden
Basic Human Capital
•
2.20: Agricultural policy costs
1. Health (See Appendix 5 for details):
•
6.02: Efficiency of legal framework
•
6.13: Extent and effect of taxation (weight = 1/2)
•
4.05: Current business impact of malaria
•
4.06: Current business impact of tuberculosis
•
4.07: Current business impact of HIV/AIDS
•
4.08: Medium-term business impact of malaria
•
4.09: Medium-term business impact of tuberculosis
•
7.01: Intensity of local competition
•
4.10: Medium-term business impact of HIV/AIDS
•
7.03: Extent of market dominance
•
4.15: Infant mortality (hard data)
•
7.06: Effectiveness of anti-trust policy
•
4.16: Life expectancy at birth (hard data)
•
7.07: Prevalence of mergers and acquisitions
•
4.17: Tuberculosis prevalence (hard data)
•
4.18: Malaria prevalence (hard data)
•
2.12: Cost of importing foreign equipment
•
4.19: HIV/AIDS prevalence (hard data)
•
2.13: Business impact of domestic trade barriers
•
2.14: Business impact of foreign trade barriers
•
2.15: Business impact of customs procedures
•
2.28: Imports, 2003 (hard data)
2. Primary Education
•
4.20: Gross primary enrollment (hard data)
Advanced Human Capital
1. Quantity of Education
•
2. Competition (weights should be the fraction of
Imports on GDP)
A. Domestic Competition
B. Foreign Competition (Imports)
3. Customers (Demand Conditions)
•
3.10: Availability of scientists and engineers
3.09: Government procurement of advanced technology
products (weight = 1/2)
(weight = 1/2)
•
8.01: Buyer sophistication
•
4.21: Gross secondary enrollment (hard data)
•
9.08: Degree of customer orientation
•
4.22: Gross tertiary enrollment (hard data)
2. Quality of Education System
•
3.12: Internet access in schools
•
4.01: Quality of the educational system
•
4.03: Quality of math and science education
•
9.16: Quality of management schools
3. On-the-Job Training
•
•
7th Pillar: Labor Market Efficiency
The 7th pillar is an average of three subindexes: labor
market flexibility, female participation, and meritocracy.
The Survey questions assigned to each one are:
1. Labor Market Flexibility
8.10: Local availability of specialized research and
•
6.13: Extent and effect of taxation (weight = 1/2)
training services (weight = 1/2)
•
9.18: Hiring and firing practices
9.12: Extent of staff training
•
9.19: Flexibility of wage determination
•
9.20: Cooperation in labor-employer relations
6th Pillar: Goods Market Efficiency
The 6th pillar is an average of three subindexes: government-induced distortions, competition, and demand
conditions. Competition, in turn, is a weighted average
of two components: domestic competition and foreign
competition.4
1.3: The Global Competitiveness Index
Appendix 1: How Executive Opinion Survey questions and hard data are assigned to each pillar (cont’d.)
2. Female Participation
•
4.13: Maternity laws’ impact on hiring women
•
7.08: Private sector employment of women
3. Meritocracy (incentives/effort):
•
4.12: Brain drain
•
9.15: Reliance on professional management
(weight = 1/2)
•
9.21: Pay and productivity
75
1.3: The Global Competitiveness Index
Appendix 1: How Executive Opinion Survey questions and hard data are assigned to each pillar (cont’d.)
8th Pillar: Financial Markets Efficiency
11th Pillar: Business Sophistication
The 8th pillar is a (weighted) average of three subindexes: efficiency of the financial sector, trustworthiness, and
foreign direct investment.5
The Survey questions that belong to each subindex are:
The 11th pillar is the average of two subindexes:
networks and supporting industries (clusters), and
sophistication of firms operations and strategy.
The Survey questions in each subindex are:
1. Efficiency
1. Networks and Supporting Industries (Clusters)
•
2.03: Financial market sophistication
8.02: Local supplier quantity
•
2.05: Ease of access to loans
8.03: Local supplier quality
•
2.06: Venture capital availability
8.06: State of cluster development
2. Trustworthiness / Confidence
2. Sophistication of Firms Operations and Strategy
•
2.04: Soundness of banks
9.06: Production process sophistication
•
2.09: Regulation of securities exchanges
9.07: Extent of marketing
9.09: Control of international distribution
3. FDI
•
2.16: Business impact of rules on FDI
•
9.23: Foreign ownership restrictions
9th Pillar: Technological Readiness:
The 9th pillar is simply the average of five Survey
questions and two hard data variables:
76
•
3.01: Technological readiness
•
3.02: Firm-level technology absorption
•
3.13: Quality of competition in the ISP sector
•
3.16: Laws relating to ICT
•
3.18: Cellular telephones, 2003 (hard data)
•
3.19: Internet users, 2003 (hard data)
•
8.10: Local availability of specialized research and
9.13: Willingness to delegate authority
9.15: Reliance on professional management (weight = 1/2)
12th Pillar: Innovation
The 12th pillar is the average of seven survey questions
and two hard data variables:
3.05: Quality of scientific research institutions
3.06: Company spending on research and development
3.08: University/industry research collaboration
3.09: Government procurement of advanced technology
products (weight = 1/2)
3.10: Availability of scientists and engineers (weight = 1/2)
3.17: Utility patents, 2003 (hard data)
6.04: Intellectual property protection (weight = 1/2)
training services (weight = 1/2)
9.04: Capacity for innovation
GDP – Exports + Imports (weight = 1/2) (hard data)
10th Pillar: Openness and Market Size
The 10th pillar is an average of two subindexes: local
market size and foreign market size.The foreign market
size is an average of two components: quantity of exports
and the quality of exports.6
The Survey questions and hard data assigned to each
subindex are:
1. Local Markets Size
•
GDP - Exports + Imports (weight = 1/2) (Hard data)
2. Foreign Markets (Exports) Size
A. Quantity of exports
•
2.27: Exports, 2003 (hard data)
B. Quality of exports
•
9.01: Nature of competitive advantage
•
9.02: Value chain presence
Notes
1 See Appendix 2 for a description of how hard data are transformed
into Survey-comparable values. See Appendix 3 for a description of
how we deal with data that are ranked backwards.
2 Half weight to avoid double accountability, as discussed before.
3 See Appendix 4 for a description of how we deal with inflation and
deflation.
4 See Appendix 6 for a description of how the relative weights of
domestic and foreign competition are estimated.
5 See Appendix 7 for a description of the relative weights of FDI and
local financial markets.
6 See Appendix 8 for a description on how this is constructed.
Answers to the Executive Opinion Survey questionnaires
are ranked in a 1-to-7 scale. In most of the cases (see
below for exceptions), 7 indicates the best possible outcome while 1 indicates worst possible outcome. Our
index combines these Survey data with hard data (hard
data are those that can be “objectively” measured—GDP,
the number of patents, or the number of Internet connections in a country would be examples of hard data).
Of course hard data do not come in 1-to-7 rankings.We
follow McArthur and Sachs (2001) and transform all
hard data into a 1-to-7 scale using the following procedure. If the highest value for a data series is max and the
lowest value is min, then the new 1-to-7 rank value is
related to original value using the formula:
New value = 6 x
(original value – min)
(max – min)
Notice that this formula will assign a 7 to the country
with the highest value, a 1 to the country with the
lowest value, and numbers between 1 and 7 to all other
countries.
For some variables, a higher value indicates a worse
outcome. For example, high levels of infant mortality are
bad. In this case we “reverse” the series by subtracting
the newly created variable from 8.
1.3: The Global Competitiveness Index
Appendix 2. Combining hard data and Executive Opinion Survey data
+ 1
77
Appendix 3. Dealing with Survey data ranked backwards
A small number of questions in the Survey are written a
way that numerically higher answers imply worse outcomes and numerically lower numbers imply better outcomes.That is, the answers are reported backwards relative to vast majority of the Survey. Moreover, the choices
available in the Survey do not always restrict the answers
to six categories. Of course, we need to transform the
information before we combine it with the rest of the
variables.We follow a procedure similar to the one for
transforming hard data.
In order to do this, we first locate the highest and
the lowest country average.We create then an intermediate variable that is equal to the maximum plus the minimum value (both common for all countries) minus the
original number (the one reported for each particular
country).We finally use this intermediate variable to
apply a formula similar to the one above:
New = 6 x
(intermediate – min)
(max – min)
+ 1
1.3: The Global Competitiveness Index
Appendix 4. The way we treat inflation
Economists recognize that large levels of inflation are
bad for competitiveness because large price increases
tend to be associated with uncertainty and instability.
Neither the theories of inflation nor empirical evidence
suggests that low levels of inflation are bad for productivity, competitiveness, or economic growth. Finally, economic analysts suggest that deflation harms the economy.
We capture all of these phenomena in our index by
introducing inflation in our macroeconomic stability pillar in a U-shaped manner, as depicted by Figure A1.
That is, for values of inflation between 0 and 4 percent, the country receives best possible score (that is, the
lowest level of instability). In other words, we think that
inflation rates between 0 and 4 are equally harmful to
the economy. Beyond this range, both inflation and
deflation tend to reduce competitiveness.
Because of the scaling system we use, 1 = worst to 7
= best, the country with the highest deviation will get a
1, all countries with an inflation rate within the 0–4
range will obtain a 7, and the remaining countries are
scored relative to the worst one.
In practice, we create an intermediate variable equal
to 0 if a country has an inflation between 0 and 4 percent, and a positive number otherwise (as depicted by
Figure A1).The positive number is equal to the deviation
below 0 for countries with deflation and equal to the
inflation level minus 4 for countries with inflation above
the optimal range
Higher numbers mean worse outcomes and the
range is not restricted between 1 and 7.We need, once
again, to rescale the variable so it conforms with the rest
of the variables. As usual, we first rescale into a 1-to-7
scale and we then reverse the number so that higher is
better, as discussed above.
78
Figure A1: Inflation in the pillar of macroeconomic stability
Macro instability
Inflation rate
0%
4%
In our health section, we include the economic impact
of three diseases: malaria, tuberculosis, and HIV. To estimate the economic impact of diseases, we combine hard
data on incidence collected by the World Health
Organization with questions from the Executive
Opinion Survey that reflect how these diseases affect
business.The idea is that impact of a disease on competitiveness depends not only on its incidence in the population but also on how costly this incidence is. If many
people are infected with a disease that has no economic
impact, then incidence should have little effect on productivity (for example, different strains of a disease have
different severity and the segments of population affected
by it differ across countries, which then might have a
distinct impact on the local economies). On the other
hand, if a country has little incidence of a very costly
disease, the effects on competitiveness might be major.
Thus, we need to combine the hard data on incidence
with the Survey data on the costs of these diseases for
business.
To combine these data we first rank each country’s
prevalence relative to the highest prevalence in the
world.That is, we create a ratio of own-country prevalence divided by the prevalence in the highest country.
Higher numbers (those closer to 1) indicate worse scenarios. Since the answer to Survey questions are ranked
in the opposite direction (where a higher number indicates a better outcome), we reverse the Survey numbers
so higher values indicate worse outcomes (see details
above on how to do this).
Once hard and Survey data are ranked in the same
direction, we multiply the ratio (hard data) with the
Survey average.This product is then transformed into a
1-to-7 variable using the method described above; it is
then reversed so that higher values denote better outcomes. Note that all counties where the malaria prevalence is 0 obtain a 7 in the ranking (since their competitiveness is not directly affected by it), regardless of what
the Survey says.
1.3: The Global Competitiveness Index
Appendix 5. How diseases are treated to construct the health component of basic human capital
79
Appendix 6. Domestic and foreign competition
The 6th pillar—goods market efficiency—has a
component called “competition.” Using Survey data,
we evaluate how distorted firms’ competition is in
both the domestic and the foreign market.The relative
importance of these distortions depends, however, on the
relative size of domestic versus foreign competition.
We create two new variables that indicate this
relative importance. Domestic competition is the sum of
consumption (C), investment (I), government spending
(G), and exports (X); foreign competition is equal to
imports (M).Thus, we assign a weight of (C + I + G +
X)/(C + I + G + X + M) to the Survey questions
related to local competition and M/(C + I + G + X +
M) to those related to foreign competition.
1.3: The Global Competitiveness Index
Appendix 7: Financial markets
The financial markets efficiency pillar (the 8th pillar)
consists of two components related to local financial
markets and foreign investment respectively.We believe
that foreign direct investment (FDI) should have more
crucial importance in countries with bad financial markets. In other words, if the local financial sector is very
efficient, foreign financing is less necessary.Thus, the
weight that FDI should get in the financial efficiency
pillar depends on the efficiency of the local financial
market.
We give a weight of at least 50 percent to the home
financial sector.The other 50 percent of the weight is an
average of local financial market and FDI where the relative weight depends on the efficiency of the local financial sector. For the extreme case of the worst local financial market in the world, the 8th pillar is constructed
with half of the weight for local financial market and
half of the weight for FDI. At the other extreme, when
the local markets are well functioning, the importance
of FDI is zero.
80
Appendix 8. Openness and market size
The 10th pillar of competitiveness measures the size of
the market to which local firms have access. This has
two components: the size of the local market and the
value of exports. Local market should be the sum of
consumption (C), investment (I), and government spending (G).We lack the data on these three macro components, but we do have data on exports (X), imports (M),
and GDP. By definition,
GDP = C + I + G + (X – M)
Therefore, we compute as:
Local market = GDP + M – X
Note that for comparability purposes across countries,
we measure local market in GDP-PPP adjusted units.
The second component of market size is exports. In
order to establish comparability with the local market
size, we also measure exports in domestic PPP prices.
The exact formula used, therefore, is:
Financial market = 1/2 x local + 1/2
x
[
local x (local – 1)
6
+ FDI x
[
]
1 – (local – 1)
6
]