CHAPTER 1.3

The Global CompetitivenessIndex1

XAVIER SALA-I-MARTIN, Columbia University,

Universitat Pompeu Fabra, and NBER

ELSA V. ARTADI, Harvard University

Competitiveness has become a constant fixation amongpolitical leaders, popular press, corporations, and nationaland international institutions. Even plain citizens worryabout the “competitiveness” of a nation when theyobserve, puzzled, how outsourcing or manufacturing relo-cation takes jobs from their home country.

This chapter presents a new index of competitiveness:the Global Competitiveness Index.We designed this newindex with the goal of unifying the two indexes currentlyproduced by the World Economic Forum (the GrowthCompetitiveness Index [McArthur and Sachs (2001)] andthe Business Competitiveness Index [Porter (2001)]), andit is meant eventually to replace them in the GlobalCompetitiveness Report.

Competitiveness is defined as the set of institutions,policies, and factors that determine the level of productivi-ty of a country.2 The level of productivity, in turn, sets thesustainable level of prosperity that can be earned by aneconomy. In other words, more competitive economiestend to be able to produce higher levels of income fortheir citizens.The productivity level also determines therates of return obtained by investments in an economy.Given that the rates of return are the fundamental deter-minants of the aggregate growth rates of the economy, amore competitive economy is one that is likely to grow atlarger rates over the medium to long run.

The World Economic Forum has been publishing twoindexes of competitiveness that are supposed to describetwo aspects of the same phenomenon.While the GrowthCompetitiveness Index (GCI) refers to the aggregate ormacroeconomic determinants of productivity, the BusinessCompetitiveness Index (BCI) captures the microeconomiccomponents of productivity (in fact, in 2002, the BCI wascalled the “Microeconomic Competitiveness Index”).Webelieve that the macroeconomic and microeconomicdeterminants of competitiveness cannot and should not beseparated.The ability of firms to prosper depends, amongother things, on the efficiency of the public institutions,the excellence of the education system, and the overallmacroeconomic stability of the country in which theyoperate. But an excellent macro environment does notguarantee national prosperity unless firms create valuablegoods and services using efficient methods and processesat the microeconomic level. Only by reinforcing eachother can the micro and macroeconomic characteristics ofan economy jointly determine its level of productivity andcompetitiveness.Thus, it is not surprising that the correla-tion between the GCI and BCI has always been very high(for example, last year the rank correlation between thetwo indexes was 95.4 percent).

Another difference between the BCI and GCI is sup-posed to be that, while the BCI captures the “static” or“level” determinants of productivity of a country, the GCIis supposed to capture its “dynamic” or “growth”

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prospects.As mentioned above, we think that the conceptof competitiveness involves static and dynamic compo-nents: although the productivity of a country clearlydetermines its ability to sustain a high level of income, it isalso one of the central determinants of the returns toinvestment, which is one of the central factors explainingan economy’s growth potential.Thus, given that productivityhas both static and dynamic implications for a country’sstandard of living, an alternative (although almost identi-cal) definition of competitiveness would be the set of institu-tions, policies, and factors that set the sustainable currentand medium-term levels of economic prosperity.3

In this chapter we propose a unified approach thatcaptures both the microeconomic and macroeconomicfoundations of competitiveness as well as its static anddynamic consequences in a single index that we call theGlobal Competitiveness Index.We call it “Global” becausethe index is destined to become the flagship index of theGlobal Competitiveness Report, and because it is meant tocapture the entirety of factors that help determine theproductivity of nations.

The new index is based on three principles.

Principle 1. Productivity is complex: Twelve pillars ofcompetitivenessThe first principle is that the determinants of competitive-ness are many and complex. Some of the best economicminds of the last two hundred years have asked whatdetermines the wealth of nations.Adam Smith argued thatspecialization and the division of labor was key.ThomasMalthus and David Ricardo, two of the best economists ofthe 19th century, thought that natural resources imposed abinding limit on the level of prosperity.The law of dimin-ishing returns meant that population growth would even-tually require the use of low-quality land, and this wouldreduce production per capita and cap the potential foreconomic growth.

The neoclassical economists of the 20th centuryemphasized investment in physical capital and infrastruc-tures.This belief underlay many plans that governed theeconomy of the Soviet Union and the countries under itspolitical influence. It was also the foundation upon whichinstitutions such as the World Bank operated for decades.4

The failure of many developing countries to grow despitethe aid of the donors proved that investing in physicalcapital was not enough to generate aggregate wealth.Economists, then, looked for other mechanisms. Educationand training (or human capital, as modern economists callit) became the center of economic research. Developingcountries were advised to educate their children and toinvest in the expansion of their human capital.Theydid. . .but economic growth failed to materialize in mostof them.

Technological progress (whether created by the coun-try or copied from the leading economies) was thenthought to be a central determinant of economic growth.5

Few people today disagree with this idea, although thismerely shifts the question from “what determines thegrowth rate of GDP?” to “what determines the rate oftechnological progress?”This is why economists have keptsearching. Many answers have been proposed: openness,macroeconomic stability, governance, the rule of law,institutions, lack of corruption, market orientation, gov-ernment waste, firm sophistication, demand conditions,market size, and many others.

Each of these conjectures rests on solid theoreticalfoundations and makes economic sense; some even havestrong empirical support.The central point, however, isthat they could all be true at the same time because theyare not mutually exclusive.The main lesson from two centuries of economic thinking should be that the processof economic development is rather complex and manyfactors are needed for a country to succeed.As WilliamEasterly (2002) famously put it:“there is no such a thingas a Holy Grail of economic success.”

We capture this complexity by assigning the manyfactors that underlie competitiveness to 12 areas that wecall the 12 pillars of economic competitiveness.These pillars are:

First pillar: InstitutionsThe institutional environment forms the framework with-in which private individuals, firms, and governments inter-act to generate income and wealth. In 1776,Adam Smithargued that wealth could not be created in a world whereproperty rights are not well defined and guaranteed. DeSoto (2000) also defends the importance of the system ofproperty rights. Owners of land, corporate shares, andeven intellectual property are unwilling to invest in theimprovement and upkeep of their property if their rightsas owners are insecure. Equally importantly, if propertycannot be bought and sold with the confidence that theauthorities will endorse the transaction, the market itselfwill fail to generate dynamic growth.The absence ofproperty rights also drives people out of formal marketsinto the informal sector. De Soto estimates that people the developing and former communist countries holdmore than US$9 trillion in what he calls “dead capital”—property that is owned informally, but not legally, and isthus incapable of forming the basis of robust economicdevelopment. More recently, an important and voluminousstrand of empirical research confirms the importance ofpublic institutions as key determinants of the current levelof GDP per capita.6

The importance of institutions is not restricted to thelegal framework. Government attitudes toward marketsand freedoms and the efficiency of its operations are alsovery important: excessive bureaucracy and red tape,7

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overregulation, corruption, dishonesty in dealing withpublic contracts, lack of transparency and trustworthiness,or the political dependence of the judiciary system imposesignificant economic costs to businesses and slows downthe process of economic development.

Although the economic literature has mainly focusedon public institutions,“private institutions” are also impor-tant ingredients in the process of creation of wealth.Corporate governance, transparency, and accountability, forexample, are seen as important by economists who focuson the theory of the firm: bargaining over the ex-postrents of a firm become important in a world in which isimpossible to write contracts that fully specify the divisionof rents under all possible contingencies.8

Second pillar: Physical infrastructuresA second important determinant of competitiveness is thephysical infrastructure environment. For many years, economicdevelopment economists,9 practitioners, international insti-tutions, and donors10 have emphasized investment in phys-ical infrastructures as a required ingredient in the processof economic growth. Private firms cannot operate satisfac-torily in a economy where it is hard to transport factors ofproduction, final goods, or services; where it is hard tocommunicate or transmit information (because telephonelines are down a substantial fraction of the time or inter-net connections are hard and expensive); or where theelectrical supply is unreliable.

Third pillar: Macro stabilityThe stability of the macroeconomic environment isimportant for business and, therefore, is important for theoverall competitiveness of a country.Although it is cer-tainly true that macroeconomic stability alone cannotincrease the productivity of a nation, it is not less true thatmacroeconomic disarray harms the economy. Firms can-not make informed decisions when the inflation rate is inthe hundreds (typically as a result of public finances beingout of control).The financial sector cannot function if thegovernment runs gigantic deficits (especially if, as a result,it represses banks and it forces them to lend it money atbelow-market interest rates).The government cannot pro-vide services efficiently if it has to make enormous interestpayments on its past debts. In sum, the economy cannotgrow unless the macro environment is stable or favorable.This is why the macroeconomic environment is the thirdpillar of economic competitiveness.11

Fourth pillar: SecurityAlthough not much attention is given in the economicdevelopment literature to the problem of personal security,and although neither the GCI nor the BCI (the twoindexes published by the World Economic Forum) include

it, wealth and prosperity can hardly be created if the safetyof managers, administrators, employees, or even customerscannot be guaranteed because of military conflicts, terror-ism, organized crime, or political and economic kidnap-pings.A country that cannot guarantee the personal safetyof its citizens is a country that cannot be competitive.12

Fifth pillar: Human capitalHuman capital is the factor of production associated withthe human body.We think of it as having two importantcomponents.The first one is what we could call basichuman capital, which consists of the basic requirements fora human body to function and be productive. Chiefamong these requirements is health.The productivity ofan unhealthy human body is less than that of a healthycounterpart.The recent AIDS and malaria pandemics inlarge regions of the world makes it clear that businessconditions deteriorate when the health of the populationdeclines.13 Another component of basic human capital isbasic education: literacy and primary schooling have nowa-days become essential requirements for competitiveness.

In more advanced economies, good health and basiceducation are not enough for citizens to earn a decent liv-ing.Advanced education (secondary and tertiary school-ing) and flexible skills need to be acquired in high-qualityschools or in the firm through sophisticated on-the-jobtraining.The quality of the education system, therefore,not only its enrollment rates and the quantity of scientistsand engineers, plays an essential role in the process ofwealth creation for these more advanced forms of humancapital.14

Sixth pillar: Goods market efficiencyThe efficiency of the products and services markets is alsoan important factor in a nations’ productivity. Goods mar-ket efficiency is needed in at least three levels. First, effi-cient markets require non-disruptive public interventions(that is, policies and regulations need to cause as little dis-ruption as possible). Excessive or inefficient taxes, burden-some subsidy policies, or nontransparent legal systems aresome ways in which government actions distort the mar-kets for goods and services. Second, market efficiency isdriven by business competition. Competition imposes thenecessary discipline and readiness on firms so that theyoperate in the most efficient manner. Market dominanceby one or a few firms tends to generate market inefficien-cies, as do restrictions to competition from foreign rivals.Third, market efficiency depends on demand conditionssuch as customer sophistication: customers who acceptpoor treatment by firms tend not to impose the necessarydiscipline on companies for efficiency to be achieved inthe market.

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Seventh pillar: Labor market efficiencyMany economic analysts (especially in Europe) emphasizethe flexibility of the labor market as a leading determinantof competitiveness.The usual complaint is that tax andtransfer systems tend to reduce incentives to work and thatregulations impeding the hiring and firing of workers tendto impose heavy costs on business.Although we agreewith this view, we think of efficiency of the labor marketin a broader sense that includes not only public actions(taxes, transfers, regulations, and so on), but also privatepractices. For example, labor-employer relations that arevery confrontational tend to generate an adverse businessenvironment.The systematic promotion of relatives ratherthan workers with superior qualification, or the paymentof wages that are not related to productivity, tend to haveperverse effects on the productivity of the economy.

Another labor practice that is harmful to competitive-ness is discrimination. Discrimination consists of not allo-cating jobs based on the talent of the candidates but basedinstead on their race, religion, gender, or some such similarconsideration. One of the most widespread discriminatorypractices is the one that affects women’s labor participa-tion: countries that exclude half of their populations fromthe best jobs are countries that misallocate half of theirtalent.This has important consequences for a country’sability to generate prosperity.

Eighth pillar: Financial market efficiencyAn efficient financial sector is needed to allocate theresources saved by a nation’s citizens to its most productiveuses.A proficient financial sector channels resources to thebest entrepreneurs rather than to the politically connected.A modern financial sector develops products and methodsso that small innovators with good ideas can implementthem.A well-functioning financial sector needs to providerisk capital and loans and be trustworthy and transparent.In a globalized world, the role of foreign financing is alsoimportant, especially for economies with less developedfinancial systems.Thus, we include the foreign financing(in the form of foreign direct investment) in our analysisof financial market efficiency.

Ninth pillar: Technological readinessOne of the central differences between rich and poorcountries is that rich countries tend to use more advancedand complex production processes and tend to producemore sophisticated products and services. In other words,they tend to have a superior technological background.Whether the technology used has or has not been invent-ed within its borders is immaterial for our purposes.Thecentral point is that the firms operating in the countryhave access to these advanced products and blueprints.That is, it does not matter whether a country has inventedelectricity, 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 isirrelevant. However, the level of technology available tofirms in a country needs to be distinguished from thecountry’s ability to innovate and expand the frontiers ofknowledge.That is why we separate technological readi-ness from innovation, which is the 12th pillar below.

Tenth pillar: Openness and market sizeThe size of the market affects productivity because largemarkets allow firms to better exploit economies of scale.Traditionally, the markets available to firms have been con-strained by the borders of the nation. In the era of global-ization, exports have become a substitute for domesticmarkets, especially for small countries.

The empirical evidence on the relation betweeninternational trade and growth is highly controversial.There is a lot of evidence showing that trade is positivelyassociated with growth.15 There is some evidence suggest-ing that these results are not as strong and convincing asone would like, but there is no evidence suggesting thattrade and growth are negatively associated. Our reading ofthe literature is that the relation between openness andgrowth is likely to be positive and robust, especially forsmall countries with small domestic markets. For largereconomies, the domestic market may be large enough thatno extra gains are achieved by further opening borders totrade.Thus, we think of international trade as a substitutefor domestic demand in determining the size of the mar-ket for the firms of the country.This is particularly impor-tant in a world in which economic borders are not asclearly delineated as political ones. In other words, whenBelgium sells goods to the Netherlands, the nationalaccounts register the transaction as an export (so theNetherlands is a foreign market of Belgium), but whenCalifornia sells the same kind of output to Nevada, thenational accounts register the transaction as domestic (soNevada is a domestic market of California). By addingdomestic and foreign markets in our measure of marketsize, we avoid discriminating against geographic areas(such as the European Union) that are broken into manycountries but have one common market.This is why wedo so when we construct the tenth pillar of economiccompetitiveness: the market size.

Eleventh pillar: Business sophisticationEconomic development usually requires increasing degreesof business sophistication. One form of sophistication isthe formation of clusters.As defined by Porter (2003),“clusters are geographically proximate groups of intercon-nected companies, suppliers, service providers, and associated institutions in a particular field, linked by commonalities and complementarities.” Clusters affect

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competitiveness in various ways: first, firms with a clusterhave more efficient access to specialized suppliers, employ-ees, information, and training than isolated firms, and thisincreases their productivity. Second, clusters increase thecapacity for productivity growth.This is because opportu-nities for innovation are often seen more easily withinclusters, and because the skills, assets, and capital requiredto innovate tend to be more available around clusters.Thethird way in which clusters affect competitiveness is by theformation of new businesses through the reduction of bar-riers to entry (for example, the presence of many experi-enced workers and access to all the needed inputs andspecialized services within a proximity makes it easy to setup new firms, which reduces barriers to entry).

A second form of business sophistication is throughmore complex operations and strategies. For example, theuse of marketing or branding, the utilization of superiordistribution systems, the access to advanced technologies,and the introduction of modern business organizationalforms are all ingredients in the process of business mod-ernization (see Porter, 2003).

Twelfth pillar: InnovationThe last pillar of competitiveness is technological innova-tion. One of the central tenets of neoclassical growth the-ory is that, in the long run, the only sustainable source ofeconomic prosperity is technological progress.16 Althoughsubstantial gains can be obtained by improving institu-tions, building infrastructures, reducing macroeconomicinstability, or increasing the human capital of the popula-tion, all these factors seem to run into eventual diminish-ing returns.The same is true for the efficiency of thelabor, financial, or goods markets. In the long run, stan-dards of living cannot be expanded without technologicalinnovation. Innovation is particularly important foreconomies as they approach the frontiers of knowledgeand the possibility of copy and imitation tend to disap-pear.The environment that is most inductive to innova-tion includes modern universities and research institutionsthat cooperate with businesses, a legal environment thatprotects intellectual property rights, public institutions thatunderstand the importance of knowledge and act on thisunderstanding when they make purchasing decisions, andthe availability of scientists and engineers who can partici-pate in the process of technological improvement.

Although we describe the 12 pillars of competitive-ness separately, we do so only for expository purposes.This should not obscure the fact that they are not inde-pendent: not only they are related to each other, but theytend to reinforce each other. For example, innovation(12th pillar) is not possible in a world without institutions(1st pillar) that guarantee intellectual property rights, itcannot 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), withoutinfrastructures (2nd pillar), or in nations at war (4th pillar).

Although the actual construction of the index willinvolve the aggregation of the 12 pillars into a singleindex, we report measures of the 12 pillars separatelybecause offering a more disaggregated analysis can bemore useful to countries and practitioners.This is becausesuch an analysis gets closer to the actual areas in which aparticular country needs to improve.

Principle 2. Stages of developmentThe second principle on which the Global CompetitivenessIndex is founded is that economic development is adynamic process of successive improvement, in whicheconomies find increasingly sophisticated ways of produc-ing and competing. In other words, the process of eco-nomic development evolves in stages.

Many economists in the past have postulated theoriesof “stages of development.” Perhaps the most famous of allthese theories was that of American historian W.W.Rostow.17 Although Rostow’s theory involves five stages,his was essentially a theory of industrialization throughsavings and investment.The various stages were phasesthrough which the required resources to invest were accu-mulated, but successive take off occurred only throughphysical capital accumulation.

Our view is that the process of growth and develop-ment is a lot more complicated than a simple process ofinvestment in physical capital. It involves the successfulimplementation of policies and institutions on many dif-ferent fronts. How important each factor is depends onthe level of development of a particular country: whatmakes the United States competitive may not be the sameas what makes Angola competitive because these twocountries are in different phases of development.Thus, weadopt the framework of stages of development to organizethe index.This framework is close in spirit to that ofPorter (1990) for a variety of reasons. One reason is that,since the index presented in this chapter is destined toeventually substitute for the GCI and BCI, and given thatthe BCI is theoretically based on Porter (1990), we prefernot to break too much with the past and so continue touse a theoretical framework similar to that of the BCI. Butcontinuity is not the main reason for adopting a theory ofstages of development close in spirit to Porter’s.The cen-tral point is that we do believe that the main factors deter-mining competitiveness for poor countries are essentiallydifferent from those that matter in more advancedeconomies. Moreover, some elements of Porter’s view areuseful for both our understanding of those stages and theirimplementation as an empirical index.

Although the theory underlying our index is close inspirit to that of Porter, there are some important discrepancies.

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One difference is that, while he thinks of the process ofdevelopment as involving four phases, we will use onlythree stages. Porter’s fourth stage of development, whichhe calls the Wealth-Driven stage, leads to a decline in standards of living.The economy is driven by already-accumulated wealth, which shifts incentives away fromefficient investment and innovation. Since we do notobserve declining growth rates for economies with thehighest levels of per capita GDP, we do not include thisfourth stage in our analysis.Another difference is that theexact elements that are important at each stage are not thesame.A third difference is the way Porter sees the secondstage 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 themost 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 oftheir cheap factors (including low-cost labor and cheapunprocessed natural resources). In this phase, firms producecommodities and simple products originally invented anddesigned in other countries. In order to be competitive atthis initial stage, an economy must satisfy some basicrequirements. Chief among them are good institutions,sufficient infrastructures, basic human capital, macroeco-nomic stability, and overall personal security.An importantpoint is that being successful in this stage eventually meanslosing competitiveness unless economies prepare for thenext stage.The reason is that successful economies experi-ence positive growth rates, and this means growing wagerates. For a country whose source of competitiveness is thelow price of its labor, a growing salary implies a loss ofcompetitiveness.

In the second stage, which we call the efficiency-drivenstage, efficient production practices become the mainsource of competitiveness.The quality of an economy’sproducts (not only its prices) and the effectiveness of theproduction processes determine the productivity of firmsin this phase.To achieve this, nations need to improve theefficiency of their goods markets, labor markets, and finan-cial markets.They also need to have an improved educa-tion and training system and to have access to the besttechnologies (even if they need to import them fromabroad). Because competitiveness at this level is foundedon efficiency, access to larger markets allows business toexploit economies of scale.20

Finally, in the third stage, which we call innovation-driven stage, successful economies can no longer competein price or even quality because their own success hasincreased prices (especially wages) so much that they canno longer compete by producing the same goods. It istime for these economies to produce “different” goods,innovative products and practices using the most advancedmethods of production and organization. In this phase,businesses need to increase their sophistication by organiz-ing in clusters and by opting for advanced and superioroperations. Firms compete with unique strategies.Institutions and incentives supporting innovation becomethe central part of economic competitiveness.

Of course, each of the 12 pillars of competitivenessoutlined in the previous section matter for every one ofthe stages of development. But different factors matter dif-ferently for countries in different stages. For example,although the ability to innovate matters for all nations, it isundoubtedly more important for advanced countries thanfor 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 ineach of the three stages.To this end, we group the pillarsthat we think are more important in the factor-drivenstage into what we call basic requirements. Basic require-ments include institutions (1st pillar), physical infrastruc-tures (2nd pillar), basic human capital (first part of the 5thpillar), macroeconomic stability (3rd pillar), and personalsecurity (4th pillar).

We group the pillars that are more important in theefficiency-driven stage into what we call efficiency enhancers.The efficiency enhancers include goods market efficiency(6th pillar), labor market efficiency (7th pillar), financialmarket efficiency (8th pillar), advanced human capital(second part of the 5th pillar), technological readiness (9thpillar), and openness/market size (10th pillar).

Finally, we group the pillars that are more importantin the innovation-driven stage into what we call innovationand sophistication factors, which includes business sophistica-tion and innovation, our 11th and 12th pillars respectively.

An important practical advantage of framing theprocess of economic development in stages is that it helpscountries prioritize the areas in which they should focustheir attention. By giving more weight to some pillars thanto others, the analysis presented in this chapter can be usedas a tool for countries to pay attention to the pillars that aremore important for their stage of development. Countriesin stage 1 that score low in innovation or in businesssophistication should not worry too much. Countries instage 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 issummarized in Figure 1.

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Figure 1: The twelve pillars of competitiveness

Once the three basic groups are defined, the index ofcompetitiveness is constructed as a weighted average ofthe three groups. In other words,

GCI = �1 x basic requirements + �2 x efficiency enhancers + �3 x innovation factors (Eq 1)

where �1, �2, and �3 are the weights that each subindexgets in the overall index.21

The idea behind the concept of stages of develop-ment is that all components matter in all stages, but somematter more than others in different stages. In otherwords, the weights (the �’s) that each subindex gets in theoverall GCI depend on the stage of a particular country.The exact weights of each of the three groups are dis-played in Table 1. In the factor-driven stage, the basicrequirements have 50 percent, the efficiency enhancershave a weight of 40 percent, and the innovation andsophistication factors have small weight of 10 percent.

Table 1: Weights of the three main groups of pillars ateach stage of development

Innovation and Basic Efficiency Sophistication

Weights (�’s) Requirements Enhancers Factors

Factor-Driven Stage 50 percent 40 percent 10 percentEfficiency-Driven Stage 40 percent 50 percent 10 percentInnovation-Driven Stage 30 percent 40 percent 30 percent

In the efficiency-driven stage, the weights of the basicrequirements and the efficiency enhancers are reversed(that is, 40 percent and 50 percent respectively), while theweight of the innovation and sophistication factorsremains at 10 percent.

Finally, in the innovation-driven stage, the weight ofthe basic requirements falls to 30 percent, the weight ofthe efficiency enhancers goes back to 40 percent whilethat of the innovation and sophistication factors increasesto 30 percent.22

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Basic Requirements

Key for Factor-DrivenEconomies

Efficiency Enhancers

Key for Efficiency-DrivenEconomies

Innovation andSophistication Factors

Key for Innovation-DrivenEconomies

The Twelve Pillars of Competitiveness

1. Institutions2. Infrastructures3. Macroeconomic Stability4. Personal Security

5a. Basic Human Capital

5b. Advanced Human Capital6. Good Market Efficiency7. Labor Market Efficiency8. Financial Market Efficiency9. Technological Readiness

10. Openness/Market Size

11. Business Sophistication12. Innovation

Principle 3. TransitionsThe third principle on which the new GCI index isfounded is that, as economies develop, they move fromone stage to the next in a smooth fashion rather than inabrupt jumps.23 Thus, the weights of each of the subindex-es (the �’s in equation 1), change smoothly as a countrydevelops.This means that we have five groups of countries:the three groups that belong to the three stages describedabove, plus the countries that are moving from stage 1 tostage 2 plus those that are moving from stage 2 to 3.

In practice, the allocation of countries to each groupis 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 frac-tion of its exports in the form of primary goods isabove 70 percent.24 A total of 41 countries are in thisstage (see Table 2 for a list of countries).

2. A country with a per capita income betweenUS$3,000 and $9,000 that does not export more than70 percent in primary goods belongs to the secondstage.A total of 21 countries are in this stage.

3. A country with more than US$17,000 per capitaincome and less than 70 percent of the exports inprimary goods belongs to the third stage.A total of24 countries are in this stage.

4. Countries with income per capita between US$2,000and $3,000 are said to be in transition from stage 1 tostage 2.The shares of basic requirements for thesecountries decline continuously from 50 percent to 40percent and the share of efficiency enhancers contin-uously increase from 40 percent to 50 percent as thelevel of income increases from $2,000 to $3,000.Notice that, because the share of the innovation fac-tors is 10 percent in both stage 1 and stage 2,economies in transition between these two stages donot suffer changes in the share of innovation factors.The precise formula for the change in these shares isgiven in the next section.25 A total of 10 countries arein this transitional phase.

5. Countries with income per capita between US$9,000and $17,000 are said to be in transition betweenstages 2 and 3. For these countries, the shares of basicrequirements continuously decline from 40 percent to30 percent, the share of efficiency enhancers declinesfrom 50 percent to 40 percent and the share of inno-vation factors increases from 10 percent to 30 per-cent.A total of 8 countries move along this transition.

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 basicrequirements get a 50 percent weight for countries thatare unambiguously in stage 1 and a 40 percent for coun-tries that are in stage two. For countries in between, theweight smoothly declines from 50 percent to 40 percentas their level of income increases. Similarly, for countriesin the third stage of development, the basic requirementssubindex weight is 30 percent.Thus, for countries thatmove along the transition between the second and thirdstages, the weight of this subindex smoothly declines from40 percent to 30 percent.The relation between the weightof the basic factors and the level of development is depict-ed in Figure 2.

Similarly, the weights of the efficiency enhancerscomponent gets a 40 percent weight for countries in stage1, a 50 percent weight for countries in stage 2, andsmoothly increases from 40 percent to 50 percent as thecountry grows between these two stages.The weight thensmoothly declines back to 40 percent as countries movebetween stages 2 and 3.The evolution of the importanceof efficiency factors as the economy develops is depictedin Figure 3.

Finally, the weight of the innovation factors remainsconstant at 10 percent between stages 1 and 2, and it thensmoothly increases to 30 percent as countries movebetween stages 2 and 3.The evolution of the weight ofinnovation factors in the overall global competitivenessindex is depicted in Figure 4.

One advantage of allowing for the weights of eachsubcomponent to change smoothly along the transition isthat countries that do not prepare for more advancedphases of development as they grow out of stage 1 intostage 2 get penalized.We think that countries that do notadapt their economic environments to the new stages tendto lose competitiveness.The reason is that wages tend toincrease in economies that grow.Thus, countries that growfrom the factor-driven stage to the efficiency-driven stagetend to lose their ability to compete in prices and lowcosts. In other words, as economies in stage 1 grow, theyslowly lose their competitiveness.A good index of com-petitiveness, therefore, must capture this phenomenon andmust therefore partly penalize economies that, whileapproaching stage 2, do not prepare for the challengesinvolved in this more sophisticated phase of economicdevelopment. Our index has this property because, forcountries that do not adapt to the more advanced phases,the values of the efficiency enhancers tend to be lowerthan the values of the basic requirements. By smoothlyreducing the weights of the basic requirements andincreasing those of the efficiency enhancers, we tend tolower the overall value of the index for those countries astheir economy grows.

We do a similar thing for economies that move alongthe transition from stage 2 to stage 3.

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Table 2: List of countries in each stage

Stage 1 Transition from 1 to 2 Stage 2 Transition from 2 to 3 Stage 3

Income of less than US$2,000 Income between Income of more than US$3,000 Income between Income of more or more than 70% primary exports US$2,000 and $3,000 and less than $9,000 US$9,000 and $17,000 than US$17,000

1 Algeria** Brazil Argentina Cyprus Australia2 Angola* Bulgaria Botswana Greece Austria3 Bahrain** Ecuador Chile Israel Belgium4 Bangladesh El Salvador Costa Rica Korea Canada5 Bolivia Jamaica Croatia Malta Denmark6 Bosnia and Hercegovina Macedonia Czech Republic Portugal Finland7 Chad* Peru Estonia Slovenia France 8 China Romania Hungary Taiwan Germany9 Colombia Thailand Latvia Hong Kong SAR10 Dominican Republic Tunisia Lithuania Iceland11 Egypt Malaysia Ireland12 Ethiopia Mauritius Italy13 Gambia Mexico Japan14 Georgia Panama Luxembourg15 Ghana Poland Netherlands16 Guatemala Russian Federation New Zealand17 Honduras Slovak Republic Norway 18 India South Africa Singapore19 Indonesia Trinidad and Tobago Spain20 Jordan Turkey Sweden21 Kenya Uruguay Switzerland22 Madagascar United Arab Emirates23 Malawi United Kingdom24 Mali* United States25 Morocco26 Mozambique27 Namibia28 Nicaragua29 Nigeria*30 Pakistan31 Paraguay32 Philippines33 Serbia and Montenegro34 Sri Lanka35 Tanzania36 Uganda37 Ukraine38 Venezuela**39 Vietnam40 Zambia41 Zimbabwe

* 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.

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Figure 2: The importance of basic requirements at various stages of development

50%

40%

30%

$2,000 $3,000 $9,000 $17,000

Income per capita (not to scale)

Wei

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ts (�

1)

Transition TransitionStage 1 from 1 to 2 Stage 2 from 2 to 3 Stage 3

Figure 3: The importance of efficiency enhancers at various stages of development

50%

40%

30%

$2,000 $3,000 $9,000 $17,000

Income per capita (not to scale)

Wei

ght o

f effi

cien

cy e

nhan

cers

(�2)

Transition TransitionStage 1 from 1 to 2 Stage 2 from 2 to 3 Stage 3

Summary of the methodology: Building the GlobalCompetitiveness Index

Step 1: Construct the twelve pillarsFollowing the tradition of both our predecessors (theGrowth Competitive Index and the Business CompetitiveIndex), our index combines hard data and Survey datacollected by the World Economic Forum through itsExecutive Opinion Survey.

These data are combined to estimate the 12 pillars ofeconomic development described in Section 1.The exactallocation of Survey questions and hard data to each of thepillars is described in Appendix 1.All questions get thesame weight within subsections of the pillar.26

Step 2: Build the three subindexesEach pillar is allocated to a subindex as follows:

Subindex 1: Basic Requirements:1st Pillar: Institutions2nd Pillar: Infrastructures3rd Pillar: Macroeconomic Stability4th Pillar: Security5th Pillar: Basic Human Capital

Subindex 2: Efficiency Enhancers:5th Pillar:Advanced Human Capital6th Pillar: Goods Market Efficiency7th Pillar: Labor Market Efficiency8th Pillar: Financial Market Efficiency9th Pillar:Technological Readiness10th Pillar: Openness and Market Size

Subindex 3: Innovation Factors:11th Pillar: Business Sophistication12th Pillar: Innovation

Step 3: Allocate countries to stages of developmentWe then allocate each of the 104 countries to one of thethree stages of development (or the transitional stages) asdescribed in Section 3.The results are displayed in Table 2.

Step 4: Estimate the shares that each subindex gets for eachcountryOnce a country is assigned to a stage of development, weassign the weights that each of the three subindexes getsfor each country. Remember that the theory of stages ofdevelopment suggests that, for less advanced economies,the basic requirements are more important; for intermedi-ate economies, the efficiency enhancers are key; and foradvanced countries, the innovation factors are central.Theexact weights are depicted in Table 1.

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Figure 4: The importance of innovation factors at various stages of development

30%

20%

10%

$2,000 $3,000 $9,000 $17,000

Income per capita (not to scale)

Wei

ght o

f inn

ovat

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fact

ors

(�3)

Transition TransitionStage 1 from 1 to 2 Stage 2 from 2 to 3 Stage 3

Step 5: Estimate the Global Competitiveness IndexThe Global Competitive Index is then estimated as theweighted average of the three subindexes (see Equation 1).

How to interpret the IndexWhen observing the index, some analysts might be puz-zled by the low value of the Global Competitive Index forcountries that have experienced high growth rates in thepast, or the high values obtained by countries with poorrecent economic growth performances.

First of all, we should remember that the Index is notmeant to capture anything to do with short-term businesscycles. In other words, highly competitive economies areas subject to short-term booms and recessions as noncom-petitive ones. Having experienced high or low growth ratesin the recent past has little to do with the competitivenessof a nation because competitiveness is not a vaccineagainst business cycles.This is rightly captured by ourIndex.

Second, and perhaps more importantly, low currentcompetitiveness is consistent with elevated growth rates inthe past because the process of economic growth is deter-mined both by the level of productivity and by the “con-vergence” components of a country. Convergence growth isthe growth that economies experience as various types ofinvestment react to changes in the medium- to long-termeconomic environment.As an example, imagine that acountry, which in 1980 had very low levels of productivityand efficiency, increased those levels dramatically between1980 and 2004.The new levels of competitiveness maystill not be the best in the world, but they are much largerthan they were 24 years ago. Under those circumstances,we expect the growth rate of this country to have beenvery large over the last 24 years, yet our index will proba-bly give this nation a middle ranking in the world.Similarly, a country with a high level of productivity mayhave experienced very low growth rates of GDP per capi-ta over a period of 20 years if this level of competitivenesshas not improved much in the past.

In other words, the values of the GlobalCompetitiveness Index should not necessarily be correlat-ed with the past growth performance of a country.Changes in the value of the index over the medium tolong term, on the other hand, should be correlated withthe rate of economic growth.

ResultsTable 3 displays the results of computing the GlobalCompetitiveness Index for 2004.The countries are rankedin decreasing order.The second column contains the valueof the index and the third column the rank number.Thefollowing six columns contain the information (value and

rank) for each of the three subindexes: the basic require-ments subindex, the efficiency enhancers subindex, andthe innovation factors subindex respectively.The nextthree tables decompose the index into its 12 pillars.

The most competitive country in the world is theUnited States, with an overall score of 5.21, followed byFinland (5.04), and Denmark (4.95), Switzerland (4.93),and Sweden (4.92), which conclude the top five.TheUnited States does not score particularly well in basicrequirements (rank 18: the main cause is its dismal macro-economic stability—rank 83—and its not-so-great per-formance in security—rank 37), but it is the world’s leaderin both efficiency enhancers and innovation factors. Sincethe United States is in the third stage of development (theinnovation stage), the weight of the basic requirements isrelatively minor, so the other two subindexes put thiscountry in the leading position. Finland leads the world inbasic requirements, but it only ranks 6th in efficiencyenhancers (it is interesting to notice its 18th place in labormarket efficiency) and 4th in innovation factors. Denmarkis 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 ofGermany 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 competitivecountry in the world is Angola (2.55), closely followed by Chad (2.64).Angola ranks 104th in basic requirementsand 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), andMozambique (100th with 2.98).These countries score dismally almost across the board in the pillars that aremost important for their level of development (the excep-tion is the relatively good macroeconomic performanceexperienced by Mozambique—rank 42nd in the world).

The next five countries at the bottom of the compet-itiveness rankings are not all African, and they include twoEuropean countries: the former republics of YugoslaviaBosnia-Hercegovina (3.13) and Serbia-Montenegro (3.16),two African countries Mali (3.13) and Tanzania (3.14), andone Latin American, Bolivia (3.19).

Averaging out the value of the index by region (seeFigure 5), we see that the most competitive region in theworld is North America.The values of the second andthird regions (Western Europe and East Asia) are quiteclose to each other.The fourth position is for the MiddleEast and North Africa.The next three regions (EasternEurope, South and Central America, and South andCentral Asia respectively) are also quite close. Sub-SaharanAfrica closes the ranking in the last position.

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* Middle East and North Africa

3.0

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3.8

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Figure 5: Global competitiveness by region

North America

Western Europe

East Asia-Pacific

MENA* Eastern Europe Central andSouth America

South-CentralAsia

Sub-SaharanAfrica

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United States 5.21 1 5.50 18 5.02 1 5.18 1Finland 5.04 2 6.03 1 4.54 6 4.70 4Denmark 4.95 3 5.99 2 4.55 5 4.42 8Switzerland 4.93 4 5.88 6 4.45 8 4.61 6Sweden 4.92 5 5.76 8 4.45 7 4.69 5Germany 4.86 6 5.75 10 4.27 14 4.74 3Singapore 4.85 7 5.89 5 4.60 4 4.15 14Hong Kong SAR 4.81 8 5.95 4 4.65 2 3.90 20United Kingdom 4.80 9 5.48 20 4.61 3 4.38 9Japan 4.79 10 5.35 22 4.26 15 4.94 2Taiwan 4.72 11 5.31 23 4.38 10 4.44 7Netherlands 4.72 12 5.59 14 4.36 11 4.32 10Iceland 4.70 13 5.80 7 4.42 9 3.97 19Norway 4.69 14 5.96 3 4.25 16 4.01 18Canada 4.66 15 5.58 15 4.30 12 4.23 13Australia 4.63 16 5.70 11 4.28 13 4.04 17France 4.60 17 5.49 19 4.15 20 4.30 11Austria 4.57 18 5.61 12 4.13 21 4.11 16Belgium 4.54 19 5.51 17 4.12 22 4.14 15New Zealand 4.54 20 5.60 13 4.25 17 3.87 23Luxembourg 4.52 21 5.76 9 4.16 19 3.75 24Israel 4.48 22 5.06 34 4.18 18 4.28 12Malaysia 4.47 23 5.36 21 3.91 25 3.69 26Estonia 4.46 24 5.31 24 4.03 24 3.26 40Bahrain 4.39 25 5.20 29 3.71 30 3.01 55Korea 4.38 26 5.30 25 3.87 26 3.87 22Ireland 4.38 27 5.23 27 4.11 23 3.88 21Jordan 4.32 28 5.25 26 3.49 45 3.04 51Chile 4.29 29 5.20 30 3.76 29 3.27 38Tunisia 4.25 30 5.17 31 3.55 40 3.32 35United Arab Emirates 4.21 31 5.55 16 3.81 27 3.40 33China 4.20 32 4.85 41 3.59 38 3.43 31Thailand 4.17 33 4.90 38 3.57 39 3.31 36Spain 4.10 34 5.08 33 3.79 28 3.53 29Slovenia 4.09 35 5.13 32 3.63 32 3.41 32South Africa 4.08 36 4.76 46 3.63 33 3.60 27India 4.07 37 4.53 56 3.60 37 3.69 25Czech Republic 4.06 38 4.83 42 3.60 36 3.35 34Lithuania 4.06 39 4.80 43 3.61 34 3.30 37Portugal 4.05 40 5.21 28 3.64 31 3.20 41Slovak Republic 4.03 41 4.78 45 3.61 35 3.16 44Malta 4.01 42 5.01 36 3.52 42 2.78 74Namibia 3.98 43 4.80 44 3.24 56 2.83 68Latvia 3.97 44 4.86 40 3.47 47 2.93 63Morocco 3.97 45 4.70 49 3.27 53 3.14 45Hungary 3.96 46 4.75 47 3.51 44 3.08 48Egypt 3.95 47 4.67 50 3.23 57 3.18 43Indonesia 3.92 48 4.56 55 3.28 52 3.27 39Brazil 3.88 49 4.39 67 3.51 43 3.55 28Mauritius 3.86 50 4.86 39 3.24 55 2.98 59Greece 3.84 51 4.94 37 3.47 48 3.13 47Cyprus 3.83 52 5.02 35 3.53 41 2.93 62Costa Rica 3.83 53 4.57 53 3.36 49 3.18 42Panama 3.81 54 4.65 51 3.32 51 2.89 64El Salvador 3.80 55 4.51 58 3.21 59 2.69 80Italy 3.80 56 4.56 54 3.48 46 3.48 30Romania 3.75 57 4.48 61 3.19 60 2.88 65Botswana 3.75 58 4.62 52 3.25 54 2.79 73Dominican Republic 3.71 59 4.42 64 3.07 69 2.70 79Mexico 3.70 60 4.47 62 3.21 58 3.02 54Vietnam 3.68 61 4.48 60 2.95 79 2.63 87Algeria 3.68 62 4.71 48 2.70 92 2.50 91Trinidad and Tobago 3.68 63 4.50 59 3.16 62 2.96 60Russian Federation 3.67 64 4.42 65 3.18 61 3.14 46

(cont’d)

Overall Index BASIC REQUIREMENTS EFFICIENCY ENHANCERS INNOVATION FACTORSCountry Score Rank Score Rank Score Rank Score Rank

Three main components

Table 3: The Global Competitiveness Index

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Jamaica 3.66 65 4.23 71 3.33 50 3.00 56Sri Lanka 3.65 66 4.31 68 3.03 70 2.81 71Turkey 3.62 67 4.41 66 3.10 66 3.08 49Ghana 3.62 68 4.18 75 3.11 65 2.82 69Colombia 3.61 69 4.15 78 3.10 67 3.00 57Bulgaria 3.60 70 4.24 70 3.08 68 2.68 81Uruguay 3.57 71 4.52 57 2.98 76 2.66 82Poland 3.57 72 4.25 69 3.13 63 2.99 58Ukraine 3.55 73 4.18 74 2.90 82 3.03 53Philippines 3.55 74 4.03 82 3.11 64 2.84 67Argentina 3.54 75 4.44 63 2.96 78 2.81 70Peru 3.53 76 4.19 73 3.00 74 2.64 85Nigeria 3.53 77 4.08 80 2.97 77 3.07 50Uganda 3.50 78 4.02 83 3.01 73 2.87 66Croatia 3.46 79 4.21 72 3.00 75 2.80 72Venezuela 3.45 80 4.16 77 2.77 88 2.64 86Gambia 3.45 81 3.94 89 3.01 72 2.77 75Macedonia, FYR 3.40 82 4.08 81 2.83 85 2.57 89Guatemala 3.37 83 4.02 84 2.75 90 2.60 88Kenya 3.37 84 3.72 93 3.01 71 3.03 52Madagascar 3.36 85 3.97 87 2.76 89 2.71 78Georgia 3.35 86 3.94 88 2.85 83 2.36 95Pakistan 3.35 87 3.78 92 2.91 81 2.94 61Ecuador 3.34 88 4.18 76 2.55 98 2.44 93Honduras 3.29 89 4.13 79 2.49 99 2.30 97Paraguay 3.26 90 3.99 85 2.60 95 2.25 99Zambia 3.25 91 3.61 96 2.93 80 2.76 76Nicaragua 3.24 92 3.98 86 2.58 96 2.16 102Malawi 3.22 93 3.70 94 2.80 87 2.57 90Bangladesh 3.20 94 3.81 91 2.63 94 2.41 94Bolivia 3.19 95 3.90 90 2.55 97 2.18 101Serbia and Montenegro 3.16 96 3.55 98 2.80 86 2.64 84Tanzania 3.14 97 3.47 100 2.84 84 2.73 77Bosnia and Hercegovina 3.13 98 3.66 95 2.67 93 2.35 96Mali 3.13 99 3.60 97 2.70 91 2.48 92Mozambique 2.98 100 3.53 99 2.48 101 2.26 98Zimbabwe 2.96 101 3.41 102 2.48 100 2.65 83Ethiopia 2.88 102 3.42 101 2.35 102 2.23 100Chad 2.64 103 3.09 103 2.23 104 2.04 103Angola 2.55 104 2.92 104 2.26 103 1.88 104

Overall Index BASIC REQUIREMENTS EFFICIENCY ENHANCERS INNOVATION FACTORSCountry Score Rank Score Rank Score Rank Score Rank

Three main components

Table 3: The Global Competitiveness Index (cont’d.)

Table 4: Global Competitiveness Index: Basic requirements

2. Physical 5. Basic 1. Institutions infrastructures 3. Macro stability 4. Security human capital

Country Score Rank Score Rank Score Rank Score Rank Score Rank

1 United States 5.22 8 6.12 9 4.79 83 4.44 37 6.91 232 Finland 5.50 2 6.28 7 5.71 12 5.74 1 6.94 183 Denmark 5.37 5 6.61 1 5.55 17 5.52 3 6.92 214 Switzerland 5.16 11 6.43 4 5.52 22 5.34 6 6.97 45 Sweden 5.13 13 6.16 8 5.43 31 5.13 15 6.98 26 Germany 5.15 12 6.44 3 5.02 65 5.19 13 6.94 137 Singapore 5.53 1 6.34 6 5.79 6 5.29 7 6.49 748 Hong Kong SAR 5.18 9 6.48 2 5.75 9 5.38 5 6.93 209 United Kingdom 5.43 4 5.45 20 5.10 54 4.56 30 6.86 3110 Japan 4.73 20 6.12 10 4.60 90 4.33 42 6.99 111 Taiwan 4.65 22 5.36 21 5.47 29 4.54 31 6.52 7212 Netherlands 5.18 10 6.02 12 5.31 35 4.49 34 6.94 1513 Iceland 5.45 3 5.77 17 5.19 47 5.64 2 6.97 314 Norway 5.13 14 5.85 15 6.41 1 5.47 4 6.95 915 Canada 5.05 15 5.87 13 5.41 32 4.61 26 6.96 616 Australia 5.26 7 5.83 16 5.49 23 4.95 17 6.96 517 France 4.60 26 6.37 5 5.04 62 4.51 33 6.96 818 Austria 4.99 16 5.72 18 5.32 34 5.08 16 6.95 1019 Belgium 4.62 23 6.09 11 5.22 44 4.66 23 6.94 1620 New Zealand 5.31 6 4.96 25 5.53 21 5.23 9 6.94 1721 Luxembourg 4.98 17 5.85 14 5.81 5 5.23 10 6.94 1422 Israel 4.53 28 4.87 26 4.64 89 4.32 44 6.95 1123 Malaysia 4.74 19 5.30 22 5.53 19 4.59 27 6.63 6224 Estonia 4.50 30 4.74 31 5.77 7 4.73 20 6.80 4125 Bahrain 4.60 25 4.76 30 5.22 43 4.63 25 6.81 3626 Korea 3.87 50 5.19 23 6.06 4 4.54 32 6.86 2927 Ireland 4.78 18 4.11 42 5.54 18 4.84 19 6.92 2228 Jordan 4.48 31 4.33 37 5.43 30 5.22 11 6.76 4729 Chile 4.53 29 4.62 34 5.59 15 4.39 39 6.88 2830 Tunisia 4.61 24 4.34 36 5.29 37 4.85 18 6.76 4631 United Arab Emirates 4.69 21 5.52 19 5.53 20 5.27 8 6.74 5032 China 3.91 47 3.49 60 6.06 3 4.14 53 6.64 6033 Thailand 4.01 41 4.30 39 5.74 10 4.15 52 6.28 8034 Spain 4.10 39 4.80 28 5.48 27 4.08 56 6.95 1235 Slovenia 3.97 43 4.55 35 5.49 24 4.71 22 6.91 2436 South Africa 4.59 27 4.87 27 5.21 45 3.41 82 5.73 8637 India 3.92 46 3.35 63 4.68 87 4.33 43 6.35 7938 Czech Republic 3.44 72 4.66 33 5.14 51 4.00 59 6.90 2639 Lithuania 3.89 49 4.17 40 5.29 38 3.87 65 6.80 3740 Portugal 4.16 36 4.68 32 5.14 52 5.19 14 6.90 2541 Slovak Republic 3.75 56 3.86 48 5.24 41 4.19 49 6.86 3042 Malta 4.24 33 3.86 47 4.83 77 5.20 12 6.94 1943 Namibia 4.46 32 5.04 24 5.25 40 3.77 69 5.50 8844 Latvia 3.57 65 4.02 43 5.64 14 4.31 45 6.75 4945 Morocco 4.08 40 3.74 53 5.04 60 4.48 35 6.16 8146 Hungary 3.80 54 3.75 52 4.97 68 4.38 40 6.83 3547 Egypt 3.97 42 3.84 50 4.81 81 4.10 55 6.62 6548 Indonesia 3.87 51 3.93 45 5.08 58 3.49 80 6.42 7549 Brazil 3.80 55 3.53 58 4.32 96 3.65 75 6.64 6150 Mauritius 3.80 53 4.17 41 5.36 33 4.19 48 6.78 4451 Greece 3.94 45 4.33 38 4.95 70 4.65 24 6.85 3352 Cyprus 4.19 35 4.78 29 4.85 75 4.58 29 6.68 5553 Costa Rica 3.96 44 3.14 70 4.84 76 4.04 58 6.90 2754 Panama 3.51 68 3.94 44 5.09 57 3.91 62 6.80 4055 El Salvador 3.90 48 3.86 49 4.96 69 3.11 92 6.70 5456 Italy 3.38 77 3.87 46 4.86 74 3.74 70 6.96 757 Romania 3.24 80 3.31 64 5.15 50 4.07 57 6.62 6458 Botswana 4.15 38 3.81 51 5.67 13 4.38 40 5.06 9059 Dominican Republic 3.13 84 3.15 69 5.10 56 4.11 54 6.60 6860 Mexico 3.50 69 3.39 62 5.31 36 3.40 83 6.77 4561 Vietnam 3.67 61 2.45 91 5.48 26 4.20 47 6.58 7062 Algeria 3.50 70 3.20 67 6.31 2 3.90 63 6.62 6363 Trinidad and Tobago 3.62 64 3.60 55 5.58 16 2.94 96 6.75 4864 Russian Federation 2.99 93 3.59 56 5.72 11 3.14 90 6.64 59

(cont’d)

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Table 4: Global Competitiveness Index: Basic requirements (cont’d.)

2. Physical 5. Basic 1. Institutions infrastructures 3. Macro stability 4. Security human capital

Country Score Rank Score Rank Score Rank Score Rank Score Rank

65 Jamaica 3.72 58 3.55 57 4.35 95 2.72 98 6.79 4366 Sri Lanka 3.70 59 2.79 80 4.66 88 3.66 74 6.73 5167 Turkey 3.48 71 3.21 66 4.54 92 4.18 50 6.66 5768 Ghana 4.20 34 2.88 75 4.75 84 4.73 21 4.32 9569 Colombia 3.54 67 3.06 73 4.98 67 2.43 103 6.73 5270 Bulgaria 3.07 88 3.18 68 5.18 48 3.00 95 6.79 4271 Uruguay 3.74 57 3.63 54 3.95 100 4.43 38 6.85 3472 Poland 3.17 82 3.07 72 5.07 59 3.07 93 6.86 3273 Ukraine 2.75 100 3.48 61 5.49 25 3.28 88 5.92 8474 Philippines 3.39 75 2.55 87 5.04 61 2.67 101 6.51 7375 Argentina 3.15 83 3.52 59 5.26 39 3.50 79 6.80 3876 Peru 3.23 81 2.72 81 5.10 55 3.34 84 6.59 6977 Nigeria 3.32 78 2.35 93 5.76 8 3.32 85 5.65 8778 Uganda 3.56 66 2.47 88 4.82 79 3.42 81 5.83 8579 Croatia 3.10 85 3.30 65 4.90 72 3.82 67 5.94 8380 Venezuela 2.89 98 3.08 71 5.02 64 3.02 94 6.80 3981 Gambia 4.15 37 2.90 74 3.70 101 4.45 36 4.48 9482 Macedonia, FYR 3.04 89 2.83 77 5.10 53 2.69 100 6.71 5383 Guatemala 3.03 90 2.64 83 5.16 49 2.70 99 6.56 7184 Kenya 3.64 63 2.42 92 4.74 85 2.56 102 5.23 8985 Madagascar 3.25 79 2.33 94 4.53 94 3.71 71 6.04 8286 Georgia 3.03 91 2.47 89 4.57 91 3.29 87 6.36 7787 Pakistan 2.96 94 2.81 78 5.03 63 3.78 68 4.31 9688 Ecuador 2.91 97 2.60 85 5.47 28 3.30 86 6.60 6789 Honduras 3.01 92 2.83 76 5.01 66 3.21 89 6.61 6690 Paraguay 2.69 103 2.23 96 4.83 78 3.53 78 6.68 5691 Zambia 3.67 62 2.68 82 4.72 86 4.16 51 2.80 10292 Nicaragua 3.08 86 2.19 98 4.07 99 3.90 64 6.66 5893 Malawi 3.84 52 2.55 86 3.38 103 3.92 61 4.79 9294 Bangladesh 2.80 99 2.31 95 5.20 46 2.37 104 6.35 7895 Bolivia 2.74 101 2.17 100 4.54 93 3.70 72 6.37 7696 Serbia and Montenegro 3.07 87 2.46 90 4.07 98 3.93 60 4.19 9897 Tanzania 3.44 73 2.63 84 4.82 80 3.70 73 2.78 10398 Bosnia and Hercegovina 2.95 96 2.18 99 4.80 82 3.57 76 4.80 9199 Mali 3.68 60 2.16 101 4.87 73 4.58 28 2.72 104100 Mozambique 2.95 95 2.14 102 5.23 42 3.14 91 4.20 97101 Zimbabwe 3.39 76 2.80 79 2.45 104 3.87 66 4.53 93102 Ethiopia 3.42 74 2.22 97 4.23 97 4.28 46 2.96 101103 Chad 2.69 102 1.36 104 4.91 71 2.93 97 3.58 99104 Angola 2.47 104 1.73 103 3.52 102 3.55 77 3.35 100

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Table 5: Global Competitiveness Index: Efficiency enhancers

5. Advanced 6. Goods market 7. Labor market 8. Financial 9. Technological 10. Openess and human capital efficiency efficiency market efficiency readiness market size

Country Score Rank Score Rank Score Rank Score Rank Score Rank Score Rank

1 United States 5.01 4 4.59 3 5.05 3 5.93 3 5.32 4 4.20 12 Finland 5.36 1 4.29 14 4.33 18 5.88 4 5.34 3 2.05 183 Denmark 5.06 3 4.33 12 4.64 9 5.88 5 5.31 5 2.12 154 Switzerland 4.95 6 4.36 10 4.79 5 5.59 14 4.86 17 2.15 125 Sweden 5.10 2 4.14 21 4.13 25 5.77 8 5.50 2 2.06 166 Germany 4.62 19 4.22 17 3.51 82 5.25 22 5.09 10 2.93 37 Singapore 4.81 12 4.80 2 5.11 2 5.61 12 5.22 7 2.02 198 Hong Kong SAR 4.24 26 4.90 1 5.37 1 6.00 2 5.27 6 2.16 109 United Kingdom 4.72 17 4.53 4 4.67 8 6.27 1 5.03 14 2.47 510 Japan 4.75 15 4.02 25 4.35 16 4.43 52 5.16 8 2.82 411 Taiwan 4.96 5 4.50 5 4.72 7 4.89 30 5.10 9 2.12 1412 Netherlands 4.84 9 4.35 11 4.11 31 5.77 9 4.86 16 2.21 813 Iceland 4.73 16 4.27 15 4.91 4 5.27 21 5.66 1 1.67 2914 Norway 4.79 14 4.11 23 4.43 15 5.48 15 5.06 12 1.64 3315 Canada 4.83 10 4.32 13 4.48 13 5.61 13 4.69 20 1.88 2116 Australia 4.89 7 4.38 8 4.19 23 5.76 10 4.92 15 1.54 3717 France 4.82 11 4.06 24 3.57 78 5.43 17 4.60 21 2.44 618 Austria 4.81 13 4.19 18 3.81 56 5.14 26 4.86 18 1.99 2019 Belgium 4.88 8 3.97 27 3.81 57 5.33 18 4.59 22 2.15 1320 New Zealand 4.66 18 4.49 6 4.33 17 5.77 7 4.71 19 1.52 3921 Luxembourg 3.89 35 4.39 7 4.46 14 5.84 6 4.52 24 1.83 2422 Israel 4.51 20 3.88 31 4.17 24 5.43 16 5.04 13 2.05 1723 Malaysia 3.90 34 4.18 19 4.56 10 4.93 29 4.13 28 1.74 2624 Estonia 4.34 24 4.12 22 4.55 11 5.23 23 4.59 23 1.34 6525 Bahrain 3.56 51 4.14 20 4.32 19 5.22 24 3.72 39 1.30 6826 Korea 4.49 22 3.92 28 3.47 85 4.13 67 5.06 11 2.16 927 Ireland 4.50 21 4.25 16 4.00 37 5.71 11 4.34 25 1.86 2328 Jordan 3.68 43 3.72 37 3.99 38 4.65 40 3.48 45 1.43 5629 Chile 3.70 41 3.92 29 4.12 26 5.32 19 4.08 32 1.40 5930 Tunisia 3.97 31 3.89 30 4.11 32 4.42 53 3.47 47 1.46 5131 United Arab Emirates 3.52 53 4.38 9 4.77 6 4.68 38 4.02 33 1.51 4132 China 3.23 61 3.58 43 3.98 40 3.77 82 3.24 54 3.74 233 Thailand 3.65 46 3.87 32 4.48 12 4.30 59 3.48 46 1.65 3234 Spain 4.30 25 3.72 36 3.64 75 5.05 28 4.12 29 1.88 2235 Slovenia 4.35 23 3.72 35 3.70 66 4.16 65 4.22 27 1.65 3136 South Africa 3.57 50 3.99 26 3.77 61 5.29 20 3.71 40 1.44 5437 India 3.67 45 3.67 38 3.78 60 4.85 32 3.44 48 2.16 1138 Czech Republic 4.00 30 3.43 50 4.12 27 4.16 66 4.27 26 1.60 3439 Lithuania 4.12 27 3.51 45 3.88 46 4.86 31 3.78 37 1.48 4740 Portugal 3.78 38 3.65 39 3.86 47 5.17 25 3.95 34 1.47 5041 Slovak Republic 3.90 33 3.63 41 4.23 20 4.63 42 3.87 36 1.38 6142 Malta 3.73 40 3.44 49 3.66 72 4.69 36 4.11 30 1.48 4643 Namibia 2.84 78 3.59 42 3.91 45 4.76 34 3.07 60 1.26 7644 Latvia 4.00 29 3.33 58 4.03 36 4.47 49 3.69 41 1.31 6745 Morocco 3.14 67 3.64 40 4.12 28 4.32 58 2.91 67 1.48 4846 Hungary 3.96 32 3.40 52 3.92 43 4.55 44 3.73 38 1.49 4347 Egypt 3.44 56 3.42 51 3.91 44 3.97 72 3.15 58 1.51 4048 Indonesia 3.27 60 3.74 34 3.66 74 4.28 60 2.99 64 1.75 2549 Brazil 3.61 48 3.48 48 3.82 52 4.76 33 3.69 42 1.69 2850 Mauritius 3.19 63 3.58 44 3.46 87 4.53 45 3.18 57 1.49 4551 Greece 4.04 28 3.50 46 3.57 77 4.67 39 3.56 44 1.47 4952 Cyprus 3.69 42 3.86 33 3.79 58 4.49 47 3.87 35 1.49 4453 Costa Rica 3.52 54 3.38 56 4.11 29 4.63 41 2.94 66 1.59 3554 Panama 3.09 69 3.20 71 3.82 54 5.08 27 3.40 49 1.34 6655 El Salvador 2.80 79 3.25 66 3.98 39 4.76 35 3.04 61 1.42 5856 Italy 3.85 36 3.30 61 3.14 102 4.08 68 4.11 31 2.38 757 Romania 3.68 44 3.04 77 3.73 65 4.07 69 3.24 53 1.40 6058 Botswana 3.03 71 3.50 47 4.20 22 4.50 46 2.94 65 1.29 7159 Dominican Republic 2.78 80 3.04 79 4.09 33 4.06 70 3.19 56 1.28 7560 Mexico 3.14 66 3.05 76 3.69 69 4.39 56 3.25 52 1.74 2761 Vietnam 2.85 77 3.32 59 4.08 34 3.72 85 2.46 88 1.28 7462 Algeria 2.77 81 3.02 80 3.57 76 3.32 100 2.31 94 1.18 9263 Trinidad and Tobago 3.17 65 3.34 57 3.82 53 4.56 43 2.84 72 1.24 8264 Russian Federation 3.75 39 3.22 70 4.03 35 3.61 91 2.81 73 1.66 30

(cont’d)

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Table 5: Global Competitiveness Index: Efficiency enhancers (cont’d.)

5. Advanced 6. Goods market 7. Labor market 8. Financial 9. Technological 10. Openess and human capital efficiency efficiency market efficiency readiness market size

Country Score Rank Score Rank Score Rank Score Rank Score Rank Score Rank

65 Jamaica 3.21 62 3.27 63 3.96 41 4.47 50 3.63 43 1.45 5266 Sri Lanka 2.87 76 3.30 60 3.51 81 4.41 54 2.71 78 1.35 6467 Turkey 3.18 64 3.26 65 3.68 70 3.68 88 3.30 50 1.50 4268 Ghana 2.71 86 3.39 54 3.95 42 4.69 37 2.72 76 1.22 8369 Colombia 3.08 70 3.18 73 3.66 73 4.40 55 2.84 71 1.44 5570 Bulgaria 3.63 47 3.23 69 3.66 71 3.75 83 3.01 62 1.22 8471 Uruguay 3.49 55 3.04 78 3.48 84 3.83 79 2.88 69 1.20 8872 Poland 3.83 37 2.90 87 3.23 99 3.99 71 3.29 51 1.58 3673 Ukraine 3.55 52 2.88 90 3.78 59 3.25 104 2.49 84 1.43 5774 Philippines 3.37 58 3.19 72 3.74 64 3.84 78 3.00 63 1.54 3875 Argentina 3.57 49 2.90 88 3.30 97 3.68 89 3.07 59 1.25 8076 Peru 3.03 72 2.92 85 3.57 79 4.47 48 2.75 75 1.26 7777 Nigeria 2.73 84 3.28 62 3.83 51 3.96 74 2.62 80 1.38 6278 Uganda 2.51 90 3.39 53 3.86 48 4.23 63 2.76 74 1.29 7279 Croatia 3.39 57 2.92 86 3.41 90 3.69 87 3.20 55 1.36 6380 Venezuela 2.88 75 2.62 96 3.39 91 3.72 84 2.87 70 1.16 9681 Gambia 2.54 87 3.39 55 4.11 30 4.28 61 2.48 87 1.25 8182 Macedonia, FYR 3.31 59 2.82 92 3.69 68 3.70 86 2.26 95 1.18 9183 Guatemala 2.33 94 2.81 93 3.48 83 3.86 77 2.71 77 1.29 7384 Kenya 2.76 82 3.24 68 3.76 62 4.36 57 2.65 79 1.29 7085 Madagascar 2.26 95 2.94 83 3.85 49 3.82 80 2.55 83 1.16 9486 Georgia 3.01 73 2.57 98 4.21 21 3.64 90 2.42 91 1.25 7987 Pakistan 2.18 98 3.27 64 3.23 100 4.44 51 2.90 68 1.44 5388 Ecuador 2.53 89 2.47 101 3.22 101 3.39 97 2.49 85 1.19 8989 Honduras 2.05 100 2.54 100 3.33 94 3.58 93 2.20 99 1.21 8690 Paraguay 2.37 93 2.87 91 3.31 95 3.57 94 2.42 90 1.06 10391 Zambia 2.54 88 3.11 74 3.82 55 4.27 62 2.58 81 1.26 7892 Nicaragua 2.40 91 2.41 102 3.55 80 3.96 75 2.08 101 1.08 10293 Malawi 2.37 92 2.93 84 3.69 67 4.18 64 2.33 93 1.30 6994 Bangladesh 2.21 96 2.97 81 3.42 89 3.81 81 2.23 96 1.16 9595 Bolivia 2.71 85 2.55 99 3.09 103 3.56 95 2.22 97 1.16 9796 Serbia and Montenegro 3.12 68 2.97 82 3.75 63 3.33 99 2.49 86 1.17 9397 Tanzania 2.20 97 3.25 67 3.84 50 3.97 73 2.57 82 1.19 9098 Bosnia and Hercegovina 2.88 74 2.89 89 3.37 92 3.46 96 2.21 98 1.20 8799 Mali 2.11 99 3.09 75 3.46 86 3.89 76 2.45 89 1.21 85100 Mozambique 1.99 101 2.66 95 3.28 98 3.61 92 2.19 100 1.14 98101 Zimbabwe 2.74 83 2.68 94 2.75 104 3.29 101 2.38 92 1.04 104102 Ethiopia 1.98 102 2.59 97 3.45 88 3.27 103 1.75 103 1.08 101103 Chad 1.62 103 2.33 103 3.30 96 3.28 102 1.72 104 1.09 100104 Angola 1.57 104 2.30 104 3.36 93 3.37 98 1.83 102 1.12 99

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11. Business sophistication 12. Innovation

Country Score Rank Score Rank

1 United States 5.66 1 4.70 12 Finland 5.34 4 4.06 33 Denmark 5.23 8 3.61 94 Switzerland 5.25 6 3.97 65 Sweden 5.33 5 4.06 46 Germany 5.49 3 3.98 57 Singapore 4.81 18 3.49 118 Hong Kong SAR 4.85 16 2.94 239 United Kingdom 5.24 7 3.52 1010 Japan 5.60 2 4.28 211 Taiwan 5.13 11 3.74 812 Netherlands 5.18 9 3.46 1213 Iceland 4.75 21 3.19 1814 Norway 4.83 17 3.18 1915 Canada 5.08 12 3.38 1416 Australia 4.87 15 3.21 1717 France 5.15 10 3.45 1318 Austria 4.99 14 3.24 1619 Belgium 4.99 13 3.29 1520 New Zealand 4.78 19 2.96 2221 Luxembourg 4.58 24 2.93 2422 Israel 4.75 20 3.82 723 Malaysia 4.47 30 2.90 2524 Estonia 3.96 43 2.56 3625 Bahrain 3.91 48 2.10 7326 Korea 4.64 23 3.11 2027 Ireland 4.74 22 3.01 2128 Jordan 3.68 62 2.40 4429 Chile 4.22 32 2.32 4930 Tunisia 4.06 36 2.58 3431 United Arab Emirates 4.48 28 2.32 5032 China 4.01 39 2.84 2633 Thailand 4.21 33 2.41 4234 Spain 4.45 31 2.61 3135 Slovenia 4.05 37 2.76 2836 South Africa 4.47 29 2.73 2937 India 4.56 25 2.82 2738 Czech Republic 4.04 38 2.67 3039 Lithuania 4.07 35 2.53 3740 Portugal 3.96 42 2.43 4041 Slovak Republic 3.91 47 2.41 4342 Malta 3.46 75 2.10 7443 Namibia 3.51 69 2.15 6744 Latvia 3.75 55 2.11 7045 Morocco 4.00 40 2.28 5546 Hungary 3.67 63 2.50 3847 Egypt 4.09 34 2.27 5648 Indonesia 3.93 44 2.60 3349 Brazil 4.49 27 2.61 3250 Mauritius 3.75 54 2.21 6051 Greece 3.86 49 2.40 4552 Cyprus 3.80 52 2.07 7753 Costa Rica 3.92 46 2.45 3954 Panama 3.72 59 2.06 7955 El Salvador 3.58 67 1.79 9556 Italy 4.54 26 2.43 4157 Romania 3.47 72 2.28 5358 Botswana 3.34 80 2.24 5759 Dominican Republic 3.52 68 1.89 9060 Mexico 3.82 51 2.23 5961 Vietnam 3.17 87 2.10 7562 Algeria 3.02 93 1.98 8863 Trinidad and Tobago 3.75 56 2.18 6364 Russian Federation 3.71 60 2.56 35

(cont’d)

11. Business sophistication 12. Innovation

Country Score Rank Score Rank

65 Jamaica 3.66 64 2.33 4766 Sri Lanka 3.46 74 2.15 6567 Turkey 3.99 41 2.17 6468 Ghana 3.40 76 2.23 5869 Colombia 3.79 53 2.20 6270 Bulgaria 3.34 79 2.03 8471 Uruguay 3.22 86 2.11 7172 Poland 3.68 61 2.30 5273 Ukraine 3.74 57 2.32 5174 Philippines 3.60 66 2.08 7675 Argentina 3.63 65 2.00 8576 Peru 3.47 73 1.81 9477 Nigeria 3.85 50 2.28 5478 Uganda 3.36 78 2.37 4679 Croatia 3.38 77 2.21 6180 Venezuela 3.24 85 2.04 8181 Gambia 3.48 71 2.06 8082 Macedonia, FYR 3.11 90 2.03 8383 Guatemala 3.32 82 1.88 9184 Kenya 3.73 58 2.33 4885 Madagascar 3.28 84 2.14 6886 Georgia 2.73 99 1.98 8787 Pakistan 3.92 45 1.96 8988 Ecuador 3.12 89 1.76 9689 Honduras 2.95 94 1.64 9990 Paraguay 2.94 95 1.55 10291 Zambia 3.48 70 2.04 8292 Nicaragua 2.68 101 1.64 10093 Malawi 3.07 92 2.06 7894 Bangladesh 3.09 91 1.74 9795 Bolivia 2.74 98 1.61 10196 Serbia and Montenegro 3.13 88 2.15 6697 Tanzania 3.33 81 2.13 6998 Bosnia and Hercegovina 2.89 96 1.81 9399 Mali 2.86 97 2.10 72100 Mozambique 2.67 102 1.85 92101 Zimbabwe 3.31 83 1.99 86102 Ethiopia 2.73 100 1.74 98103 Chad 2.61 103 1.47 103104 Angola 2.35 104 1.41 104

Table 6: Global Competitiveness Index: Innovation factors

Concluding RemarksThis chapter presents a new index of competitivenessbased on 12 pillars that capture the complex nature of thedeterminants of the productivity of nations.The pillars arecomprised of institutions, physical infrastructures, macro-economic stability, personal security, human capital, theefficiency of the goods, labor and financial markets, tech-nological readiness, market size, business sophistication,and innovation.

The 12 pillars are aggregated into three subindexescalled basic requirements, efficiency enhancers, and innovationfactors.These subindexes are cast in a framework of stagesof development in which different factors matter differ-ently at different stages of economic development. In thefirst stage of development, (the factor-driven stage), thekey factors are the basic requirements. In the second stage,(the efficiency-driven stage), the most important are theefficiency enhancers. In the last stage, (the innovation-driven stage), the central inputs are the innovation factors.

The index is computed for 104 countries and worldcompetitiveness rankings are provided.The United Statesis the most competitive economy in the world, followedby Finland, Denmark, Switzerland, Sweden, Germany,Singapore, Hong Kong, the United Kingdom, and Japan.At the lower end,Angola is the worst-ranked economy inthe world, followed by Chad, Ethiopia, Zimbabwe,Mozambique, Mali, Bosnia-Hercegovina,Tanzania, andSerbia-Montenegro.

The disaggregated nature of the 12 pillars allows us topin down the most and least favorable components ofcompetitiveness for each country.

Notes1 We thank Jennifer Blanke and Augusto Lopez-Claros for their thoughts

and long conversations over the last few months. We also thankCatherine Vindret for extraordinarily able research assistance andMichael Porter and Christian Kettels for comments on an earlierdraft.

2 This definition is similar to the one used by Porter (2004).

3 Competitiveness, on the other hand, should NOT be characterized as “acountry’s share of world markets for its products.” As suggested byPorter (2003), the competitiveness of a nation is not a zero-sumgame in which one country’s gain comes at the expense of others.It is important to emphasize that this is a flawed definition of com-petitiveness because it has been widely used to justify interventionto tilt markets in one’s favor. Countries have engaged in “industrialpolicy,” provided subsidies, and devalued their currencies all in thehope of expanding exports at their neighbors’ expense, all in thehope of improving a country’s “competitiveness.” Subsidies, howev-er, shift resources away from the most productive activities, anddevaluations (even when they are called “competitive devaluations”)are nothing but a reduction of the price of one’s products and are asignal that the firms are not competitive enough. Moreover, devalua-tions tend to increase the price of imported capital goods, whichtends to make domestic firms even less competitive.

4 The idea was that the growth rate of a country depended only on thefraction of its GDP that it invested. If the savings generated by itscitizens were not enough to finance the investment required toachieve the desired growth rate, the World Bank would finance thedifference (this is why this line of thought was, and still is, called the“financing gap”). See Easterly’s chapter in this volume for more onthe role of investment as an engine of growth.

5 Schumpeter (1942), Solow (1956), and Swan (1956). Recent researchon the importance of R&D for growth includes Romer (1990), Aghionand Howitt (1992), and Grossman and Helpman (1991). See Aghionand Howitt (1992) and Barro and Sala-i-Martin (2003) for a technicalexposition 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 andSubramanian (2003).

7 See De Soto (1990) for an illuminating analysis of how bureaucracyharms growth.

8 See Shleifer and Vishny (1997) for a comprehensive survey of corporategovernance 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 usuallythought physical infrastructures are for the process of economicdevelopment.

11 See Fischer (1993).

12 See World Bank (2004) for research papers on the economic causesand consequences of crime, violence, and war.

13 See Sachs (2001) for a comprehensive review of how health affectsthe economic prosperity of nations.

14 See Schultz (1961), Becker (1993), and Lucas (1988).

15 See Frenkel and Romer (1999), Rodrik and Rodriguez (1999), andSachs 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 notagree with Porter that Canada or Australia belong to the Factor-Driven stage.

19 In the papers that accompany the presentation of the BCI (Porter,2003), the process of development is described as consisting of dif-ferent “stages.” However, the actual implementation of the indexdoes not allow for stages since all countries are treated symmetrical-ly, independent of their level of income or the stage in which theyare found. This contrasts with the companion paper to the GCI,which allows for two types of countries: those that are in the earlystages (called ”non-core economies”) and those that are moreadvanced (called “core economies”). The only difference betweencore and non-core economies, however, is the way in which techno-logical progress occurs: in the core economies, technologicalimprovements occur through R&D; in the non-core countries, itoccurs through imitation.

20 In the factor-driven stage, the size of the market is not as importantbecause basic production processes may not be subject toeconomies of scale. In fact, some of these processes (such as theextraction of natural resources) may exhibit diminishing returns. Inthe industrial world, where many processes require large sunk costsand fixed factors, economies of scale become important. In theworld of technology and innovation, the economies of scale are evenlarger because ideas are non-rival (that is, they can be used by manypeople at the same time). Non-rivalry means that once an inventionis produced, the larger the market in which it can be sold, the moreprofitable it is for the entrepreneur who invented it.

21 Since these are weights, the coefficients �1, �2, and �3 are requiredto add up to 1.

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22 Technical note: These weights were chosen using a maximum likeli-hood method of an econometric model that had the growth rate ofper 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 regressionallowed 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 stagesof development theory suggests that econometric analysis thatforces all countries to have the same regression coefficients is mis-specified. Thus, empirical results that suggest that certain variablesare not robustly correlated with economic growth, with competitive-ness or with productivity are flawed. See Sala-i-Martin, Doppelhofer,and Miller (2004) for a paper on robust econometric methods incross-country growth regressions.

23 Note that the Growth Competitive Index, the only index of the GCRthat actually allows for two stages of the development, introduces adiscrete jump as countries move from non-core to core economies.Since the definition of core economy is based exclusively on thenumber of patents (core economies are those with more than 15patents per million population and a non-core country is one that hasfewer than that), as a country increases its innovation effort andmoves across the 15-patent threshold, the weights assigned to eachsubindex change discretely. It could, therefore, be the case that acountry that increases its innovation rate ends up suffering a dramat-ic fall in the ranks. Although this has never happened since the GCIwas first introduced in 2001, this is a potential problem and an addi-tional reason why the GCI needs to be improved.

24 Factor-driven economies are those that compete in low prices. Weproxy low wages with low income levels, which is why we assigncountries with 2003 income per capita below US$2000 to this group.GDP per capita is measured at exchange rates: international firmscompeting for low-cost production should look at exchange-ratecomparable costs rather than PPP-adjusted costs. Primary exportsare important factors that usually compete in prices. This is why weinclude countries with a high primary goods content in their exportsin this category.

25 See also Figures 2, 3, and 4.

26 We think of each question as addressing slightly different aspects ofthe same phenomenon. Since there are no theoretical or empiricalreasons to believe that some aspects are more important than oth-ers, we decide to give the same weight to all questions within a pil-lar. However, seven Survey question variables and one hard-datavariable are used in two sections in the construction of the index. Inorder to avoid double counting, we divide their value by 2 before weinclude them in the computation.

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Appendix 1: How Executive Opinion Survey questions and hard data are assigned to each pillar 1

This appendix provides details on how the GlobalCompetitiveness Index is constructed.All of the Surveyand hard data variables used in this index can be foundin the data tables section of this Report with moredetailed descriptions.

1st Pillar: Institutions

The 1st pillar is an average of two subindexes: publicinstitutions and private institutions.

Public institutions, in turn, is an average of threecomponents: property rights, honesty and corruption ofthe public sector, and government inefficiencies (whichcaptures red tape, excess bureaucracy and waste).

Private institutions is an average of four compo-nents: 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

• 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

• 6.01: Judicial independence

• 6.10: Favoritism in decisions of government officials

• 6.28: Business costs of irregular payments

• 6.29: Diversion of public funds

• 6.31: Public trust of politicians

• 6.32: Prevalence of illegal political donations

C. Government Inefficiency (red tape, bureaucracy and

waste)

• 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

• 7.05: Administrative burden for startups

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

• 9.24: Strength of auditing and reporting standards

C. Transparency

• 6.34: Pervasiveness of money laundering through banks

• 6.35: Pervasiveness of money laundering through non-

bank 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 toeach 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:

• 2.22: Government surplus/deficit, 2003

• 2.23: National savings rate, 2003

• 2.25: Inflation, 20033

• 2.26: Interest rate spread, 2003

• 2.29: Government debt/GDP ratio, 2003

4th Pillar: Personal Security

The 4th pillar has only one component, which consistsof four Survey questions:

• 2.02: Business costs of terrorism

• 6.16: Reliability of police services (weight = 1/2)

• 6.17: Business costs of crime and violence

• 6.18: Organized crime

5th Pillar: Human Capital

The 5th pillar contains two subindexes: basic humancapital and advanced human capital.

Basic human capital is an average of two compo-nents: health and primary education. See Appendix 5 fora complete description of how we use hard and Surveydata to obtain an estimation of national health.

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Appendix 1: How Executive Opinion Survey questions and hard data are assigned to each pillar (cont’d.)

Advanced human capital is an average of three com-ponents: the quantity of education, the quality of theeducation system, and on-the-job training.

The Survey questions and hard data used in eachcomponent are:

Basic Human Capital

1. Health (See Appendix 5 for details):

• 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

• 4.10: Medium-term business impact of HIV/AIDS

• 4.15: Infant mortality (hard data)

• 4.16: Life expectancy at birth (hard data)

• 4.17: Tuberculosis prevalence (hard data)

• 4.18: Malaria prevalence (hard data)

• 4.19: HIV/AIDS prevalence (hard data)

2. Primary Education

• 4.20: Gross primary enrollment (hard data)

Advanced Human Capital

1. Quantity of Education

• 3.10: Availability of scientists and engineers

(weight = 1/2)

• 4.21: Gross secondary enrollment (hard data)

• 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

• 8.10: Local availability of specialized research and

training services (weight = 1/2)

• 9.12: Extent of staff training

6th Pillar: Goods Market Efficiency

The 6th pillar is an average of three subindexes: govern-ment-induced distortions, competition, and demandconditions. Competition, in turn, is a weighted averageof two components: domestic competition and foreigncompetition.4

We again combine survey and hard data in thesecomponents.The list of variables in each of them is thefollowing:

1. Government-Induced Distortions:

• 2.17: Tax burden

• 2.20: Agricultural policy costs

• 6.02: Efficiency of legal framework

• 6.13: Extent and effect of taxation (weight = 1/2)

2. Competition (weights should be the fraction of

Imports on GDP)

A. Domestic Competition

• 7.01: Intensity of local competition

• 7.03: Extent of market dominance

• 7.06: Effectiveness of anti-trust policy

• 7.07: Prevalence of mergers and acquisitions

B. Foreign Competition (Imports)

• 2.12: Cost of importing foreign equipment

• 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)

3. Customers (Demand Conditions)

• 3.09: Government procurement of advanced technology

products (weight = 1/2)

• 8.01: Buyer sophistication

• 9.08: Degree of customer orientation

7th Pillar: Labor Market Efficiency

The 7th pillar is an average of three subindexes: labormarket flexibility, female participation, and meritocracy.

The Survey questions assigned to each one are:

1. Labor Market Flexibility

• 6.13: Extent and effect of taxation (weight = 1/2)

• 9.18: Hiring and firing practices

• 9.19: Flexibility of wage determination

• 9.20: Cooperation in labor-employer relations

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

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Appendix 1: How Executive Opinion Survey questions and hard data are assigned to each pillar (cont’d.)

8th Pillar: Financial Markets Efficiency

The 8th pillar is a (weighted) average of three subindex-es: efficiency of the financial sector, trustworthiness, andforeign direct investment.5

The Survey questions that belong to each subindex are:

1. Efficiency

• 2.03: Financial market sophistication

• 2.05: Ease of access to loans

• 2.06: Venture capital availability

2. Trustworthiness / Confidence

• 2.04: Soundness of banks

• 2.09: Regulation of securities exchanges

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:

• 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

training services (weight = 1/2)

10th Pillar: Openness and Market Size

The 10th pillar is an average of two subindexes: localmarket size and foreign market size.The foreign marketsize is an average of two components: quantity of exportsand the quality of exports.6

The Survey questions and hard data assigned to eachsubindex 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

11th Pillar: Business Sophistication

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. Networks and Supporting Industries (Clusters)

8.02: Local supplier quantity

8.03: Local supplier quality

8.06: State of cluster development

2. Sophistication of Firms Operations and Strategy

9.06: Production process sophistication

9.07: Extent of marketing

9.09: Control of international distribution

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 questionsand 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)

9.04: Capacity for innovation

GDP – Exports + Imports (weight = 1/2) (hard data)

Notes

1 See Appendix 2 for a description of how hard data are transformedinto Survey-comparable values. See Appendix 3 for a description ofhow 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 anddeflation.

4 See Appendix 6 for a description of how the relative weights ofdomestic and foreign competition are estimated.

5 See Appendix 7 for a description of the relative weights of FDI andlocal financial markets.

6 See Appendix 8 for a description on how this is constructed.

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Appendix 2. Combining hard data and Executive Opinion Survey data

Answers to the Executive Opinion Survey questionnairesare ranked in a 1-to-7 scale. In most of the cases (seebelow for exceptions), 7 indicates the best possible out-come while 1 indicates worst possible outcome. Ourindex combines these Survey data with hard data (harddata are those that can be “objectively” measured—GDP,the number of patents, or the number of Internet con-nections in a country would be examples of hard data).Of course hard data do not come in 1-to-7 rankings.Wefollow McArthur and Sachs (2001) and transform allhard data into a 1-to-7 scale using the following proce-dure. If the highest value for a data series is max and thelowest value is min, then the new 1-to-7 rank value isrelated to original value using the formula:

New value = 6 x (original value – min) + 1(max – min)

Notice that this formula will assign a 7 to the countrywith the highest value, a 1 to the country with the lowest value, and numbers between 1 and 7 to all othercountries.

For some variables, a higher value indicates a worseoutcome. For example, high levels of infant mortality arebad. In this case we “reverse” the series by subtractingthe newly created variable from 8.

Appendix 3. Dealing with Survey data ranked backwards

A small number of questions in the Survey are written away that numerically higher answers imply worse out-comes and numerically lower numbers imply better out-comes.That is, the answers are reported backwards rela-tive to vast majority of the Survey. Moreover, the choicesavailable in the Survey do not always restrict the answersto six categories. Of course, we need to transform theinformation before we combine it with the rest of thevariables.We follow a procedure similar to the one fortransforming hard data.

In order to do this, we first locate the highest andthe lowest country average.We create then an intermedi-ate variable that is equal to the maximum plus the mini-mum value (both common for all countries) minus theoriginal number (the one reported for each particularcountry).We finally use this intermediate variable toapply a formula similar to the one above:

New = 6 x (intermediate – min) + 1(max – min)

Appendix 4. The way we treat inflation

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Economists recognize that large levels of inflation arebad for competitiveness because large price increasestend to be associated with uncertainty and instability.Neither the theories of inflation nor empirical evidencesuggests that low levels of inflation are bad for produc-tivity, competitiveness, or economic growth. Finally, eco-nomic analysts suggest that deflation harms the economy.We capture all of these phenomena in our index byintroducing inflation in our macroeconomic stability pil-lar in a U-shaped manner, as depicted by Figure A1.

That is, for values of inflation between 0 and 4 per-cent, the country receives best possible score (that is, thelowest level of instability). In other words, we think thatinflation rates between 0 and 4 are equally harmful tothe economy. Beyond this range, both inflation anddeflation tend to reduce competitiveness.

Because of the scaling system we use, 1 = worst to 7= best, the country with the highest deviation will get a1, all countries with an inflation rate within the 0–4range will obtain a 7, and the remaining countries arescored relative to the worst one.

In practice, we create an intermediate variable equalto 0 if a country has an inflation between 0 and 4 per-cent, and a positive number otherwise (as depicted byFigure A1).The positive number is equal to the deviationbelow 0 for countries with deflation and equal to theinflation level minus 4 for countries with inflation abovethe optimal range

Higher numbers mean worse outcomes and therange is not restricted between 1 and 7.We need, onceagain, to rescale the variable so it conforms with the restof the variables.As usual, we first rescale into a 1-to-7scale and we then reverse the number so that higher isbetter, as discussed above.

Figure A1: Inflation in the pillar of macroeconomic stability

Macro instability

Inflation rate0% 4%

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Appendix 5. How diseases are treated to construct the health component of basic human capital

In our health section, we include the economic impactof three diseases: malaria, tuberculosis, and HIV. To esti-mate the economic impact of diseases, we combine harddata on incidence collected by the World HealthOrganization with questions from the ExecutiveOpinion Survey that reflect how these diseases affectbusiness.The idea is that impact of a disease on competi-tiveness depends not only on its incidence in the popula-tion but also on how costly this incidence is. If manypeople are infected with a disease that has no economicimpact, then incidence should have little effect on pro-ductivity (for example, different strains of a disease havedifferent severity and the segments of population affectedby it differ across countries, which then might have adistinct impact on the local economies). On the otherhand, if a country has little incidence of a very costlydisease, the effects on competitiveness might be major.Thus, we need to combine the hard data on incidencewith the Survey data on the costs of these diseases forbusiness.

To combine these data we first rank each country’sprevalence relative to the highest prevalence in theworld.That is, we create a ratio of own-country preva-lence divided by the prevalence in the highest country.Higher numbers (those closer to 1) indicate worse sce-narios. Since the answer to Survey questions are rankedin the opposite direction (where a higher number indi-cates a better outcome), we reverse the Survey numbersso higher values indicate worse outcomes (see detailsabove on how to do this).

Once hard and Survey data are ranked in the samedirection, we multiply the ratio (hard data) with theSurvey average.This product is then transformed into a1-to-7 variable using the method described above; it isthen reversed so that higher values denote better out-comes. Note that all counties where the malaria preva-lence is 0 obtain a 7 in the ranking (since their competi-tiveness is not directly affected by it), regardless of whatthe Survey says.

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 relativeimportance of these distortions depends, however, on therelative size of domestic versus foreign competition.

We create two new variables that indicate this relative importance. Domestic competition is the sum ofconsumption (C), investment (I), government spending(G), and exports (X); foreign competition is equal toimports (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.

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Appendix 8. Openness and market size

The 10th pillar of competitiveness measures the size ofthe market to which local firms have access. This hastwo components: the size of the local market and thevalue of exports. Local market should be the sum ofconsumption (C), investment (I), and government spend-ing (G).We lack the data on these three macro compo-nents, 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. Inorder to establish comparability with the local marketsize, we also measure exports in domestic PPP prices.

Appendix 7: Financial markets

The financial markets efficiency pillar (the 8th pillar)consists of two components related to local financialmarkets and foreign investment respectively.We believethat foreign direct investment (FDI) should have morecrucial importance in countries with bad financial mar-kets. In other words, if the local financial sector is veryefficient, foreign financing is less necessary.Thus, theweight that FDI should get in the financial efficiencypillar depends on the efficiency of the local financialmarket.

We give a weight of at least 50 percent to the homefinancial sector.The other 50 percent of the weight is anaverage of local financial market and FDI where the rela-tive weight depends on the efficiency of the local finan-cial sector. For the extreme case of the worst local finan-cial market in the world, the 8th pillar is constructedwith half of the weight for local financial market andhalf of the weight for FDI.At the other extreme, whenthe local markets are well functioning, the importance of FDI is zero.

The exact formula used, therefore, is:

Financial market = 1/2 x local + 1/2

x local x (local – 1)

+ FDI x 1 – (local – 1)

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