The Competitiveness of Nations: Why Some Countries Prosper While Others Fall Behind
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World Development Vol. 35, No. 10, pp. 1595–1620, 2007
2007 Elsevier Ltd. All rights reserved
0305-750X/$ - see front matter
www.elsevier.com/locate/worlddev
doi:10.1016/j.worlddev.2007.01.004
The Competitiveness of Nations: Why
Some Countries Prosper While Others Fall Behind
JAN FAGERBERG and MARTIN SRHOLEC
University of Oslo, Norway
and
MARK KNELL *
NIFU-STEP, Norway
Summary. — Why do some countries perform much better than other countries? This paper out-
lines a synthetic framework, based on Schumpeterian logic, for analyzing this question. Four dif-
ferent aspects of competitiveness are identified: technology, capacity, demand, and price. The
contribution of the paper is particularly to highlight the three first aspects, which often tend to
be ignored due to measurement problems. The empirical analysis, based on a sample of 90 countries
on different levels of development during 1980–2002, demonstrated the relevance of technology,
capacity, and demand competitiveness for growth and development. Price competitiveness seems
generally to be of lesser importance.
2007 Elsevier Ltd. All rights reserved.
Key words — competitiveness, development, innovation, Sub-Saharan Africa, Asian tigers
1. INTRODUCTION that these things are intimately related. We out-
line an analytical framework, based on
Why do some countries grow so much faster Schumpeterian logic, which justifies why we
and have much better trade performance than should focus on both GDP and trade perfor-
other countries? What are the crucial factors mance and their mutual relationship to explain
behind such differences? Which policies can competitiveness of countries.
governments pursue to improve the relative Arguably, there is a tendency among many
performance of their economies (and welfare economists to obscure the discussion of com-
of their citizens)? Questions such as these moti- petitiveness by focusing on extremely simplified
vate a concern for the competitiveness of coun- representations of reality that abstract from the
tries. Although the concept of country very facts that make competitiveness an impor-
competitiveness has proven to be controversial, tant issue for policy makers and other stake-
the importance of the underlying challenges holders in a country. A well-known example
makes it unlikely that this issue will lose the of this is the idea of ‘‘perfect competition,’’
attention of policy makers soon. 1
The ‘‘competitiveness of countries’’ is a rela-
tive term. What is of interest is not an absolute * Earlier versions of this paper were presented at the
performance, however we define it, but how UNECE Spring Seminar, Geneva, February 23, 2004,
well a country does relative to others. Further- the Second Globelics Conference, Beijing, October
more, the concept usually has a double mean- 18–20, 2004, and the DRUID Tenth Anniversary Sum-
ing, it relates to both the economic well being mer Conference 2005, Copenhagen, June 27–29, 2005.
of its citizens, normally measured through We wish to thank the participants and three anonymous
GDP per capita, and the trade performance of reviewers for useful suggestions. Final revision accepted:
the country. 2 Our underlying assumption is January 22, 2007.
15951596 WORLD DEVELOPMENT
which presupposes that all agents have access 2. A SYNTHETIC FRAMEWORK
to the same body of knowledge, produce goods
of identical quality, and sell these in price-clear- In this section, we develop a simple growth
ing markets, so that the only thing left to care model based on Schumpeterian logic, which
about is to get the price right. For a long time, encompasses many of the empirical models,
this led applied economists and analysts to fo- used in the applied literature on the subject.
cus on price as the only aspect of competitive- As most growth models, this model abstracts
ness. Long ago Joseph Schumpeter described from trade, but in a second step, we will ac-
the shortcomings of such simplifications. The count for that as well. Two central insights
true nature of capitalist competition, he argued, are gained from modern growth theory. First,
is not price competition, as envisaged in tradi- consistent with Schumpeter’s arguments and
tional textbooks, but competition: more recent formal theorizing on the subject
based on his perspective (Aghion & Howitt,
‘‘from the new commodity, the new technology, the 1992; Romer, 1990), growth is assumed to be
new source of supply, the new type of organization the outcome of innovation and diffusion of
(. . .) – competition which commands a decisive cost new technological knowledge rather than
or quality advantage and which strikes not at the (physical) capital accumulation (as in the tradi-
margins of the profits and the outputs of the existing tional neoclassical growth model). 3 However,
firms but at their foundations and their very lives.’’
(Schumpeter, 1943, p. 84).
in contrast to these new growth models, we
do not focus on the deeper reasons for differ-
ences in the rate of innovation across countries
In this paper, we depart from the ‘‘perfect but concentrate on the effects that such differ-
competition’’ approach and the idea of technol- ences may have on economic performance. Sec-
ogy as a public good. Rather, following Dosi ond, we accept the widely held view that access
(1988) and others, we assume that technology to knowledge is a necessary but not sufficient
is cumulative and context dependent in ways condition for prosperity. Knowledge needs to
that prevent the economic benefits of innova- be combined with a sufficiently developed
tion to spread more or less automatically. How- ‘‘absorptive capacity’’ (Cohen & Levinthal,
ever, this does not imply that diffusion of 1990; Kim, 1997) or ‘‘social capability’’ (Abra-
technology from the developed part of the movitz, 1986) in order to deliver the desired
world cannot serve as a powerful factor behind economic results.
growth and competitiveness in low-income Consider that the (volume of) GDP in a
countries (Fagerberg & Godinho, 2004). On country (Y) is a function of its technological
the contrary, we side with the economic histori- knowledge (T) and its capacity for exploiting
an Gerschenkron (1962) in his suggestion that the benefits of knowledge (C):
the technological gap between a frontier and a
latecomer country represents ‘‘a great promise’’ Y ¼ f ðT ; CÞ; ð1Þ
for the latter, since it provides the latecomer
with the opportunity of imitating more ad- where T is a function of knowledge (or innova-
vanced technology in use elsewhere. However, tion) created in the country (N) and knowledge
following this line of thought and that of diffused to the region from outside (D):
Abramovitz (1986, 1994a, 1994b), we stress T ¼ hðN ; DÞ: ð2Þ
the stringent requirements for getting the most
out of such opportunities. We use the term Assume further that the diffusion of external
‘‘capacity competitiveness’’ for this aspect of knowledge follows a logistic curve (Metcalfe,
the competitiveness of a country, which we sug- 1988). This implies that the contribution of dif-
gest, be considered in addition to the two fusion of externally available knowledge to eco-
other aspects – technology and price competi- nomic growth is an increasing function of the
tiveness – mentioned above. Finally, following distance between the level of knowledge appro-
one of the suggestions in the literature on com- priated in the country and that of the country
petitiveness (see the next section), we also take on the technological frontier. Hence, for the
into account the ability of a country to exploit frontier country, this contribution will be zero
the changing composition of demand, by offer- by definition. Let the total amount of knowl-
ing attractive products that are in high demand edge, adjusted for differences in size of coun-
at home and abroad. We label this (fourth) tries (e.g., per capita, hence the cap
aspect ‘‘demand competitiveness.’’ superscript), in the frontier country and theTHE COMPETITIVENESS OF NATIONS 1597
country under consideration, be T cap
and T cap
i , and services. To see how the latter may be ta-
respectively, and let d be the rate of growth of ken into account consider a simple two-econ-
knowledge diffused to the region from outside omy model, in which one ‘‘country’’ interacts
(D): with the rest of the ‘‘world.’’ Let exports be
X, imports be M, and W be world demand,
T cap
i all measured in terms of volume. Following
d ¼ c cT gap ; where T gap ¼ : ð3Þ
T cap
the logic outlined in the introduction, we as-
sume that a country’s exports depend on four
By differentiation and substitution, we arrive
factors: (1) its technological competitiveness
at the following solution for growth of GDP,
(its knowledge assets relative to competitors);
using small case letters for growth rates (e.g.,
(2) its capacity to exploit technology commer-
y = dY/Y, etc.):
cially (again relative to competitors); (3) its
y ¼ ceYT eTD ceYT eTD T gap þ eYT eTN n þ eYC c; ð4Þ price competitiveness (relative prices on trade-
oY T ables in common currency); and (4) world de-
where eYT ¼ oT Y
refers to the partial elasticity mand. The two first factors, technology and
of GDP with respect to technology (similar capacity, are the same as earlier but measured
for other variables). relative to the world average. Consider exports
In the model, three sets of factors determine as
the rate of growth of a country: (1) the poten-
tial for exploiting knowledge developed else- X ¼ f ðT ; C; P ; W Þ; ð5Þ
where; (2) the creation of new knowledge
where T, C, P are technology, capacity, and
within the country; and (3) the growth in the
price competitiveness in country i, relative to
capacity to exploit (or ‘‘absorb’’) knowledge
the world:
(independently of where it is created).
The model encompasses many of the empiri- Ti Ci Pi
cal models found in the literature. For instance, T ¼ ; C¼ ; P¼ :
T world C world P world
many if not most empirical models used in the
‘‘catching-up’’ literature are variants of Eqn. Since imports in this model are the ‘‘world’s’’
(4) when we drop the innovation term (see, exports, we can model imports in the same way,
e.g., Baumol, Blackman, & Wolff, 1989). noting that the competitiveness variables in this
Focusing more explicitly on the role of innova- case are the inverse of those in Eqn. (5) and that
tion for catch-up, Fagerberg (1987, 1988a) domestic demand (Y) replaces world demand:
showed that countries that caught up very fast
1 1 1
also had a very rapid growth of innovative M ¼g ; ; ;Y : ð6Þ
T C P
activity. The analysis suggested that superior
growth in innovative activity was the prime fac- If we – for the time being – take world de-
tor behind the huge difference in performance mand and technology, capacity, and price com-
between newly industrialized countries (NICs) petitiveness as given, Eqns. 5 and 6 give us two
in Asia and Latin America in the 1970s and relationships between three endogenous vari-
early 1980s. Fagerberg and Verspagen (2002) ables (Y, X, and M). 4 To solve the open econ-
have shown that the rapid increase in its inno- omy model for, say, GDP growth we need an
vative performance was the primary cause of additional constraint linking growth to trade.
the continuing rapid growth of the Asian NICs It is common to assume in the literature that
relative to other country groupings in the dec- there exist economic mechanisms that prevent
ade that followed. Moreover, available research a country from continuing on paths that would
(Fagerberg, 1987; Fagerberg & Verspagen, not be sustainable in the long run, such as accu-
2002) indicates that innovation may have be- mulating ever-increasing debts or claims on a
come more important for economic growth grand scale vis-à-vis the rest of the world. Argu-
over time (while imitation has become more ably, there may be different mechanisms of this
demanding). Hence, ignoring the role of inno- sort, and the relevance may not be the same
vation for the study of ‘‘catching-up, forging everywhere. It may occur through adjustments
ahead and falling behind,’’ to use the terminol- of the fiscal and monetary policy stance, but
ogy of Abramovitz (1986) may not be a partic- it may also be the result of working of markets,
ularly good idea. such as the capital, labor and currency markets.
The model opens up for international tech- However, interesting as such differences may
nology flows but abstracts from flows of goods be, we shall not dwell further into these issues1598 WORLD DEVELOPMENT
here, but assume that in the end the result will tors will be. Moreover, the last two terms in
be a sustainable one. Formally, following ear- (8) resemble the open-economy growth model
lier contributions by Thirlwall (1979) and Fag- suggested by Thirlwall (1979). The first of
erberg (1988b), what we assume is balanced these two terms is the familiar Marshall–Lern-
trade (Eqn. (7)). 5 An alternative way to formu- er condition, which states that the sum of the
late this restriction that is consistent with our price elasticities for exports and imports
model is to assume that the surplus (deficit) (when measured in absolute value) has to be
used to service foreign debts (financed from for- higher than one if deteriorating price compet-
eign assets) is a constant fraction of exports (or itiveness is going to harm the external balance
imports). 6 Thus, the analysis presented here is (and – in this case – the rate of growth of
consistent with a world in which countries have GDP). The second reflects the argument put
foreign debts or assets. forward by Thirlwall (1979) and Kaldor
(1981) that the extent to which a country is
XP ¼ M: ð7Þ specialized in industries that are in high
(low) demand at home and abroad may be
We assume, as before (Eqns. (2) and (3)), that
of vital importance for its economic growth.
technology depends on both national sources
Thus, the simple growth model outlined previ-
(N) and diffusion (D) from abroad, 7 and that
ously and the Kaldor–Thirlwall model are
the latter follows a logistic curve. By totally dif-
special cases of a general ‘‘Schumpeterian’’
ferentiating (2) and (3) and (5)–(7), substitut-
open economy model.
ing, and rearranging, the solution for the
growth of GDP follows:
eXT þ eMT eXT þ eMT gap 3. SOME ‘‘STYLIZED FACTS’’ ABOUT
y ¼ ceTD ceTD T THE COMPETITIVENESS OF
eMY eMY COUNTRIES 1980–2002
eXT þ eMT eXC þ eMC
þ eTN nþ c
eMY eMY In the remaining sections of this paper, we
eXP þ eMP þ 1 eXW apply the above framework to a broad range
þ pþ w: ð8Þ of countries during 1980–2002. An appropriate
eMY eMY
analysis of the competitiveness of countries also
We see that the growth of a country now de- requires the development of a more compre-
pends on five factors: (1) the potential for hensive and sophisticated set of indicators than
exploiting knowledge developed elsewhere, are traditionally used. This is particularly the
which depends on the country’s level of techno- case for ‘‘technology competitiveness’’ and
logical development relative to the world fron- ‘‘capacity competitiveness,’’ both of which are
tier; (2) creation of new knowledge multi-dimensional in character and conse-
(technology) in the country relative to that of quently hard to measure. We also develop a
competitors; (3) growth in the capacity to ex- new indicator of ‘‘demand competitiveness’’
ploit knowledge, independent of where it is cre- that captures the underlying ideas behind the
ated, relative to that of competitors; (4) change inclusion of this particular dimension in a bet-
in relative prices in common currency, and (5) ter way. Despite these requirements, we ob-
growth of world demand weighted by the ratio tained a sample of 90 countries (see
between the income elasticity for exports and Appendix) that have very different development
that of imports. levels and trends. The framework together with
By comparing Eqn. (8) with the reduced the indicators will allow us to explain some
form of the simple growth model considered important differences in economic performance
previously (Eqn. 4), we see that, apart from across different types of countries over time.
the two last terms on the right-hand side, Figure 1 presents some basic data on devel-
the model has the same structure. The only opment levels and trends for the countries in-
difference is that the coefficients of the growth cluded in our investigation. While the vertical
equation (the reduced form) now are sums of axis measures the initial level of productivity
coefficients for the similar variables in the or income (GDP per capita in PPPs), the hori-
equations for exports and imports divided by zontal axis reports annual average growth over
the income elasticity of imports. Hence, the the period (1980–2002). By combining these
higher the income elasticity for imports is, two aspects, level and trend, four different
the lower the effect on growth of all other fac- quadrants emerge.THE COMPETITIVENESS OF NATIONS 1599
Figure 1. GDP growth (1980–2002). Note: Dashed horizontal and vertical lines indicate sample averages. Source: Own
computations based on the World Bank (2005).
First, to the upper left, we have countries with There is a lot of diversity in how countries
above average level of GDP per capita but rela- perform. Although in each and every case there
tively slow growth, that is countries that ‘‘lose will be specific factors at work, and we will try
momentum.’’ Most developed countries cluster to take these into account to some extent, the
in this category (with Switzerland as the prime main purpose of our discussion is to identify,
example). In contrast, in the upper right quad- measure, and test for the impact of some gen-
rant, we have countries that continue to grow eral factors that may be of interest when dis-
fast despite a high level of GDP per capita cussing the wide differences across countries in
(‘‘moving ahead’’). The most spectacular exam- economic performance. These four factors are
ples are Luxembourg, Ireland, Hong–Kong, and (1) technology competitiveness, (2) capacity
Singapore. Of particular interest is the perfor- competitiveness, (3) price competitiveness, and
mance of the developing economies, those gen- (4) demand competitiveness. Of these the for-
erally found in the lower half of the graph. mer two are clearly multi-dimensional and
Here, we see a very clear distinction between therefore more difficult to handle.
those that are ‘‘catching-up’’ (in the lower right) Our approach will be to find reliable indica-
and those that are ‘‘falling further behind’’ (in tors, express them in comparable units and
the lower left). The former, those that appear weigh them together.Whenever possible, the
to be on a ‘‘catching-up’’ trajectory, include indicators are defined as activities measured in
the remaining ‘‘Asian tigers,’’ a number of devel- quantity adjusted by size of the country. To in-
oping Asian economies, notably China, and crease coverage across countries and limit influ-
some African and Latin-American countries. ence of shocks and measurement errors
However, as is evident from the lower left quad- occurring in specific years, we used three-year
rant, most developing countries from Africa and averages at the beginning and end of the period
Latin America continue to fall further behind. (1980–82 and 2000–02), and the nearest1600 WORLD DEVELOPMENT available period for indicators with limited time time, the average change in the indicator over series. 8 In general, the selected indicators have this period would be set to zero by definition broad coverage compared to alternative mea- (and consequently not reflected in the compos- sures but in a few cases, we needed to estimate ite variable either). To see why this might be missing data. The last column in Appendix Ta- problematic consider the role of ICT for, com- ble A.1 gives the percentage of estimated miss- petitiveness. Going back a few decades the ing observations. As is evident from the table ICT revolution was still in its infancy and this share is with very few exceptions almost arguably of relatively modest importance for negligible, the main exception being the indica- competitiveness. Today access to a well-devel- tor ‘‘average years of schooling’’ for which the oped ICT infrastructure has become necessary coverage was only 89% (due to lacking observa- for any firm (or country), reflecting the tre- tions for some former Socialist countries). In a mendous growth of ICT investments in recent few other cases, the coverage was in the area years. To be able to consider such structural 94–97%. The missing observations were esti- changes, we standardize the indicators by mated with the help of other indicators in the using pooled data (from both the initial and dataset using the impute procedure in Stata the final period). This implies that changes in 9.1. 9 Most of the missing data relate to indica- a composite indicator will reflect both shifts tors used in the construction of the composite in countries’ positions relative to each other ‘‘capacity competitiveness’’ variable. As will be- and shifts in the importance of the various come evident (see below) this composite vari- indicators over time. able is based on nine different indicators (with roughly equal weights), all of which are highly (a) Technology competitiveness correlated; hence the likelihood that the estima- tion of a small number of missing data for a few Technology competitiveness refers to the indicators should lead to a bias in the compos- ability to compete successfully in markets for ite variable must be regarded as low. new goods and services. This type of competi- It would be preferable to have prior knowl- tiveness is related to the innovativeness of a edge about the ‘‘true weights’’ to use in the con- country. There is, however, no available data struction of the composite variables. Not source which measures innovativeness directly. having this information, we either had to give Instead, what we have are different data sources each variable an equal weight (e.g., Archibugi reflecting different aspects of the phenomenon. & Coco, 2004), or estimate the composite R&D expenditures, for instance, measure some variables with the help of factor analysis (but not all) of the resources that go into devel- (e.g., Adelman & Morris, 1965; Temple & oping new goods and services. However, be- Johnson, 1998), which is the approach chosen cause data are lacking for many countries, here. 10 It is based on the idea that strongly cor- particularly in the early 1980s, this indicator related indicators refer to the same underlying could not be included in the analysis. Patent (latent) dimension, so that a data set consisting statistics, on the other hand, measures the out- of many indicators can be reduced into a single put of (patentable) inventions. This is a very or a small number of composite variables (the reliable data source, but the propensity to pat- so-called factor scores), each reflecting a signif- ent varies considerably across industries, with icant part of the total variance (see Basilevsky, many innovations not patented (or even patent- 1994). 11 Appendix Table A.2 shows the results able). To increase the reliability of the compos- of the factor analysis for technology and capac- ite indicator we add a measure of the quality of ity competitiveness. In both cases, we detected the science base (on which innovation activities only one factor with eigenvalue higher than to some extent depend) as reflected in articles unity, supporting the proposition that the indi- published in scientific and technical journals. cators taken into account do in fact reflect the Moreover, a well-developed ICT infrastructure same dimension. is widely acknowledged as a must for innova- To weigh together a large number of indi- tion. Ideally, one would have liked to include vidual indicators into one composite variable, data on the diffusion of new, important ICTs it is necessary to standardize the indicators such as, say, personal computers or mobile on a common scale. We do this by deducting phones but unfortunately such data are only the mean of the indicator and dividing it by available for the last decade or so. We therefore its standard deviation. However, by standard- chose to measure it by the number of telephone izing the indicators at two different points in mainlines per head, which – at least for recent
THE COMPETITIVENESS OF NATIONS 1601
Figure 2. Technology competitiveness (1980–2002). Note: Dashed horizontal and vertical lines indicate sample averages.
Source: Own computations based on various sources (see Appendix).
years – was found to be very closely correlated not develop the transistor, but showed a supe-
to the spread of other ICT products. 12 rior capacity to US firms when it came to
Figure 2, plots the level and trend in technol- exploiting this new technology in a way that
ogy competitiveness against each other. When sustained competitiveness. Many of the inroads
compared with the trend of GDP per capita in of Japanese producers into Western markets
Figure 1, the indicator for technological com- during most of the post-war period were of this
petitiveness displays a much stronger tendency kind. However, although the distinction may be
toward divergence. Generally, countries either clear enough in theory, in practice it may not be
move ahead of the others or fall further behind, all that simple, since resources that are devoted
with only a few staying in the two remaining to developing new goods and services may also
categories. Japan, Finland, and the United be beneficial for the ability to exploit such inno-
States are the most prominent among the coun- vations economically and vice versa (Cohen &
tries that move ahead technologically. Those Levinthal, 1990).
falling further behind include most developing Our focus here is on the capabilities that are
countries in Africa, Asia, and Latin America. important for the capacity to exploit technolog-
Taiwan and Korea were among the relatively ical opportunities. Abramovitz (1986, 1994a,
few initially backward countries to catch-up 1994b), who used the term ‘‘social capa-
technologically. bility’’ 13 to describe this phenomenon, empha-
sized three general factors as being particularly
(b) Capacity competitiveness relevant: (1) technical/organizational compe-
tence (level of education), (2) availability/qual-
In many respects, the distinction between ity of financial institutions/markets, and (3)
technology competitiveness and capacity com- quality/efficiency of governance. These factors
petitiveness is crucial. For instance, Sony did can all be measured by available indicators,1602 WORLD DEVELOPMENT
albeit imperfectly. However, by taking into ac- Silanes, & Schleifer, 2004). These problems not-
count a broad range of indicators, some of the withstanding, we will try to consider this factor
problems associated with a particular data by using existing survey/opinion data on adher-
source/indicator may be ‘‘averaged out.’’ For ence to basic political, civil, and human
the first factor, we include secondary and ter- rights. 15
tiary education (as reflected in gross enrollment Figure 3 plots the level and trend of capacity
rates) and average number of schooling years competitiveness against each other. This figure
(as a broad measure of human capital stock). confirms that many developed countries, joined
Regarding the development of the financial sys- by the Asian tigers, have high and growing
tem, we take into account the share of the total capacity for exploiting new technology. How-
money supply that people entrust others to ever, some developed countries (Canada, Aus-
handle, 14 the extent of domestic credit to pri- tria, and Japan for instance) appear to lose
vate sector, and the degree of monetary stabil- momentum along this dimension. As with tech-
ity represented by historical record of nological competitiveness, many low-income
inflation rates. The quality/efficiency of gover- economies, particularly from Africa, continue
nance is more difficult to measure with preci- to fall behind in capacity competitiveness as
sion, especially in time series. The reason is well. However, compared to technological
that the main source of information consists competitiveness there is more convergence
of opinion polls and expert assessments (which going on in the capacity to exploit technologi-
might be influenced by factors other than those cal opportunity, because a number of low-in-
we are interested in, say, a general mood of come countries, such as Bolivia, Thailand,
‘‘optimism’’ among the respondents at the time Chile, and South Africa, catch-up at a rela-
or the reverse, see Glaeser, La Porta, Lopez-de- tively fast rate.
Figure 3. Capacity competitiveness (1980–2002). Note: Dashed horizontal and vertical lines indicate sample averages.
Source: Own computations based on various sources (see Appendix).THE COMPETITIVENESS OF NATIONS 1603
(c) Price competitiveness (d) Demand competitiveness
For a long time, economists focused mainly Kaldor (1978), Thirlwall (1979), and others
on price and/or cost comparisons when discuss- have suggested that the relationship between
ing competitiveness. This trend reflects the tra- a country’s production (or trade) structure
ditional view on competitiveness, which and the composition of world demand may
emphasizes the potentially damaging effects of also be of importance for competitiveness. De-
excessive wage growth on the economy (the mand is not likely to grow at the same pace for
higher the growth of costs or prices, the lower all products. In particular, products based on
the rate of growth and vice versa). As a rough important innovations in the not too distant
test of this argument, Figure 4 plots the most past are likely to experience high growth and
commonly used indicator of price or cost com- this may affect countries differently depending
petitiveness, growth of unit labor costs in man- on their specialization pattern (Fagerberg,
ufacturing in a common currency (ULC), on 2002). As an illustration, consider growth in
the vertical axis against growth of GDP per ca- world demand (approximated by growth in
pita on the horizontal. As is evident from the world trade) over the period under investiga-
graph, there is no clear trend. 16 Countries with tion here. If we rank growth of world trade
high growth in ULC appear just as likely to during this period by products (at the three di-
grow fast as to be among the laggards. Hence, git level of SITC, rev. 2), it becomes clear that
if there is a causal relationship of the type com- over one quarter of the growth is accounted for
monly assumed, its impact must be overshad- by only five (out of 233) products. Four of
owed by the effects of other factors that also these products belong to the group of ICT
affect growth. products that show spectacular growth
Figure 4. GDP growth and price competitiveness (1980–2002). Note: Dashed horizontal and vertical lines indicate
sample averages. Source: Own computations based on various sources (see Appendix).1604 WORLD DEVELOPMENT
throughout this period. 17 Other types of prod- Figure 5 plots the relationship between de-
ucts that grew relatively fast include pharma- mand competitiveness (vertical axis), and
ceuticals, instruments, and various types of growth of GDP per capita (horizontal axis).
machinery, while many raw materials and agri- A clearly distinguishable group of fast-grow-
cultural products displayed slow growth. Argu- ing countries that also benefit from favorable
ably, such changes are bound to have demand conditions emerges from the analysis.
important effects on growth and trade. We cap- Ireland, Taiwan, Korea, Singapore, Malaysia,
ture this aspect by weighting the growth of China, and India appear to have gained the
world demand by commodity (gj) by the initial most from changes in the composition of de-
commodity composition (specialization) of mand. One alarming trend is that many of
each country’s exports (sij): the least developing countries, particularly in
Xm Africa, scored low on demand competitiveness
wi ¼ ðgj sij Þ; and had slow growth. By contrast, many
j¼1 developed countries grow relatively slowly
Pn but still enjoy positive demand competitive-
X t1
ij
t
i¼1 X ij ness. Some developing countries also grew fast
sij ¼ Pm t1
and g j ¼ Pn t1
; ð9Þ
j¼1 X ij i¼1 X ij
in spite of unfavorable demand conditions.
Arguably, as with price competitiveness, it is
where Xij denotes country’s i (i = 1, . . ., n) ex- difficult to assess the proper impact of de-
ports of a product group j (j = 1, . . ., m) and mand competitiveness on growth and develop-
t 1 and t are two points in time. A high score ment without reverting to a broader
indicates favorable demand conditions for framework that also considers other relevant
country’s exports. factors.
Figure 5. GDP growth and demand competitiveness (1980–2002). Note: Dashed horizontal and vertical lines indicate
sample averages. Source: Own computations based on various sources (see Appendix).THE COMPETITIVENESS OF NATIONS 1605
4. GLOBAL COMPETITIVENESS: ogy with its output, for example, productivity
EXPLORING THE DYNAMICS (GDP per capita). Hence, to calculate the po-
tential for diffusion we use the log of initial level
Having developed indicators of the different of GDP per capita (Ygap). 18 The expectation,
aspects of competitiveness, we apply these indi- then, is that the effect of this variable should
cators in an analysis of the differing growth per- be negative (dragging down growth in frontier
formance of the countries. However, the short countries and – by comparative standards –
time period for which reliable data are available giving a boost to those further behind). For
and the lack of annual observations for some the other four variables, we used the indicators
key variables put severe limits on the possibili- developed in the previous section. However, the
ties of econometric work. We therefore re- standardization procedure used in creating the
frained from estimating the entire model, and composite indicators of technology and capac-
chose instead to concentrate on its reduced ity competitiveness made it difficult to calculate
form, as given by Eqn. (8). In this equation, growth rates, so we used the differences in the
the rate of economic growth of a country level of these variables between the final and
should be a weighted sum of five different fac- the initial year instead. Eqn. (10) below restates
tors: (1) the potential for diffusion; (2) growth Eqn. (8) in an econometric form (adding an er-
in technological competitiveness; (3) growth in ror term):
capacity competitiveness; (4) growth in price
competitiveness; and (5) demand competitive- y i ¼ a0 þ a1 Y gap
i þ a2 ni þ a3 ci þ a4 pi þ a5 wi þ mi :
ness. The main purpose of the estimation, then, ð10Þ
is to estimate these weights, which we use to as-
sess the impact of the different aspects of com- We transform all the variables to a common
petitiveness on economic growth. scale (standardized by deducting the mean and
A challenge when applying this model empir- dividing by the standard deviation). This
ically is to find an approximation for the total transformation allows for a direct comparison
level of technology appropriated in a country of parameter values (so-called beta values are
(independent of origin) relative to the frontier reported, see Wooldridge, 2003, pp. 114–115),
(the most advanced country in the sample). with higher numerical values indicating a
As in most other empirical applications of this greater explanatory role in the regression.
sort, we chose to identify the level of technol- The first column in Table 1 presents results
Table 1. Regression results
OLS Iteratively re-weighted least squares OLS Excluding outliers
Constant 0.02 0.002
(0.28) (0.03)
Log of the initial GDP per capita 0.79*** 0.76*** 0.82***
(6.24) (6.86) (8.45)
Technology 0.31*** 0.31** 0.41**
(2.65) (2.39) (2.61)
Capacity 0.33*** 0.33*** 0.36***
(3.14) (3.55) (3.90)
Price 0.19*** 0.18** 0.18***
(2.62) (2.19) (3.99)
Demand 0.41*** 0.35*** 0.31***
(3.02) (2.82) (3.22)
F-test 14.50 12.93 19.66
R2 0.46 0.53
Observations 90 90 80
Note: The dependent variable is growth of GDP (in PPPs constant international USD). Beta values of the parameters
are reported. Absolute value of robust t-statistics in parentheses. *, **, and *** denote significance
pffiffiffiffiffiffiffiffiffiffiffi at the 10%, 5%, and
1% levels. DFITS used to exclude outliers with a cut-off point at abs ðDFITSÞ > 2 ðk=nÞ.1606 WORLD DEVELOPMENT of the regression analysis for Eqn. (10) when distinguished between variables significantly estimated by ordinary least squares (OLS). correlated with growth 22 (and hence that The coefficients for the five variables included might serve as likely candidates for being in- in the model all having the expected signs, sig- cluded among the omitted factors) and those nificantly different from zero at the 1% level, that were not (and which therefore might qual- lend strong support to the model. To test for ify as ‘‘instruments’’ in the tests for endogene- the possible impact of outliers (countries with ity, see Table A.4). very special characteristics/performance), we We identified five exogenous variables impor- also include estimates of Eqn. (10) with regres- tant for economic growth, reflecting differences sion techniques that are more robust to the in geography, nature, and climate. Table 2 re- inclusion of outliers (iteratively re-weighted ports the consequences of including these in a least squares) 19 and OLS without the main regression on economic growth together with outliers). The results from these robust regres- the other variables of the model. The first col- sions suggest that the presence of outliers has umn reports the results using OLS, while the little impact on the estimates. This, of course, second and third columns contain estimates of reinforces our belief in the findings presented the same equation with the robust regression here. techniques. The results confirm that several fac- Another potential problem has to do with the tors related to geography and nature (longi- possibility of omitted variables. For instance, if tude, elevation, access to ocean, quality of there are omitted exogenous variables related soil, and climate) are important for economic to, say, nature, geography, or history that are growth and increase the explanatory power of in fact quite important for how countries per- the regression. However, all the core competi- form, we run the risk of putting too much tiveness variables survived the test. Although emphasis on – or getting biased estimates of – the magnitude of the estimated coefficients for our explanatory variables (e.g., the different as- the core variables decreased somewhat in most pects of competitiveness). The standard way to cases (though not significantly so), the esti- test for this, which we will apply below, is to mates remained significant as conventionally identify a set of indicators for such omitted defined. It is noteworthy that, as in Table 1, exogenous variables and study the conse- the results for the technology and capacity quences of adding these to the regression. How- competitiveness variables are actually strength- ever, biased estimates may also come from ened when outliers are excluded, indicating that failing to take into account a possible feedback the findings reported here in no way depend on from the dependent variable (economic growth) the inclusion of a few countries with deviating on the various types of competitiveness taken characteristics. into account in the model (the so-called endo- Table 3 illustrates how the model explains geneity bias). We may exclude such feedback differences in economic growth between coun- a priori for demand competitiveness (which de- tries with different types of characteristics pends on historical, given data) but not for the (based on the regression in the first column in other three. Various methods are available for Table 2). Since it is not practical to illustrate dealing with problems related to endogeneity, this for 90 countries, we aggregated them into but since these methods generally are less effi- eight different country groups (among which cient than OLS, it is advisable first to try to one consists of what is traditionally considered establish the extent to which such a problem as the developed world). Since the diversity in is indeed present. To explore this, we computed both initial levels and performance is much lar- the Durbin–Wu–Hausman test for endogene- ger in Asia than elsewhere, we operate with ity, 20 the results of which indicate that there four different groups in this case (East, South, is no convincing evidence of an endogeneity West, and the Asian tigers) compared to two bias in the present case (see Appendix Table in Africa and one for Latin America (see A.4). Appendix Table A.3 for composition of the Since the tests discussed above require data groups). As is evident from the table, the model for a number of new exogenous variables captures most of the qualitative features, (not included in Table 1), we started by col- although it underestimates the growth of some lecting data for variables that, following the catching-up economies, particularly in East advice of earlier studies on economic Asia (which includes China). The model cor- growth, 21 might be considered as potentially rectly predicts that the rich countries grow rel- useful in the analysis. In the second step, we atively slowly, mainly because the potential for
THE COMPETITIVENESS OF NATIONS 1607
Table 2. Regression results with selected exogenous factors
OLS Iteratively re-weighted OLS excluding
least squares outliers
Constant 0.03 0.01
(0.42) (0.09)
Log of the initial GDP per capita 0.79*** 0.79*** 0.83***
(7.00) (6.66) (7.41)
Technology 0.24* 0.25* 0.44***
(1.80) (1.95) (2.74)
Capacity 0.25*** 0.26*** 0.27***
(2.91) (2.89) (3.23)
Price 0.13* 0.14* 0.13**
(1.82) (1.66) (2.35)
Demand 0.33*** 0.33*** 0.25***
(3.02) (2.68) (2.91)
Longitude of country centroid 0.17** 0.16* 0.17**
(2.05) (1.80) (2.34)
High-low elevation 0.24*** 0.22** 0.23***
(2.63) (2.59) (3.53)
Access to ocean or navigable river 0.26*** 0.22** 0.20**
(2.65) (2.12) (2.38)
Desert tropical ecozone 0.15** 0.16* 0.16**
(2.11) (1.79) (2.56)
Very or moderately suitable soil for agriculture 0.17* 0.16* 0.13*
(1.98) (1.81) (1.96)
F-test 10.01 10.30 12.87
R2 0.60 0.66
Observations 90 90 80
Note: The dependent variable is growth of GDP (in PPPs constant international USD). Beta values of the parameters
are reported. Absolute value of robust t-statistics in parentheses. *, **, and *** denote significance at the 10%, 5%, and
pffiffiffiffiffiffiffiffiffiffiffi
1% levels. DFITS used to exclude outliers with a cut-off point at absðDFITSÞ > 2 ðk=nÞ.
benefiting from technology diffusion is smaller negative impact in Sub–Saharan Africa and
for rich than for poor countries (and the failure Latin America.
of many rich countries to improve competitive- It also becomes evident in Table 3 and in the
ness sufficiently to make up for this loss). The regression analysis that price competitiveness
prediction is also reasonable for the Asian ti- appears trivial when compared with other
gers, where technology, capacity, and demand aspects of competitiveness. 23 Although the
competitiveness account for most of the rapid sign of the effect is the expected one, the quan-
growth, although geography, nature, and cli- titative effect is relatively small, which implies
mate also contribute positively. In general, the that above average price-growth for tradeables
poorer countries suffer from deteriorating tech- does hamper economic growth but not
nology competitiveness (relative to the sample much. 24 Since the payoff is likely to be small,
average), and the same holds to some extent an important policy implication for developing
for capacity competitiveness. Moreover, an economies is that they should focus on building
unfavorable match between production struc- social and technological capabilities rather than
ture and external demand hampers the growth attempting to influence costs and prices on
of many developing countries, particularly in tradeables through the manipulation of ex-
Africa. Factors related to geography, nature, change rates. Nevertheless, although the posi-
and climate also contribute to uneven develop- tive effect on economic growth of improving
ment in the developing world, with a positive price competitiveness is likely to be small
impact in Asia and North Africa and a clear (partly because of the negative terms of trade1608 WORLD DEVELOPMENT
effect that it entails), the effect on domestic pro-
Note: Based on column 1 in Table 2. Average growth was 3.7% over the period. N is number of observations. Data for GDP (in PPPs constant international USD) are
Geography, etc.
duction of tradeables – and hence employment
in that sector – may be much larger. Hence, to
0.5
0.9
the extent that a country has a huge reserve of
0.2
1.1
0.9
0.7
0.4
0.8
(adequately qualified) labor that it wishes to
transfer to the tradeables sector, boosting
growth there by keeping prices on tradeables
relatively low may appear as a sensible policy.
This may be one explanation for the fact that
Demand
China and some other developing countries
Table 3. Actual and estimated differences in growth vis-à-vis the world average (in percentage points), 1980–2002
0.1
0.2
0.2
0.5
0.6
0.6
1.0
0.1
seem to prefer to keep their currencies under-
valued.
The use of composite variables for technol-
ogy and capacity competitiveness implies that
Price
0.1
0.1
0.0
0.0
0.3
0.0
0.0
0.0
the results reported here are not directly com-
parable with previous research. However,
there are many studies that have used (one
or more of) the data sources taken into ac-
Capacity
0.2
0.1
0.1
0.4
count here to explain differences in cross-coun-
0.2
0.8
0.2
0.1
try growth performance, and the results
Contribution of the explanatory factors
reported here are arguably consistent with
the lessons from this literature. 25 For in-
stance, both Griffith, Redding, and Van Ree-
Technology
nen (2004) and Fagerberg and Verspagen
0.2
0.3
0.2
0.2
0.3
0.3
0.4
1.1
(2002) find support for the proposition that
R&D and innovation are important for catch-
ing-up (and economic growth more generally).
The important role played by education (or
GDP per capita
Log of initial
human capital) for growth has been high-
1.6
0.7
0.4
lighted by a number of studies (Barro, 1991;
1.1
2.0
0.0
0.5
1.8
Benhabib & Spiegel, 1994) 26 and the same
holds for finance (King & Levine, 1993; Le-
vine, 1997; Levine & Zervos, 1998). More re-
cently, a number of studies have emphasized
Estimated
in growth
difference
the strong links between (various aspects of)
0.2
1.0
0.5
3.2
2.0
2.0
0.0
0.5
governance and growth performance (Acemo-
glu, Johnson, & Robinson, 2001; Glaeser
et al., 2004; Rodrik et al., 2004). Regarding
in growth
difference
Actual
demand competitiveness there is a growing lit-
0.4
1.0
0.5
3.7
2.9
1.7
0.1
0.3
erature focusing on the role of specialization
for growth. Research indicates that specializa-
tion in natural-resource based products has
Initial GDP
been shown to be a curse rather than a bless-
per capita
16,625
8,477
2,670
1,209
8,605
5,481
3,720
1,741
ing for many developing countries (Hussain,
1999; Sachs & Warner, 2001). Specialization
in technology-intensive products, on the other
from the World Bank (2005).
hand, has been shown to be conducive to
27
19
18
N
4
5
5
7
4
growth (Cuaresma & Wörz, 2005; Dalum,
Laursen, & Verspagen, 1999; Plümper & Graff,
Developed countries
Sub-Saharan Africa
2001).
Latin America
North Africa
Asian Tigers
South Asia
West Asia
East Asia
5. CONCLUSIONS
The purpose of this paper was to scrutinize
empirically why some countries consistentlyTHE COMPETITIVENESS OF NATIONS 1609
outperform others. We adopted a theoretical The differences across country groups are
perspective that places emphasis on the role striking. As for technology competitiveness,
played by four different aspects of competitive- there is a clear divide between the advanced
ness: technology, capacity, demand, and price/ countries, with healthy and continuing in-
cost. The contribution of the paper is particu- creases, and the rest of the world, with little
larly to highlight the first three aspects, which or no progress. The Asian tigers stand out with
often tend to get lost because of measurement the best performance. Apart from innovation
problems. (as reflected by patents), which continue to con-
Our empirical analysis, based on a sample of tribute to divergence, a major factor behind
90 countries during 1980–2002, demonstrated these developments is an increasing digital di-
the relevance of technology, capacity, and de- vide, caused by much faster diffusion of ICTs
mand competitiveness for economic growth. in the already developed economies and among
The former is one of the main explanations be- the Asian tigers than elsewhere. There is less
hind the continuing good growth performance divergence along the capacity dimension,
of the Asian tigers relative to other major coun- although there is not much convergence in
try groups. Deteriorating technology and capacity either. At least for one aspect, the
capacity competitiveness are, together with an financial system, there has been some catch-
unfavorable export structure, the main factors up of developing countries vis-à-vis the devel-
hampering many developing countries in oped part of the world. However, even this does
exploiting the potential to catch-up in technol- not extend to all groups of countries, as exem-
ogy and income. When unfavorable geography, plified by Latin America and Sub-Saharan
nature, and climate add to the effects of failing Africa.
competitiveness serious problems may arise, as These trends point to the possibility of
exemplified by the countries of Sub-Saharan continuing divergence in the world economy,
Africa. as emphasized also by other recent studies
What are the crucial factors behind these (Fagerberg & Verspagen, 2002). However, at
developments, and what can governments do any time some countries manage to defy
in order to improve the relative position of their the trend, as the Asian tigers have done in
economies? To deal better with these questions, the latter half of the post Second World
we illustrate in Figure 6 the factors behind the War period (and Japan before them). A
observed changes over time in technology and policy that systematically has put a high prior-
capacity competitiveness. ity on improving technology and capacity
Figure 6. Contribution to change of technology and capacity competitiveness. Source: For definitions and sources see the
Appendix.1610 WORLD DEVELOPMENT
competitiveness and exploiting the changing (Dahlman & Aubert, 2001). The adverse effects
pattern of world demand through fostering de- of unfavorable geography, nature, and climate
mand competitiveness aided these develop- that hamper the development of some develop-
ments (Wade, 1990). 27 Not every country can ing countries underline the need for improving
specialize in, say, electronics, and there may competitiveness. It is a worrying sign that the
be aspects of what the Asian tigers did that least developing countries of Sub-Saharan Afri-
are not replicable today. Nevertheless, the ca, which are the most unfavorably affected by
option of improving technology, capacity, and such external factors, also fail to narrow the
demand competitiveness is in principle open gap through building social and technological
for other developing countries as well, and capabilities. Unfortunately, many other devel-
some countries, with China as the most specta- oping countries around the world experience
cular example, are already following that route the same failure.
NOTES
1. For a critique of the concept and its use see, for 5. Fagerberg (1988b) and Meliciani (2001) found
example, Krugman (1994). For an extended discussion, that this assumption holds for the developed
see Fagerberg (1996). economies.
2. There are many definitions around, most of which 6. As is easily verified, we may multiply the left or right
reflect this ‘‘double meaning’’ in one way or another. A hand side of (7) below with a scalar without any
typical example is the following: competitiveness is ‘‘the consequence for the subsequent deductions.
degree to which, under open market conditions, a
country can produce goods and services that meet the 7. As with knowledge (T), it is necessary to measure
test of foreign competition, while simultaneously main- nationally created knowledge (N) and knowledge dif-
taining and expanding domestic real income’’ (see fused from abroad (D) relative to the world average.
OECD, 1992, p. 237).
8. For details on definitions, sources and coverage see
3. Traditionally, economists used to assume that Appendix Table A.1. Articles in scientific and engineer-
growth was the result of accumulation of physical ing journals are from 1986 and 1999 and average
capital (cf. Solow, 1956). By the end of the 1980s, schooling years in population refer to 1980 and 2000.
Schumpeter’s ideas focused economists on innovation We used only data from the initial and final year (not the
and diffusion as the sources of economic growth (Aghion three-year averages) for these indicators. Moreover, for
& Howitt, 1992; Romer, 1990), and physical capital the indicator of monetary stability, we used the standard
accumulation became one of the endogenous variables. deviation of the GDP deflator during the 1970s (for the
For an overview of the literature on technology and initial period) and 1990s (for the final period).
growth, see Fagerberg (1994).
9. See the Stata 9 Manual for details.
4. It is not possible to exclude a priori a feedback
from the endogenous variables (growth and trade) on
competitiveness but we have at the present stage of the 10. For more on the construction of composite indica-
analysis chosen to regard competitiveness as exogenous. tors see Freudenberg (2003) and Nardo et al. (2005).
The arguments in favor of such a feedback are
probably the strongest for price competitiveness, since 11. We can use two methods to acquire the factor
it depends on wage and productivity growth, both of scores. Although sometimes biased, regression-scored
which may depend on economic growth. Nevertheless, factors tend to be more accurate, while the method
the extent to which this actually happens will also proposed by Bartlett produces unbiased factors that
depend on the system of income determination/wage tend to have larger mean squared error (Bartlett,
negotiations, the working of which may differ a lot 1937). Although we use the latter, our analysis is
from country to country. In the end this is an empirical robust to the method chosen, since the factor scores
question, which needs to be explored empirically (see obtained by the two methods are highly correlated (by
Section 4). more than 99%).THE COMPETITIVENESS OF NATIONS 1611
12. An inspection of the recent data suggests that the 17. A table showing this is available on request from
indicator of telephone mainlines can be used as a the authors. Of course, growth in world trade may also
proxy for the overall development of ICT infrastruc- reflect globalization of production, so that it is possible
ture. Over 2000–02 the number of telephone mainlines that some of this growth is not reflecting the growth of
is highly correlated to personal computers (0.92), demand proper (Srholec, 1997). Nevertheless, there is no
internet users (0.91), and mobile phones (0.92). Some doubt that ICT products have been a driving force
limited data are available for the first half of the behind the changes in the composition of world demand
nineties, when distribution of these variables follows a during this period.
similar pattern. The number of telephone mainlines is
correlated to personal computers (0.86) and mobile 18. A rival interpretation of this variable, based on the
phones (0.76) over 1990–92 as well as to internet users traditional neoclassical theory of growth (Solow, 1956),
(0.71) over 1993–95. All the ICT indicators are per would be that it reflects the potential for catch-up due to
capita. lower capital-labor ratios (which according to that
theory may be assumed to be reflected in lower levels
13. A related concept is ‘‘social capital,’’ for example, of GDP per capita). However, it has been shown that a
the ability of a population to engage in socially reasonably parameterized growth model of the Solow
beneficial, cooperative activities, which many often type yields predictions that are not consistent with the
relate to the spread of honesty and thrust across the evidence (much quicker convergence than what can be
population (Woolcock & Narayan, 2000 for an over- observed) and, hence, that other approaches (such as the
view). Although there have been some attempts recently present one) are called for (for an overview and
to collect data of relevance for the measurement of discussion see Aghion & Howitt, 1998). For further
‘‘social capital,’’ the ‘‘World Value Survey’’ deserves evidence of the role of capital accumulation versus
particular mentioning (Basanez & Inglehart, 1998), the technology in developing countries, see Benhabib and
limited coverage of these data, especially for the eighties, Spiegel (1994).
does not allow us to include such aspects here. For
instance, Knack and Keefer (1997), who used such data 19. Iteratively re-weighted least squares is a method of
to explore the relationship between trust, cooperative robust regression, which assigns a weight to each
behavior, and economic growth, were only able to observation with higher weights given to better behaved
include 29 (mostly developed) countries into the inves- observations. In extremely deviant cases (those with
tigation. Cook’s Distance greater than 1) weights may be set to
missing (so that these do not become included in the
14. The literature interprets this ‘‘contract intensive analysis.
money’’ indicator as reflecting the extent of property
rights enforcement (Clague, Keefer, Knack, & Olson, 20. The Durbin–Wu–Hausman test is a two-stage
1999). However, in our view it can just as well be seen as procedure (Wooldridge, 2002, pp. 118–122). First, the
an indicator of the development of the financial system potentially endogenous variables are regressed against
of a country. the instruments. Then add the residuals obtained from
these regressions to the original regression on economic
15. Some analysts have tried to extend the above growth. If the estimated coefficients of the residuals in
analysis by including not only the effectiveness/quality this latter regression are significantly different from zero
governance but also measures reflecting the character then there is an endogeneity problem (and least squares
of the political system (constitutions, election rules, estimates are biased). This is not the case here (see
etc.). However, the available econometric evidence Appendix Table A.4).
seems to confirm what follows from casual
observation, namely that the political and legal systems 21. Examples of such exogenous variables (suggested
of successful countries (and unsuccessful ones as well) in the empirical literature) include latitude, longitude,
can differ a lot (Glaeser et al., 2004). Catch-up land area, elevation, or access to ocean (Gallup, Sachs,
friendly policies, it seems, may originate in very & Mellinger, 1999; Rodrik, Subramanian, & Trebbi,
different political and legal systems (from communist 2004), climate (Kiszewski, Mellinger, Spielman, &
China to democratic Ireland, to take just two exam- Malaney, 2004; Masters & McMillan, 2001), fraction-
ples). alization of the population along ethnic and other
dimensions (Alesina, Devleeschauwer, Easterly, Kurlat,
16. Kaldor (1978) and Fagerberg (1996) both found & Wacziarg, 2003; Easterly & Levine, 2001; Fearon,
that rising ULC could be associated with improvements 2003; Fearon & Laitin, 2003), endowments of natural
in export performance, especially among the more resources and history of war and conflict (Fearon &
technologically advanced countries. Laitin, 2003).You can also read
