Structural Change and Economic Dynamics 21 (2010) 70–83

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Structural Change and Economic Dynamics

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Applying Comprehensive Neo-Schumpeterian Economics to LatinAmerican Economies

Dominik Hartmanna, Andreas Pykaa,∗, Horst Hanuschb

a University of Hohenheim, Economics Institute (520I), D-70593 Stuttgart, Germanyb University of Augsburg, Universitätsstr. 16, D-86135 Augsburg, Germany

a r t i c l e i n f o

Article history:Received November 2009Received in revised form November 2009Accepted November 2009Available online 24 November 2009

JEL classification:O10O54

a b s t r a c t

The paper develops a Comprehensive Neo-Schumpeterian theory of development allowingsynthesizing the market-driven, the state-driven and the more recent knowledge-basedapproaches. The theoretical part of this paper identifies (i) freedom and social welfare,(ii) knowledge and innovations, and (iii) future-oriented economic structures as mutualinterconnected and reinforcing objective classes of development. In the empirical part wereveal characteristic patterns and structural bottlenecks in the future-orientation of LatinAmerican economies. While in some countries knowledge is the main bottleneck for future-oriented development, other countries suffer from inefficient economic structures or the

E11

Keywords:Comprehensive Neo-SchumpeterianEconomicsLatin America

exclusion of large parts of the population from economic life.© 2009 Elsevier B.V. All rights reserved.

ClustersIndicators

1. Introduction

Innovation and variety are two keywords in Pier-PaoloSaviotti’s oeuvre (Saviotti, 1996). Variety instantiates in allrelevant economic variables like technologies and the ser-vices they provide; or in firms and their knowledge bases aswell as their strategic orientations; or in regions and coun-tries concerning e.g. their institutional setups. Innovationis the process which affects variety negatively (reducing

the number of different occurrences, i.e. selection) as wellas positively (increasing the number of different occur-rences, i.e. mutation). Our contribution is picking up theSaviottian notions of variety and innovation by applyingthem to a study of countries in Latin America in order

∗ Corresponding author.E-mail addresses: a.pyka@uni-hohenheim.de (A. Pyka),

horst.hanusch@wiwi.uni-augsburg.de (H. Hanusch).

0954-349X/$ – see front matter © 2009 Elsevier B.V. All rights reserved.doi:10.1016/j.strueco.2009.11.003

to detect specific patterns of organization for economicdevelopment.

In previous work, so-called Comprehensive Neo-Schumpeterian Economics (CNSE), developed by Hanuschand Pyka (2007a) is empirically applied to European andOECD countries in order to detect specific patterns inthe future-orientation of industrialized countries (Hanuschand Pyka, 2007b). CNSE transfers the ideas of innovationgoing hand in hand with true uncertainty from industrydynamics to financial markets as well as to the publicsector. For a balanced growth and a prolific developmentpotential the missing future-orientation in only one ofthese economic areas can be the decisive bottleneck ham-pering all dynamic development processes (Saviotti and

Pyka, 2009). The empirical application of this approach toindustrialized European and OECD countries has shownthat a single optimal design is nonexistent, but specificpatterns can be found. These different designs (e.g. theScandinavian model, the Mediterranean model or the

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D. Hartmann et al. / Structural Chang

entral European Model) co-exist and also change overime (Hanusch and Pyka, 2007c).

This paper applies the CNSE-approach to the specificonditions in developing and emerging countries of Latinmerica. The perspective of CNSE obviously allows new

nsights in the role of technological change for devel-pment and growth, not only in the northern but alson the southern parts of the world. This leads to a bet-er understanding of internal obstacles for qualitativehange driven by entrepreneurship and the introductionf novelties in their various and multifaceted forms andhe related co-evolutionary processes (Hanusch and Pyka,007a). However, for an application of CNSE to the south-rn hemisphere, the specificities and path-dependencies ofevelopment countries have to be considered. In particu-

ar, Amartya Sen’s capability approach (Sen, 1999), as wells some insights from the global competitiveness researchLópez-Claros et al., 2006a,b), and the Global Network forconomics of Learning, Innovation and Competence Build-ng Systems (Johnson et al., 2003; Arocena and Sutz, 2005)nspired us to transform the three pillars of Comprehensiveeo-Schumpeterian Economics, namely industry, financialarkets, and the public sector, to three objective classes of

conomic development, namely (i) freedom of actors andocial welfare, (ii) the capacity to create, implement, diffusend imitate knowledge, and (iii) a future-oriented eco-omic structure. With these three major objective classesf economic development we are able to cover the mostmportant prerequisites for prosperous and prolific devel-pment relevant in Latin American economies. We choosehis angle of perspective to provide new insights into thetructural socioeconomic setup of Latin American coun-ries by considering the impact of mass deprivation andocial imbalances, weaknesses of the institutional setupsnd (low) future-orientation of the economic structuresn the ability of an economy to reach the Schumpete-ian Development corridor where prolific developmentakes place (Hanusch and Pyka, 2007a). The original pillars

industry, finance and public sector – of Comprehen-ive Neo-Schumpeterian are still substantial elements ofhe overall system, but distributed adequately betweenhe three objective classes of development. Accordingly,he underlying rationale behind CNSE is maintained, buthe angle of perspective is adapted, in order to generateew insights in the structural dissimilarities, strengths andottlenecks for entrepreneurship, innovation and future-riented economic development in Latin America.

The paper is organized as follows: to improve thenderstanding of structural conditions allowing for orindering creative destruction processes in develop-

ng countries, Section 2 discusses the cross-fertilisationotentials between Neo-Schumpeterian Economics, globalompetitiveness research and agent-based approaches ofevelopment Economics. In the empirical part (Section 3)e introduce a data set describing 20 countries encom-assing 97% of the population of Latin America with a set

f 44 indicators representing the future-orientation of thehree objective classes of CNSD. For this data set we per-orm multivariate data analysis to control empirically theeliability and interconnectedness of objective classes andetect specific patterns for the developmental potential.

conomic Dynamics 21 (2010) 70–83 71

The results show that indeed different patterns can beidentified. While in some countries knowledge is the mainbottleneck for future-oriented development, other coun-tries suffer from inefficient economic structures, lack oflearning by solving opportunities or the exclusion of largeparts of the population from participating actively in thedevelopment and innovation processes that hamper com-petence improvement and qualitative change. It becomesobvious that only an appropriate combination of the inter-connected and mutually reinforcing factors knowledge,freedom and future-oriented economic structure will leadto qualitative change and sustainable economic devel-opment in the long run. Section 4 provides an outlookon further research and concludes that mutual learningbetween Neo-Schumpeterian Economics and complemen-tary research approaches should be fostered in order toreceive an improved understanding of entrepreneurship,innovation and qualitative change in developing and tran-sition countries.

2. Developmental economics in a modernSchumpeterian perspective

Joseph A. Schumpeter’s Theory of Economic Develop-ment (1912) revealed the role of entrepreneurs and theimplementation of new combinations as core mechanismof capitalistic development dynamics. Neo-Schumpeterianapproaches concentrate mainly on the role these newcombinations play for competitiveness, growth dynam-ics and structural change in industrialized countries.Some researchers have also applied Neo-Schumpeterianapproaches to the southern hemisphere and have revealedimportant obstacles for structural change and knowledge-based development in less developed countries, such asthe lack of learning by solving opportunities, technologi-cal asymmetries, and the weak policy orientation towardsinnovation (e.g. Arocena and Sutz, 2005; Cassiolato et al.,2003; Cimoli, 2005; Katz, 2007). However, in order to createa consistent theory of Comprehensive Neo-SchumpeterianDevelopment for less developed countries, further theoret-ical and empirical discussion is necessary.

Development Economics and Global CompetitivenessResearch help to provide insights into the specific condi-tions and range of problems in less developed countries.Several authors showed the high cross-fertilisation poten-tials between innovation economics and agents-orienteddevelopment approaches (e.g. Johnson et al., 2003; Arocenaand Sutz, 2005). The dichotomy in Development Economicsbetween market-driven and state-led development modelsis beginning to be complemented by a rising third strandwhich focuses on knowledge-based development models(e.g. World Bank, 1999; Juma et al., 2001). A comprehensiveNeo-Schumpeterian development approach able to com-bine the understandings of all three approaches and puttingthe actor into the centre of interests is still missing.

2.1. Comprehensive Neo-Schumpeterian Economics

While developing the CNSE-approach we were guidedby the question “Why is modern Schumpeterian Economicsless visible in economics, despite its important contri-

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Despite the ethic responsibility (as well as the pos-itive economic and entrepreneurial impacts) of putting

72 D. Hartmann et al. / Structural Chang

butions to economic dynamics and growth compared tomainstream approaches?” An answer can be found in therestriction of the research programme focussing mainly oninnovation driven industry development. While the neo-classical theories offer a comprehensive approach whichencompasses besides market transactions also the mone-tary realm and the public sector, modern SchumpeterianEconomics so far has not applied its major principles ofinnovation and uncertainty to other economics domainsbesides industry (Hanusch and Pyka, 2007d).

In Hanusch and Pyka (2007a) we show that theinnovation principle can be seen as the Schumpeteriancomplement of the price mechanism. Focussing on inno-vation in all economic realms challenges the short runorientation in modern capital markets approaches aswell in the market failure based approaches for an eco-nomic theory of the welfare state. With an innovation-or future-orientation, complexity issues combined withstrong uncertainty enter economic theory and demandfor a new methodology. The crucial prerequisites of longrun prolific economic development and growth decisivelydepend not only on entrepreneurship but also on thelong run orientation on capital markets facing stronguncertainty, and a public sector willing to cope with thestrong uncertainties and increasing complexities moderneconomies are confronted with.

Of course the CNSE-approach developed for industri-alized countries cannot be transferred one-to-one to thecontext of development countries. However, we find strongevidence in the modern literature on economic develop-ment of the importance of innovation in a developmentalcontext, and therefore we transform the CNSE-approachin the following sections to an approach applicable to theeconomies of Latin America.

2.2. Agent-based development approaches

Starting in the 1970s the perception has grown thatthe efforts put into industrialization and economic growthhave not led to a significant reduction of poverty andinequalities in development countries. They failed to pro-vide the poor parts of the population with the basicrequirements such as water, electricity, health care andbasic education, and to provide the people with capa-bilities and opportunities to contribute actively to thedevelopment process. In some areas social indicators haveworsened while the overall GDP showed considerablegrowth rates. This discussion was triggered in the late1970s and early 1980s, setting the basic needs of the peoplein developing countries into the focus of interest (ILO, 1976;Streeten, 1979; Steward, 1979; Streeten et al., 1981). Thepurpose of development was seen in reducing mass depri-vation and giving all individuals the opportunity to live afull life (Streeten, 1979). The concentration of developmentpolicy on economic growth and unemployment was con-sidered as insufficient. Meeting the basic needs of people

should be the first priority of development policy: empha-sis on basic education, nutrition, sanitation and health carenot only contribute directly to the alleviation of povertyand the reduction of fertility but also improves directly andindirectly productivity and economic growth of countries

conomic Dynamics 21 (2010) 70–83

by using the resources efficiently and helping to increasethem (Streeten et al., 1981). In the basic need-approachavailable resources increase by facilitating a healthier, bet-ter educated and motivated labour force and mobilizingpreviously underutilized labour (Streeten, 1979).

In 1990, a group of economists around Mahbub ul Haq,Amartya Sen, Paul Streeten, and Keith Griffin presented theso-called Human Development Index (UNDP, 1990) whichcombined GDP per capita with life expectancy and levelsof education to trace a more comprehensive and broaderpicture of development, focussing on the social choice andlife quality. Whereas former development approaches con-centrated almost exclusively on efficiency and growth, thehuman development concept proposes a switch towardsan agent-based perspective. On the website of the UnitedNations, human development is defined as a process ofenlarging people’s choices and enhancing human capabil-ities (the range of things people can do) and freedoms,enabling them to live a long and healthy life, have accessto knowledge and a decent standard of living, and partici-pate in the life of their community and decisions affectingtheir life (UNDP, 1990). This encompasses a focus of devel-opment policies on “advancing the richness of human life,rather than the richness of the economy in which humanbeings live, which is only part of it” (Amartya Sen1).

Further progress of the human development approachand the emphasis of the role of capabilities for developmenthas been made by Amartya Sen. He introduced the conceptof development as freedom. In Sen’s agent-oriented viewof development, underdevelopment is unfreedom, whiledevelopment is an integrated process of profound changes(Sen, 1999). The extensions of freedoms that allow forcapabilities, opportunities and choice to assist and activelycontribute to development are at the time the primarygoal and fundamental means of development (Sen, 1999).Sen distinguishes five instrumental freedoms: (1) politicalfreedom, (2) economic facilities, (3) social opportunities,(4) transparency guarantees and (5) protective security.These concepts are different but not independent, and fos-ter the capabilities of persons and their possibilities ofbeing agents rather than patients (Sen, 1999).

Sen’s approach has received considerable interest fromNeo-Schumpeterian economists because of the centralrole that the actors’ capabilities play. Sen’s capabilityapproach provides a theoretical bridge to connect, adaptand apply Neo-Schumpeterian approaches to underde-veloped countries and development policy, especially ina globalized knowledge-based economy in which humancapital, entrepreneurship and innovation are increasinglybecoming the key elements for development.

2.3. Integral approaches for development andcompetitiveness

capabilities and opportunities into the focus of develop-

1 See citation in http://hdr.undp.org/en/humandev/origins[12.06.2008].

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ent policies, traditional economic key concepts, such asarket efficiency, macroeconomic stability, capital accu-ulation and economic growth remain, of course, crucial

actors for economic development. Economic growth doesot necessarily imply poverty reduction (or higher levels of

reedom) but without economic growth poverty reductionnd qualitative change seems to be impossible. Many mod-rn development and competitiveness approaches nowwitch from mono-causal analysis of development andompetitiveness to a more integral and complex type ofnalysis (see World Bank, 2003; López-Claros et al., 2006b).rowth is identified as a necessary but insufficient element

or sustainable development (UNDP, 1990; World Bank,003). For example, in the World Development Report003, economists of the World Bank argue that “ensuringustainable development requires attention not just to eco-omic growth but also to environmental and social issues.nless the transformation of society and the managementf the environment are addressed integrally along withconomic growth, growth itself will be jeopardized overhe longer term.”

The Global Competitiveness Index (GCI), developed byala-i-Martin, is a concept to measure competitivenessf countries which inspired our work on the applica-ion of the CNSE-approach to development countries. TheCI considers (i) the fulfillment of basic requirements

e.g. infrastructure, macroeconomic stability, health andrimary education), (ii) efficiency enhancer (e.g. higherducation and training, technological readiness), and (iii)nnovation and sophistication indicators as key indi-ators for competitiveness (e.g. in López-Claros et al.,006b). Despite the substantial differences between Neo-chumpeterian Economics and the neoclassical approachesehind the GCI-index, the necessity to achieve good valuesor these indicators in order to foster competitiveness andevelopment is common sense.

.4. Towards a theory of Comprehensiveeo-Schumpeterian Development for less developedountries

Johnson et al. (2003) and Arocena and Sutz (2005) con-ributed substantially to the cross-fertilisation potentialsetween development and innovation economics. Theseuthors (Johnson et al., 2003) proposed that in develop-ng countries a double focus on fostering the systems ofnnovation and competence building as well as attentiono the basic needs is necessary. Arocena and Sutz (2005)dentified the fertile intersection between Sen’s capabilitypproach and the innovation system approach and empha-ized that learning by solving requires a steady flow ofpportunities to solve non-trivial problems. In a similarein, Evers et al. (2006) pointed to the knowledge traphich emerges if the import of knowledge and technol-

gy does not foster endogenous learning processes andhe creation of important non-knowledge. Each problem-

olving process and research activity intrinsically leads tohe creation of knowledge on what we do not know andhat still has to be improved or further analysed. The

ack of non-trivial technological problem-solving oppor-unities hampers decisively the capacity for endogenous

conomic Dynamics 21 (2010) 70–83 73

capability upgrading and innovation (Arocena and Sutz,2005).

From a human development and basic needs perspec-tive, the social choice of the actors to participate in thedevelopment process has to be fostered without neglect-ing the basic needs. Social imbalances and poverty hamperoverall economic performance. From a neoclassical per-spective Sala-i-Martin (in López-Claros et al., 2006b) differsbetween factor endowment, efficiency and innovation asmain pillars for global competitiveness.

Discussing these different but complementaryapproaches shows that the adaptation of Compre-hensive Neo-Schumpeterian Economics (CNSE) to thespecific conditions and challenges in developing countrieshas to consider the inability of a large percentage of thepopulation to participate pro-actively in innovation anddevelopment as well as the serious structural problemsconcerning economic efficiency and providing the eco-nomic opportunities for learning by solving processes (seealso Arocena and Sutz, 2005). Thus, when applying CNSEto development countries the efficiency of the economicstructure and the enlarging of the capabilities of all actorsto contribute to innovation and development must bebrought into stronger focus. We argue that actors have tobe free and essentially require the cognitive capabilitiesand economic opportunities to participate in economiclife. A fertile combination between the mutual reinforcingfactors: (i) freedom and social welfare, (ii) the capacityto create, implement, diffuse and imitate knowledge andinnovations, and (iii) an efficient and future-orientedeconomic structure has to be made in order to achievesocially sustainable Comprehensive Neo-SchumpeterianDevelopment.

Of course, none of these elements alone is able tofacilitate Comprehensive Neo-Schumpeterian Develop-ment with sustained capacity to cooperate and compete,innovate and create social welfare. An efficient and appro-priately liberalized economy is necessary for economicgrowth but does not deal sufficiently with market fail-ures nor provide the economy with strategic and necessaryinvestment in knowledge. Freedom of the actors may bethe primordial objective class of development but withouta future-oriented economic structure as well as appropri-ate scientific and technological capabilities cannot lead tothe economic growth and competitiveness necessary inthe long run. Knowledge is a main ingredient for innova-tion and economic development but without an efficienteconomic structure and a supportive institutional setupthat allows for capitalization of knowledge, and whichfosters entrepreneurship and evolutionary learning activ-ities, and tackles market failures and facilitate growth, itwill not lead to innovation, competitiveness and quali-tative change in the long run. Thus, the three objectiveclasses of Comprehensive Neo-Schumpeterian Develop-ment: freedom, economic structure and knowledge aremutually reinforcing and interconnected.

3. Patterns in Latin American countries

We apply this new development approach to anal-yse patterns of development performance in the Latin

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3.3.1.1. Reliability of the factorsThe operationalization of the factors shows a high

degree of intra-factorial inter-correlations, and hence ahigh statistically reliability (Table 1).

Table 1Intra-factorial consistency.

74 D. Hartmann et al. / Structural Chang

American countries. Therefore we raised a comprehensivedata set with some 44 indicators for our objective classes.The main purposes of the empirical study are (i) the oper-ationalization of the objective classes with an adequatemeasurement instrument, (ii) the control of intra-factorialmeasurement reliability, (iii) the study of mutual inter-dependencies between the objective classes, and (iv) thestructural (dis-)similarities of countries on the Latin Amer-ica continent with respect to these objective classes. Tomeasure the intra- and inter-factor consistency we apply aconfirmative factor analysis. The structural (dis-) similari-ties are analysed by applying cluster analysis.

3.1. Data

Despite some persistent problems, data availabilityfor developing and transition countries has substantiallyimproved over the last 10–20 years. Accordingly, we couldraise a comprehensive and broad set of data compris-ing 44 indicators for the factors of knowledge, freedomand economic structure in 20 Latin American countriesfor the period from 2000 to 2005. Due to missing dataonly Cuba and some smaller countries, such as Guyana,Haiti and Belize are excluded from our analysis. How-ever, in the 20 countries analysed approximately 97% ofthe Latin American population are represented. Consid-ering the quantity and complexity of collected indicatorsand the dispersed level of development of the analysedcountries, a percentage of 1.9% missing data in the over-all data set of 44 indicators and 20 countries has to beconsidered as satisfying. Missing data has been estimatedby comparator variables as well as adequate interpolationmethods (see Appendix B). In order to achieve the highestpossible level of data comparability and to prevent severeperturbations caused by differing measurement methodsand/or politically influenced estimation methods, only dataof international leading research institutions, such as theUnited Nations, The World Bank Group, and the World Eco-nomic Forum were used.

3.2. Factors operationalization

In order to operationalize the factor freedom we useboth indicators showing the levels of freedom of the actors(e.g. health and primary education, human developmentindex), as well as indicators provoking the lack of freedomof actors (such as poverty, corruption and unemployment,infrastructure, macroeconomic (in-)stability and quality ofinstitutions). Detailed information on indicators used, datasources, analysed years, and the contents of the aggregatedindicators Human Development Index, Health and PrimaryEducation, Infrastructure, Institutions and MacroeconomicStability can be found in Appendix A. The collection ofindicators concerning the factor knowledge was inspiredby previous taxonomies to measure national innovationsystems (e.g. Godinho et al., 2004; Balzat and Pyka, 2006;

Fagerberg and Srholec, 2006; MERIT and EC-JRC, 2007)and is adapted to the specific conditions of Latin America.We collected a comprehensive data set with 20 indica-tors describing the knowledge base, innovative efforts,knowledge-output and diffusion capacity in Latin Amer-

conomic Dynamics 21 (2010) 70–83

ican countries. In order to analyse the efficiency andfuture-orientation of the economic structure we collecteda data set of 17 indicators concerning the dimensionsmarket efficiency (commodities, labour and financial mar-kets), degree of informal work (e.g. urban informal sector),enterprises performance (e.g. ISI-certificates and businesssophistication), sectoral setup (e.g. I, II, III sectors) andqualitative internationalization (e.g. foreign direct invest-ment, manufactured exports). Detailed information aboutthe indicators, their data sources, analysed years, estimateddata and the contents of aggregated indicators can be foundin Appendices A and B.

3.3. Measuring the internal consistency of the factorsand the model

To prove the reliability of the factor operationalizationas well as to reveal the correlation of the objective classes,a confirmative factor analysis with Cronbach’s Alpha isapplied. The main purpose is to examine whether thehypothesis has to be rejected that the factors freedom,knowledge and economic structure are mutual reinforcingand interconnected building blocks of a common dimen-sion (that we call socially sustainable ComprehensiveNeo-Schumpeterian Development).

Reliability is a measure of the internal consistency of acollection of indicators (e.g. literacy rate, gross secondaryand tertiary enrolment, R&D expenditures, publications,patents), showing the degree to which they indicate acommon latent construct (e.g. knowledge) (Hair et al.,1995). Cronbach’s alpha is constructed by computing themean of all possible split-half-coefficients which are esti-mated by dividing the test into two shares with randomdistribution of the items and measuring the correlationbetween both shares with the Spearman–Brown-method(Schnell et al., 2005). Cronbach’s alpha is formalized inEq. (1):

˛ = n

n − 1

(1 −

∑�2

i

�2x

)(1)

n = number of items; �2i

= variance of item i; �2x = total test

variance.Alpha can take values between 0 and 1, a commonly

used threshold value for acceptable reliability is 0.7 orlarger (Hair et al., 1995). Values should not be too close to1 because this would indicate total inter-item correlationor insufficient heterogeneity of selected items.

Cronbach’s alpha

Freedom 0.809Knowledge 0.952Economic structure 0.883

D. Hartmann et al. / Structural Change and Economic Dynamics 21 (2010) 70–83 75

Table 2(Inter-)correlations of objective classes.

Item-number Constructs Alpha, when construct deleted Cronbach’s alpha

1 Freedom 0.845

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2 Economic Structure3 Knowledge

The alpha value of the factor knowledge is very high0.952) but still significantly below 1. For the factors free-om and economic structure, the alpha values 0.809 and.883 suppose a high reliability of the empirical implemen-ation. While a series of heterogeneous indicators are takennto account (see Appendix A), the necessary intra-factorialomogeneity is maintained. Thus, an appropriate trade-offetween the complexity of the real world and the explana-ory power of the empirical model is realized. Especiallyn the case of the abstract factor freedom, the alpha valuef 0.809 is recognizable, as from a qualitative perspectiveather heterogeneous but apparently interconnected indi-ators have been considered.

.3.1.2. Inter-correlations between factorsTo prevent distortions in the reliability results by

he large number of total-system-items and casual inter-orrelations of items from different constructs, theeliability of the global system has been calculated over thehree aggregated constructs including freedom, knowledgend economic structure. The aggregation has been imple-ented by the sum of the values of the standardized items.

he results of the reliability analysis show a high (inter-correlation between the factors of the system, with anlpha value of 0.918. The respective elimination of one ofhe factors would lead to lower but still good alpha valuessee Table 2).

Each factor (objective class) is highly correlated withach of the other two factors (objective classes). The highorrelations between the factors freedom and knowledgealpha 0.894), between the factors freedom and economictructure (0.904) and also between the factors knowledgend economic structure (0.845) have to be highlighted.

Accordingly, in our case of Latin America, the theoreticalnding that freedom, knowledge and economic structurere highly (inter-)correlated factors is empirically con-rmed. The hypothesis that knowledge, freedom and eco-omic structure are interconnected and mutual reinforcinguilding blocks of a common latent dimension (we callocially sustainable Comprehensive Neo-Schumpeterianevelopment) cannot be rejected.

.4. Pattern detection

Based on the theoretical and empirical foundations ofonnectedness and reliability of the objective classes, wenalyse the cross-national (dis-)similarities between Latin

merican countries and their relative strengths and weak-esses with respect to each object class as well as theverall system performance. To meet these objectives, clus-er analysis techniques are applied (Jobson, 1992; Hairt al., 1995; Backhaus et al., 2006). The general rationale

0.8940.904 0.918

behind this analytical tool is to test a sample for the degreeof structural commonalities between the units of analysis.Its outcome is a categorization of the analysed units, so thatthe coherence of each cluster as well as the heterogene-ity between different clusters is maximized (Jobson, 1992).For this purpose distance values between the countriesare determined on the basis of the characteristics of eachentity. In particular we use squared Euclidean distances.The distance between the indicators of two countries i andj is calculated as follows (Eq. (2)):

d(i, j) =m∑

k=1

(aik − ajk)2 (2)

Here aik represents the parameter values of charac-teristic k = 1, . . ., m for country i = 1, . . ., n. Thus the entirequantitative data matrix is A = (aik)nxm.

The data are characterized by a small number of unitsof analysis (20 countries in total) and at the same time bya large number of variables (44 variables in total) and by ametric data level. Considering the diverse geographic con-ditions, ethnical compositions and different historical andpolitical development process in Latin America, single clus-ter solutions (i.e. clusters with only one country) have to beexpected. We apply the hierarchical average linkage clusteralgorithm because it is not extremely influenced by singlecases and neighbours, and it is not very susceptible to dis-tortions in case of mavericks compared to other algorithms(see Backhaus et al., 2006).

The determination of the inter-cluster diversity is cal-culated as follows (Eq. (3)):

v(K, L) = 1|K | · |L|

∑i ∈ K,j ∈ L

d(i, j) (3)

with both distinctive classes K and L (i.e. K /= L) belong-ing to the entire classification K. Since we do not intendto analyse a given, ex ante predetermined, classificationof countries, we use an agglomerative classification whichstarts with single-country clusters and entails a step-wise concentration of countries according to their degreeof structural similarities. The selected clustering methodyields an exhaustive as well as disjunctive classification.That means that every country is assigned to one clus-ter (∪K∈KK = N, with N being the total amount of analysedobjects) and no country can be part of two different classes(K, L ∈ K, K /= L, so that K ∩ L =∅).

3.5. Identification of outliers and optimal cluster number

3.5.1. OutliersThe first step of the segmentation procedure is the iden-

tification and exclusion of possible outliers which can lead

76 D. Hartmann et al. / Structural Change and Economic Dynamics 21 (2010) 70–83

Table 3Cluster profiles Comprehensive Neo-Schumpeterian Development.

Cluster profiles Freedom Knowledge Economy

A: Chile 1.83 1.44 1.13B: Costa Rica 0.58 0.81 0.68C: Uruguay 0.74 0.54 −0.12D: Argentina, Brazil 0.14 0.81 0.18E: Mexico, Panama, Trinidad and Tobago 0.36 0.18 0.69F: Colombia, El Salvador 0.17 −0.29 0.03

−0.3−0.4−0.6

G: Peru, VenezuelaH: Dom. Republic, EcuadorI: Bolivia, Guatemala, Honduras, Nicaragua, Paraguay

to distortions of cluster results, suboptimal determinationof the optimal cluster numbers and fundamentally lessinformation on the structural (dis-)similarities. The anal-ysis of the cluster dendrograms and the evolution of theheterogeneity coefficients identify Chile as significant out-lier in the factors freedom and overall system, Jamaica inthe factor knowledge and Uruguay in the factor freedom.After the specific interpretation of these cases and theirexclusion from the correspondent data set, the cluster algo-rithm is applied again in order to provide better insightsin the structural (dis-)similarities within the remainingcountries2,3.

3.5.2. Determination of the optimal cluster numberTo find the optimal cluster number (for the remain-

ing cases), the so-called elbow criterion is applied. Thismeasure is determined by analysing the change of theheterogeneity index in the different agglomeration stepsof the cluster algorithm. The elbow criterion is appliedwhen further merging steps lead to a sharp rise of theheterogeneity coefficient, i.e. a strong loss in the coher-ence of the different clusters and thus in a strong qualityreduction of the entire classification. The idea of the

elbow criterion is to find the optimal number of clusterswhich can provide the best trade-off between intra-clusterhomogeneity and at the same time inter-cluster hetero-geneity.

2 What distinguishes Jamaica and Uruguay and makes them outlier inthe respective objective classes are the facts that Uruguay can show thelowest poverty rates in Latin America (according to UN-data, 3,9% between1990-2003) and that Jamaica has remarkable high values concerning theuse of information and telecommunication technologies. Nevertheless,both countries are lacking greatly in a series of other indicators. In theobjective class freedom and the overall system, Chile shows significanthigher average values. Therefore, it agglomerates with the other coun-tries/clusters just at the last cluster step. It is important to mention, thatthe outstanding performance of Chile does not suppose that everything isgoing well (e.g. the poverty level between 1990 and 2003 has been close to10% and the GINI-coefficient with 0,55 among the highest in Latin Amer-ica); however, the relative average performance is much better than inthe other Latin- American countries.

3 It is important to state that the outstanding performance of Chile doesnot suppose that everything is going well, but that the relative averageperformance is much better than in the other Latin American countries.E.g. the extreme high value in the factor freedom is rather due to signifi-cantly higher political, institutional and macroeconomic stability than inother Latin American. With regard to poverty and the GINI coefficient,Chile and no other analysed Latin American country showed very goodvalues, but between the worst it is in the upper middle class.

1 −0.11 −0.376 −0.61 −0.219 −0.75 −0.64

3.6. Classification results

As expected, the high level of diversity and hetero-geneity of Latin American countries leads to large optimalnumbers of clusters with respect to the efficiency, opennessand future-orientation of the economy (eleven clusters),the capacity to create, implement, diffuse and imitateknowledge and innovations (seven clusters), as well asthe overall system (nine clusters). However, in the factorunfreedom some common patterns can be revealed. Afteridentifying Chile and Uruguay as outliers, two main blocksare identified: one block (encompassing Bolivia, Domini-can Republic, Ecuador, Guatemala, Honduras, Nicaragua,Paraguay, Venezuela) with very weak average perfor-mance, and another with significant better performance(encompassing Argentina, Brazil, Costa Rica, El Salvador,Jamaica, Colombia, Mexico, Panama, Peru, Trinidad andTobago). These results seem to underline that in most LatinAmerican countries just about one-third of the populationcan be considered free, having the cognitive capabilities,socioeconomic opportunities and social choice to con-tribute to and benefit from development. However, insome other countries, the ratio between people enjoyingfreedom and social choice, and people suffering of socialexclusion, poverty, political suppression, crime and inse-curity, and lack of economic opportunities and stability iseven worse.

Fig. 1 shows the identified classification within theobjective classes (knowledge, freedom and economic struc-ture) and the overall system with maps where the countriesbelonging to one cluster are drawn in the same colour.

The cluster analysis reveals (empirically sustainedon the aggregated level) the diversity of Latin Amer-ican socioeconomic setups and the different nature ofinternal structural bottlenecks which are impossible todeal with traditional approaches nor with northern-typeNeo-Schumpeterian approaches. Obviously, access to com-prehensive data on internal and external linkages andhistorical evolution patterns and dynamics on the regionaland sectoral level would increase the diversity and com-plexity even more. Nevertheless, the results match well thegeneral perception.

In order to reveal the (relative) structural bottlenecks,

we measured the performance of the different countryclusters in the objectives classes by calculating the meansquare values of the corresponding item values. Each itemwas previously N(0.1) standardized. Table 3 shows theresulting cluster profiles of the eight-cluster solution.

D. Hartmann et al. / Structural Change and Economic Dynamics 21 (2010) 70–83 77

Fig. 1. Classification results.

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While this aggregated perspective does not allow spec-ulation on specific policy suggestions on the micro level, itprovides us with some insights into the structural hetero-geneity and bottlenecks of the Latin American Economiesconcerning their aggregated performance in the objectiveclasses. Several observations concerning the strength andweaknesses can be made both within and between theresultant clusters. The data reveals that in some coun-tries knowledge is the main relative bottleneck (clustersE, F, H and I), whereas in other countries comparativelylow values in the factors freedom (e.g. cluster D and G) oreconomic structure (e.g. in clusters C and G) hamper a bal-anced socioeconomic setup in which fertile combinationof freedom of the actors, an efficient and future-orientedeconomic structure and the capacity to create, implementand diffuse knowledge and innovation leads to a fertileNeo-Schumpeterian development path.

Without doubt the concentration of policy on just oneof the three objective classes may not lead to qualitativechange because of the neglect of the interrelatedness ofsocial stability, freedom of the actors, innovative capac-ity and economic structure and dynamics. Focussing onthe factor knowledge alone will not allow dealing withsocioeconomic imbalances and economic inefficiencies indeveloping countries. A mere concentration on expandingthe capabilities, human rights, social choice and freedomsof all actors, being the main purpose of the Millenniumdevelopment goals, may underestimate the importanceof (strategic) technological competitiveness and economicefficiency. Finally, concentrating merely on the economicstructure, efficiency and openness neglects the importanceof strategic alignment towards technological and sectoralcompetence building as well as unfreedom and inability oflarge parts of the population to participate and benefit inthe innovation and development process.

4. Conclusions

In the theoretical part we identify (i) freedom of theactors and social welfare, (ii) the capacity to create, imple-ment, diffuse and imitate knowledge and innovations,and (iii) an open, efficient and future-oriented economicstructure as mutual interconnected and reinforcing objec-tive classes of socially sustainable Neo-Schumpeteriandevelopment. The actors have to be free, they need thecognitive capabilities and economic opportunities to beable to self-actualize and to promote entrepreneurshipand innovation. Socioeconomic imbalances not just imposesignificant obstacles for freedom of the actors but alsohamper economic development by creating institutionalproblems and conserving economic structures. Knowl-edge and innovation are key factors to enable economic

development and institutional change. But innovation andendogenous capability upgrading require not only knowl-edge but also an efficient and future-oriented economicstructure which supplies a steady flow of opportunities andadapts and modifies knowledge to the endogenous oppor-

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tunities and demand. Thus, only an adequate combinationof freedom, knowledge and a future-oriented structurecan lead to a prolific (and socially sustainable) Compre-hensive Neo-Schumpeterian Development corridor. Policymeasures have to be adapted to the specific national capa-bilities, opportunities and requirements and provide theactors with a sound combination of cognitive capabilitiesand economic opportunities. There is no archetype bundleof policy measures able to promote development in all LatinAmerican economies, but policy has to adapt and focus onthe specific bottlenecks for development in the respectivecountries.

Despite the extreme levels of structural heterogeneityin the Latin American Economies, some structural simi-larities between the Latin American countries, concerningthe objective classes of Neo-Schumpeterian developmentcan be revealed in the empirical analysis. In some coun-tries a stronger policy focus has to be placed on knowledge(e.g. in Mexico, Colombia, Ecuador), in other countrieson the economic structure and efficiency (e.g. Uruguayand Argentina) and in a series of countries socioeconomicimbalances suppose important constraints for a broad andsound development path which should be tackled (e.g.Brazil, Costa Rica). The least developed countries (Bolivia,Guatemala, Honduras, Nicaragua, and Paraguay) showcomparative disadvantages in all factors. Our approachsuggests that without stronger emphasis on educationand knowledge, institutional change, endogenous develop-ment and technological catch up, significant improvementsin the other two objective classes freedom and economicstructure will not be possible. Common receipts for devel-opment, e.g. the Washington consensus, may be adequatein one or the other case but will not allow to overcome thespecific internal obstacles for development in cases requir-ing stronger state intervention, e.g. in order to overcomesocioeconomic imbalances or promoting strategic align-ment towards future-oriented sectors.

This paper has to be considered as a first step towardsdeveloping a Comprehensive Neo-Schumpeterian Devel-opment theory for developing and transition countries,which still requires theoretical and empirical analysis,detailed consideration of aspects, such as obstacles forqualitative entrepreneurship, impacts of social disparitiesand migration flows, demand side factors for innovation,institutional setups, governance and public policy, (cycli-cal) (dis-)connection between finance and production,global knowledge and trade flows, geographic concentra-tion of production, sectoral dynamics, etc. Nevertheless, adecisive conclusion of this paper is that in order to developa Comprehensive Neo-Schumpeterian Development the-ory we have to include other lines of research, such asdevelopment and institutional economics. We do not wantto foster excessive eclecticism but aim to promote the

search and acceptance of complementary insights of com-patible research in order to prevent theoretical lock-ins,foster interactive learning and facilitate new combina-tions.

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Appendix A. Indicators and data sources

Indicator and definition Scaling Source Average overperiod/year

% of dataestimated

Objective class freedomHuman Development Index (GDP per capita (PPP in US$), life expectancy,

adult literacy rate)Index 0–1 United Nations Development Program – Human

Development Report 20052003 0

Population below income POVERTY line <2$ per day United Nations Development Program – HumanDevelopment Report 2005

1990–2003 5

Unemployment (Urban Unemployment was applied, because for somecountries, e.g. Argentina, there was no country data available)

Percent of total labour force Economic Commission for Latin America and theCaribbean (ECLAC) – Badestat

2002–2005 0

Corruption Perception Index Index 0–10 Transparency International – CorruptionPerception Index 2005

2003–2005 0

Health and Primary Education (Medium-term business impact of malaria,medium-term business impact of tuberculosis, medium-term businessimpact of HIV/AIDS, infant mortality, life expectancy, tuberculosisprevalence, malaria prevalence, HIV prevalence, primary enrolment)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2003 0

Infrastructure (Overall infrastructure quality, railroad infrastructuredevelopment, port infrastructure quality, air transport infrastructurequality, quality of electricity supply, telephone lines)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2005 0

Institutions (property rights, diversion of public funds, public trust ofpoliticians, judicial independence, favouritism in decisions ofgovernment officials, wastefulness of government spending, burden ofgovernment regulation, business costs of terrorism, reliability of policeservices, business costs of crime and violence, organized crime, ethicalbehaviour of firms, efficacy of corporate boards, protection of minorityshareholders’ interests, strength of auditing and accounting standards)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2005 0

Objective class: Efficient and Future-oriented Economic StructureMacroeconomics – Finance (Government surplus/deficit spending,

national saving rate, inflation, interest spread rate, government debt,real effective exchange rate)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2004 0

Market Efficiency (Agricultural policy costs, efficiency of legal framework,extent and effect of taxation, number of procedures required to start abusiness, time required to start a business, entry barriers, intensity oflocal competition, effectiveness of antitrust policy, GDP-exports andimports, exports, (hiring and firing) employment practices, flexibilityof wage determination, cooperation in labour-employer relations,reliance on professional management, pay and productivity, braindrain, private sector employment of women, financial marketsophistication, ease of access to loans, venture capital availability,soundness of banks, local equity market access)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2005 0

Business Sophistication (Local supplier quantity, local supplier quality,production process sophistication, extent of marketing, control ofinternational distribution, willingness to delegate authority, nature ofcompetitive advantage, value chain presence)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2005 0

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Appendix A (Continued )

Indicator and definition Scaling Source Average overperiod/year

% of dataestimated

ISO9001:2000 Quality Management Systems – Certifications Per million inhabitants International Standards Organization (ISO) – TheISO Survey 2004

2004 0

ISO14001:2004 Environmental Management Systems – Certifications Per million inhabitants International Standards Organization (ISO) – TheISO Survey 2004

2004 0

Agriculture, value added (% of GDP) % of GDP World Bank – Development Indicators Average 2001–2004 0Industry, value added (% of GDP) % of GDP World Bank – Development Indicators Average 2001–2004 0Services, etc., value added (% of GDP) % of GDP World Bank – Development Indicators 2001–2004 0Urban occupied population in sectors of low productivity (Total informal

sector)% of total urban population Economic Commission for Latin America and the

Caribbean (ECLAC) – Statistical Yearbook 20042000–2002 15

Urban occupied population in sectors of low productivity (independent, notqualified, informal working)

% of total urban population Economic Commission for Latin America and theCaribbean (ECLAC) – Statistical Yearbook 2005

2000–2002 10

Merchandise Trade (% of GDP) Merchandise trade as a share of GDP is thesum of merchandise exports and imports divided by the value of GDP,all in current U.S. dollars.

% of GDP World Bank – Development Indicators 2001–2004 0

Exports of goods and services (% of GDP) % of GDP World Bank – Development Indicators 2001–2004 0Manufactured Exports (primary exports are approx 1-manufactured

exports)% of merchandise exports United Nations Development Program – Human

Development Report 20052003 0

High-Technology Exports (% of manufactured exports) (% of manufactured exports) World Bank – Development Indicators 2001–2004 0Imports of goods and services % of GDP World Bank – Development Indicators 2001–2004 0Foreign direct investment, net inflows (BoP, current US$)/GDP (current

US$)% of GDP World Bank – Development Indicators; IMF 2001–2004 0

Foreign direct investment, net inflows (BoP, current US$)/Population 2005 Per capita World Bank – Development Indicators; IMF 2001–2004 0

Objective Class: KnowledgeExpenditure on R&D % of GDP Red de Indicadores de Ciencia y Tecnología –

Iberoamericana e Interamericana – (RICYT) –Indicadores comparativos

1998–2003 10

Expenditure on STA (Science and Technology Activities) % of GDP Red de Indicadores de Ciencia y Tecnología –Iberoamericana e Interamericana – (RICYT) –Indicadores comparativos

1998–2003 15

Public Expenditure on Education % of GDP Economic Commission for Latin America and theCaribbean (ECLAC) – Statistical Yearbook 2004

2000–2004 0

Public Expenditure on Education As % of total governmentexpenditure

United Nations Development Program – HumanDevelopment Report 2005

2000–2002 15

Researchers in R&D Per million people United Nations Development Program – HumanDevelopment Report 2005

1990–2003 15

Publications in SCI SEARCH Publications/100 000population

Red de Indicadores de Ciencia y Tecnología –Iberoamericana e Interamericana – (RICYT) –Indicadores comparativos

2001–2003 0

Publications in PASCAL Publications/100 000population

Red de Indicadores de Ciencia y Tecnología –Iberoamericana e Interamericana – (RICYT) –Indicadores comparativos

2001–2003 0

Adult literacy rate (Percent of population aged 15and above)

UNESCO – Educational Database 2002 0

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Gross Secondary Enrollment Gross ratio UNESCO – Educational Database 2003 0Gross Tertiary Enrollment Gross ratio UNESCO – Educational Database 2003 0Total Telephone Subscribers per 100 inhabitants Per 100 inhabitants International Telecommunication Union –

Statistics2004 0

Mobile Subscribers per 100 inhabitants Per 100 inhabitants International Telecommunication Union –Statistics

2004 0

Main Telephone line per 100 inhabitants Per 100 inhabitants International Telecommunication Union –Statistics

2004 0

Internet: Hosts Per 10 000 inhabitants International Telecommunication Union –Statistics

2004 0

Internet: Users Per 100 inhabitants International Telecommunication Union –Statistics

2004 0

PCs Per 100 inhabitants International Telecommunication Union –Statistics

2004 5

Higher Education and Training (Quality of the educational system, qualityof math and science education, quality of management schools, localavailability of specialized research and training services, secondaryschool enrollment, tertiary school enrollment, extent of staff training)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review

2005 0

Technological Readiness (Technological readiness, firm-level technologyabsorption, laws relating to ICT, FDI and technological transfer, cellulartelephones, internet users, personal computers)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2005 0

Innovation (Quality of scientific research institutions, company spendingon research and development, university/industry researchcollaboration, government procurement of advanced technologyproducts, intellectual property protection, availability of scientists andengineers, capacity for innovation, utility patents)

Index 1–8 World Economic Forum (WEF) – The Latin AmericaCompetitiveness Review 2006

2005 0

Invention coefficient (patents applied by residents per 100 000population)

Per 100 000 residents Red de Indicadores de Ciencia y Tecnología –Iberoamericana e Interamericana – (RICYT) –Indicadores comparativos; United NationsDevelopment Program–Human DevelopmentReport 2005

1999–2003 5

82 D. Hartmann et al. / Structural Change and Economic Dynamics 21 (2010) 70–83

Appendix B. Missing data

Indicators Missing data % Cases Method of estimation

Population below income POVERTY line (<2$) 5 Dominican Republic Estimation of the Dominican poverty value bycomparison of poverty values with the GDP per CapitaPoverty-value Dominican Republic estimated = Povertyall countries × (GDP per Capita DominicanRepublic/GDP per Capita all countries)

Urban occupied population in sectors of lowproductivity (Total informal sector)

15 Jamaica, Trinidad andTobago, Colombia

Colombia estimated by relation to data of Urbanoccupied population independent, not qualified,informal working Jamaica, Trinidad and Tobago basedon the comparison of their labour market data andsectoral specifics

Urban occupied population in sectors of lowproductivity (independent, not qualified,informal working)

10 Jamaica, Trinidad andTobago

Jamaica, Trinidad and Tobago values estimated basedon the comparison of their labour market data andsectoral specifics

Expenditure on R&D 10 Dominican Republic,Guatemala

Dominican Republic and Guatemala estimated bycomparing the relations of their Invention coefficients,their Public Expenditure on R&D, andInnovation-values

Expenditure on STA (Science and TechnologyActivities)

15 Dominican Republic,Guatemala, Chile

Chile estimated by comparison with Expenditure onR&D-Data; Dominican Republic and Guatemalaestimated by comparison with relations in EstimatedExpenditure on R&D-Data

Public Expenditure on Education 15 Guatemala, Honduras,Venezuela

Guatemala, Honduras, Venezuela estimated by value ofPublic Expenditure on Education (% of GDP) in relationto the other analysed countries

Researchers in R&D 15 Dominican Republic,Guatemala, Jamaica

Values estimated by comparing their Higher Educationand Training values as well as their publications in SciSearch and Pascal

PCs per 100 inhabitants 5 Dominican Republic Value estimated by the amount of Internet usersInvention coefficient (patents applied by 5 Costa Rica Value estimated by comparing the relations of

residents per 100 000 population)

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