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ЭКОНОМИКА
УДК 330.34(470+571)
H. Hanusch, Y. Hara
FIT FOR THE FUTURE. THE RUSSIAN ECONOMY IN COMPARISON TO G-19 COUNTRIES
Our study is focusing on future-orientation (innovativeness) of the group of G-19 countries, concentrating especially on Russia and using an empirical indicator approach. This group is an economic, financial and political forum which consists of 19 major economies, advanced and developing ones, allocated in Asia, Europe, Euro-Asia, North and South America, The Middle East and Oceanics. If you add the European Union you get the G-20 group which is the main economic council of wealthy nations nowadays.
Future-orientation gets its analytical and empirical relevance when it is placed and investigated within a specific development model. In our study we use "Comprehensive Neo-Schumpeterian Economics" (CNSE), developed by Hanusch and Pyka (2007), as an analytical framework.
Based on the concept of CNSE the central aim of our study is to gain new insights and findings concerning the variety of future-orientation of the G-19 countries. To meet this target we (a) try to bring the notion of future-orientation on a concrete basis by using indicator analysis embedded in the framework of CNSE; (b) investigate patterns of similarities in the set of indicators; (c) show how these patterns look like by applying cluster analysis; (d) draw some conclusions from the patterns concerning the status and variety of future-orientation in the group of G-19 countries.
Keywords: Schumpeterian Economics, Development, Country Studies, Data Estimation.
Introduction
Looking around the world economy one can observe a variety of countries which exist at different levels of development. Each of them has to master its economic future, choosing an own specific development strategy. How the various countries, belonging to different continents and cultures, will succeed in this endeavor is surely one of the most exciting and important issues of coming decades.
That is also true for Russia. This country is on the way of developing from an emerging post-socialist economy into the status of an advanced one which can play
© Хануш Х., Хара Я., 2014
Хануш Хорст - генеральный секретарь Международного общества Й.А. Шумпетера, почетный профессор кафедры экономики Университета Аугсбурга (Германия, Аугсбург), e-mail: horst.hanusch@wiwi.uni-augsburg.de.
Хара Ясуши - научный сотрудник Института инновационных исследований Университета Хитотсубаши (Япония, Токио), e-mail: hara yasushi@harayasushi1.
a visible economic role in a global world. Russia is a member of the G-8 countries, a group which in the past had an important influence in directing and controlling global affairs, economical as well as political ones.
The G-8 group of countries has been enlarged in 1999 forming now the group of G-20 or G-19 countries without the EU. Since 2008 the heads of government or heads of state meet annually to promote high level discussion of policy issues. After the 2008 Washington summit its leaders announced in 2009 that the group would replace the G-8 as the main council of economic nations. This expansion was necessary in order to accommodate to developments in the world economy taking place in the last decades. Because of their magnificent GDP growth rates a large number of countries around the world was able to catch up significantly, reaching in parts the standing of the G-8 economies. Of course, Russia is also a member of the G-20 country group.
This group is an economic, financial and political forum which consists of 19 major economies, advanced and developing ones, allocated in Asia, Europe, Euro-Asia, North and South America, the Middle East and Oceanics. If you add the European Union you get the G-20 group. The 19 single member countries of the G-20 group together account for about 77 % of world GDP, 60 % of world trade and 62 % of the world population (Vestergaard, 2011).
Our study is focusing on future-orientation of the G-19 countries with a special interest concerning Russia.
Future-orientation gets its analytical and empirical relevance when it is placed and investigated within a specific development model. Such a model determines the theoretical basis of the study and provides the necessary ingredients for an empirical application.
In our study we will use "Comprehensive Neo-Schumpeterian Economics" (CNSE) as an analytical framework (Hanusch and Pyka, 2007a). This approach is based (a) on the notion of future-orientation penetrating all spheres of socioeconomic life in developed as well as in developing countries; (b) on the principal of innovation as the main driving force and the engine of future-orientation and development.
Based on the concept of CNSE the central aim of our study is to gain new insights and findings concerning the variety of future-orientation of the G-19 countries. To meet this target we (a) try to bring the notion of future-orientation on a concrete basis by using indicator analysis embedded in the framework of CNSE; (b) investigate patterns of similarities in the set of indicators; (c) show how these patterns look like by applying cluster analysis; (d) draw some conclusions from the patterns concerning the status and variety of future-orientation in the group of G-19 countries.
We will see that CNSE is able to provide the conceptual framework for studying and picturing the future-oriented features for countries such as (a) Europe:
France, United Kingdom, Germany, Russia, Italy; (b) America: Argentina, Brazil, Mexico, United States and Canada; (c) Asia: China, Australia, Japan, Turkey, Indonesia, Korea, Saudi Arabia, India; and (d) Africa: South Africa.
Future-orientation will be described and characterized in total by fifty-seven indicators, focusing on the real sector (22), the public (18) and the financial sector (18). The indicators reflect many different activities in the various countries related to innovation and future-orientation. Dependent on data availability, the indicator sets comprise different years mainly in the period between 2007 and 2012.
In the succeeding we will proceed as follows:
At first we will give an overview of growth and development models, which exist in the literature, using economic growth elements, the characteristics of the growth or development path and the institutional setting in an economy as categorizing criteria. The variety of models discussed gives us the basis for deciding which one shall be applied as the analytical frame for our indicator analysis. We will come to the conclusion that Comprehensive Neo-Schumpeterian Economics (CNSE) is the right analytical framework and will shortly characterize this approach in section 3. The next section incorporates the main part of our study, namely the indicator-based empirical investigation of future-orientation of G-19 countries, using the framework of CNSE. The results of the study are shown and discussed in section 5. At the end of our paper some concluding remarks will be drawn.
Variety Of Growth And Development Models
General Remarks
The economic literature knows a number of different growth and development models. A variety of such models is also practiced around the world, in advanced or highly developed countries as well as in emerging or less developed economies. These models can be differentiated and characterized by using specific criteria. In order to get a comprehensive overview three categories for grouping may be used: (a) economic growth elements; (b) growth or development paths; (c) institutional settings.
In such a context two main approaches in today's growth or development theory can be emphasized: the Neo-classical approach, including "new growth theory", and the Schumpeterian growth theory. Recently, a third concept is getting intellectual and political attention, especially in Europe, called theory of "smart growth" (EU Commission, 2010). It is based on innovations in the technological, social (political), ecological field and the respective quantitative and/or qualitative growth aspects induced by merging globalization with IT, new forms of producing and distributing social (common) goods and services and sustainability as an extraordinary element of long-term growth. As we will see, the smart growth model incorporates and stresses a number of features and elements similar to those of "Comprehensive Neo-Schumpeterian Economics" (CNSE).
Neoclassical Growth Or Development Models
The neoclassical approach goes back to the work of Solow in the 1950s stressing the amount of used capital and labour in the production process as main elements of economic growth. In the following decades it was developed step by step based on several theoretical principles as, for instance, individual rationality in the behaviour and calculus of economic agents, which shows up as profit and utility maximizing on markets. Technological progress is portrayed as an exogenous phenomenon contributing to a continuous growth process which ends in a long-term stable equilibrium. The last attribute also holds true for the latest version of neoclassical reasoning, the "new growth theory".
Its virtual importance in our time, however, the neoclassical growth approach attained in the so-called "catch-up" models. The main growth elements of these models are either a cheap labour intensive production, using also given natural resources, or a capital-oriented one relying heavily on investment in infrastructure, supported by cheap capital excess and an industry-oriented economic policy. Export-orientation is also important, especially in a globalized world, as well as the import of technologies (exogenous technological progress) via foreign goods with high technological components, licenses, joint-ventures or imitation (Porter and Stern, 2004).
A typical growth or development path for "catch-up" models shows that at the beginning of the development process high growth rates occur which will diminish over time and end in stagnation if nothing is changed in the potential factors of the growth process and/or in the institutional setting. Such a growth path is representative for most of today's developing or emerging countries around the world (Shar-ma, 2012).
The institutional setting in economies or societies can be pictured by focussing on the three main socio-economic pillars, the real, the financial and the public sector. These three pillars build together an institutional architecture in which the development process of a society takes place under certain circumstances.
Typical for catch-up economies is an integrative development strategy which includes and demands a strong pillar closeness. This gives an emerging country some special opportunities. For instance, the pillars can work together very closely or even intimately to climb up the development ladder. They can protect each other against risky or unforeseen events (uncertainty) by taking over full responsibility for each other's activities. This close dependence is normally guided and controlled by the public sector. That means it is dominated by the government (authoritarian state). But it also has severe dangerous effects, namely pushing back individual freedom, limiting personal creativity, inducing centralistic and bureaucratic structures and facilitating fraud or even corruption (Chun, 2006).
Schumpeterian Approaches
Schumpeterian growth and development models gained their importance in literature and political practice in the last three decades or so. They can be differen-
tiated in a (a) traditional Schumpeterian and (b) Neo-Schumpeterian and (c) Comprehensive Neo-Schumpeterian approach.
The traditional approach goes back to Schumpeter's famous book "Theory of Economic Development", (1912) and his later published book "Capitalism, Socialism and Democracy", (1942). It reveals the role of innovations as driving force in the development process, risk taking entrepreneurs (Schumpeter Mark I, 1912), corporate innovation management (Schumpeter Mark II, 1942), technological progress as an endogenous process and growth characterized mainly as a quantitative phenomenon.
Neo-Schumpeterian Economics (NSE) builds up on the traditional approach, improved by stressing also qualitative growth factors and processes, emphasizing knowledge-based formal or informal networks, collaborations between firms, governments, universities and research institutions (Saviotti and Pyka, 2004). In the literature you may also find the denotations network (cluster) model, Silicon valley model or Eco-system model (Wallace, 2013).
The growth path in NSE is characterized by unbalanced dynamics combined with processes of catching up, falling back, forging ahead and leapfrogging. There exists no continuous growth process ending in a long-term equilibrium. Growth is characterized by punctuated equilibria, induced by structural change or socioeconomic transformations having their origins in marginal as well as disruptive innovations in the technological field.
In sharp contrast to the neoclassical approach NSE focuses less on the efficient utilization of given production processes, but more on the removal and overcoming of limiting constraints and the setting of new frontiers.
However, NSE in its present shape is still far from offering an integral theory of economic development. Most of the research of the last decades has primarily concentrated on the real sphere of an economy (Hanusch and Pyka, 2007b). Technological innovations propelling industry dynamics and economic growth obviously are a major source of economic development. But, technological innovations are not the only source, nor can industry development occur in a vacuum. Instead, development is accompanied and influenced by the monetary realms of an economy as well as the public sector.
In such an institutional setting "Comprehensive Neo-Schumpeterian Economics" (CNSE) gains its special importance and relevance as a future-oriented development concept. CNSE is based on the traditional Schumpeterian model and also on the Neo-Schumpeterian one. The most important feature of CNSE, however, is the idea of institutional relevance in the process of development, stressing besides the real sector also the financial and the public sphere of a socio-economic system as the decisive pillars of future-oriented dynamics causing quantitative growth and qualitative transformations of economies. Novelties then occur in various and mul-tifaceted forms, which embrace technological, institutional and organizational as
well as ecological and social dimensions. In this respect CNSE is close to the concept of "smart growth" propagated by the EU in its economic perspective plan "Europe 2020".
Conceptual Frame Of The Study
The central aim of our study is to gain new insights and findings concerning the status of development of the G-19 countries. To meet this target we concentrate on the main element of development, that is future-orientation. But, as we know, future-orientation has different meanings in the process of development, depending on the model used for explaining or targeting economic development. As we saw, in that respect, specific growth factors or elements play a central role as well as the development path and the institutional setting realized in an economy. So, if one tries to exercise an empirical study of future-orientation of a certain group of countries, based on indicators, he has, first of all, to choose the right model which forms the conceptual frame of the study. Should that be a Neoclassical or a Schumpeterian approach?
Neoclassical models have one great disadvantage. They are not open to a future, characterized by discontinuous dynamics driven by processes of innovation which include a permanent influx of change and transformation. Over time the development process ends up in an equilibrium which can also be described as stagnation. The main reason for that result is the development path which is determined by a static, efficiency-oriented strategy and is not able to accommodate to alterations and the necessary movements of an economy according to the demands and challenges of an uncertain future. Especially emerging economies which stick too long and too intensively to a catch up philosophy will get into severe economic troubles if they don't prepare themselves to shift from the traditional neoclassical to a modern Schumpeterian development approach.
Schumpeterian models, on the contrary, rely on a concept of future which is open to "creative destruction", to permanent changes and unexpected events. It thus incorporates true uncertainty as a central element of development. To overcome uncertainty in a Schumpeterian context, especially in the frame of CNSE, at least two requirements have to be met, an evolutionary as well as a co-evolutionary one.
In an evolutionary perspective growth or economic success in an economy has to be made possible by creating and disseminating an enduring flow of novelties in each of the three institutional pillars of an economy. In this way the process of innovation has always to be kept alive and strengthened.
Economic progress in a co-evolutionary manner presupposes that the development process is influenced and determined by the behaviour and the activities of the agents in the three institutional pillars. These factors not only shape the relationship between the pillars in a fundamental way, but also determine the future-orientation of the whole system. In an idealistic view the pillars have to fulfil certain proper roles.
In such a normative concept, also influenced by the idea of harmony and sus-tainability, the task of the real economy will be to foster at all times through innovation and parallel investments the knowledge-oriented progress and the resulting wealth of a country or a region. To accomplish this task, it needs certain individual freedoms as well as capable and risk-taking agents.
The financial sector should have a very close, almost symbiotic relationship with the real economy. Its task is not a short-term decoupling from the real economy spurred by speculation, but quite the opposite, namely the medium- and long-term oriented sustainable financial accompaniment and encouragement of innovative and successful individuals and companies.
The governmental and political responsibility lies, above all, in the monitoring of the future-oriented, long-term symbiosis of the real and the financial sectors as well as their co-evolutionary development. For that purpose government has to install an adequate intelligence and control system.
But, monitoring and controlling is only the one side of the same coin. If it is necessary, the government also has to support the co-evolutionary development of the system through specific budgetary and institutional means. On the revenue side of the budget, for instance, a growth and progress oriented tax system may be an effective instrument. On the expenditure side investments in education and research seem to be adequate measures. All in all, the public sector has to fulfil the role of an "entrepreneurial state" (Mazzucato, 2013).
What consequences have to be drawn from these considerations for our indicator analysis?
We will have to find the right indicators which mirror empirically, on the one side, the evolutionary "innovation fabric" of a country and which picture, on the other, side, the related co-evolutionary processes. That means, our primary task is to find the right indicators expressing the forces and elements of a CNSE-driven development. This challenge has to be met for each of the three pillars of the socio-economic system. Then, the pattern of similarities or dissimilarities, i.e. the variety of future-orientation in the case of the G-19 countries can be detected using cluster analysis.
Indicator Analysis Based On The CNSE Concept
Data Set
Our study is based on a comprehensive set of indicators which correspond with the CNSE concept and comprise the following G-19 countries:(a) Europe: France, United Kingdom, Germany, Russia, Italy; (b) America : Argentina, Brazil, Mexico, United States and Canada; (c) Asia : China, Australia, Japan, Turkey, Indonesia, Korea, Saudi Arabia, India; and (d) Africa : South Africa. In total, 57 indicators have been collected, reflecting the characteristics in the real, financial and public sector of these economies. The indicator sets comprise average data for the latest five years, mostly from 2007 to 2011.
Above all, the indicators reflect structural specifics of the different countries as well as the future-oriented functioning of the observed economies, including outputs of the innovation process, such as patents or the commercialization of technology and knowledge-intensive goods and services at international markets. To summarize, the data we draw upon are supposed to reflect activities taking place in the three pillars, immediately entailing future-oriented characteristics.
The indicators used, originate from various sources, the most important one being the World Bank's Open Database, especially its Main Science and Technology Statistics and its Educational Database. From these three databases patent statistics, R&D expenditure data as well as several indicators of national education systems and of qualification structures of national workforces have been extracted. Further main data sources are the Global Competitiveness Report published by the World Economic Forum and the Marketline Database (see Appendix for details).
Indicator Sets for the Three Pillars
The crucial feature of the industrial pillar in a CNSE concept is its orientation towards the future, based on innovation processes. In order to comprise this dimension structurally as well as from a process perspective, the indicators used for the real sector pillar encompass various patent information with a particular focus on knowledge intensive industries covering Biotech, ICT or other knowledge intensive services. Processes of cooperation in the form of co-patenting, for instance, are as well of relevance. Furthermore, the international orientation of a country is depicted by a couple of indicators such as FDI and foreign trade.
Future-orientation of the monetary pillar is covered by indicators like the organizational dimension of financial markets (soundness of banks, etc.) and their degree of sophistication, but also by the amount of venture capital available for the financing of start-ups. Finally, we include the difference between short- and long-term macro-economic interest rates to give some attention to the transmission process between the monetary and the real sphere of an economy.
The future-orientation of the public pillar is divided into five groups of indicators covering public revenues and expenditures, the knowledge and information infrastructure, education and science as well as the institutional framework, governing development. In addition, public expenditures on R&D or expenditures for programs of technology policy are considered by corresponding indicators (GOVERD, etc.). Infrastructural information is contained in indicators expressing the quality of internet access, etc. Indicators describing the education sector encompass quantitative information (e.g. HERD) as well as qualitative information (e.g. class room size), stemming mainly from the OECD PISA study. The science sector is included by indicators like number of publications, etc. Indicators concerning the framework conditions of development include an index of regulatory quality and political stability, etc.
Cluster Analysis
The indicator approach will be used in combination with the cluster analysis (see e.g. Jobson, 1992). Target of the cluster analysis is to detect cross-national (dis-) similarities in the structure and composition of a socio-economic system, focusing on future-orientation.
The general rationale behind the cluster analysis as an analytical tool is to test a sample of variables for the degree of structural commonalities between the units of analysis. Its outcome is a categorization of the analyzed units so that the coherence of each group (or cluster) as well as the heterogeneity across different clusters is maximized. To determine the coherence of a certain cluster and to calculate the existing diversity of different clusters, distance values between the units of analysis need to be determined on the basis of the characteristics of each entity. In other words, "cluster analysis is a set of tools for building groups (clusters) from multi-variate data objects. The aim is to construct groups with homogeneous properties out of heterogeneous large samples. The group should be as homogeneous as possible and the differences among various groups as large as possible" (Hardle and Simar, 2007).
A simple outline of a cluster analysis could be the following: At the beginning, each country is treated as an individual cluster, and a so called "distance-matrix" is created according to the used attributes. Subsequently, those clusters of countries which display the least distance to each other are assigned to a new cluster. Again, the distance between the countries is measured and a new "distance-matrix" is created. This sequence is repeated until only one cluster remains.
To identify clusters, statistical standardization has been applied for every indicator as follows: (1) equalize and standardize (convert to [-1 to 1] score) for each indicator, (2) execute cluster analysis using the Wald-method for each pillar and (3) use the elbow-method to identify the step where the distance makes a bigger jump and in this way determine the ideal or most effective number of clusters.
With the help of the elbow rule, we identified that the real sector pillar consists of 4 clusters, the financial sector pillar contains also 4 clusters and the public sector pillar embodies only 3 clusters.
Empirical Results
General Result
As a first general result we can state that the European countries France, United Kingdom and Germany always show the same cluster membership, being part of cluster 1. These countries convey a remarkable homogeneity regarding their future-orientation.
Five countries, Russia, Mexico, Turkey, Argentina and Italy, belong to cluster 2 in the real and financial sector and to cluster 3 in the public pillar. These countries, except Italy, are emerging ones, struggling for a higher development status.
Concerning its future-orientation, Italy, is the only advanced or industrial economy in the group of G-19 which is situated in pillars where the emerging economies assemble in the observed time period.
Real Sector Pillar
Cluster Analysis for the Real Sector Pillar
France 1 Russia 2 Indonesia 2 India 2
Unitedkingdom 1 Mexico 2 Canada 4 Korea 1
China 2 Italy 2 Japan 3 SaudiArabia 1
Brazil 2 UnitedStates 3 Turkey 2 Australia 4
Germany 1 SouthAfrica 4 Argentina 2
Figure 1. The real sector pillar consists of four clusters or groups as shown in figure 1: Group1: France, United Kingdom, Germany, Korea and Saudi Arabia; Group2: China,
Brazil, Russia, Mexico, Italy, Indonesia, Turkey, Argentina and India; Group3: United States and Japan; Group4: South Africa, Canada and Australia
Japan and the United States are forming an own cluster 3 showing high technology advancement and a remarkable degree of future-orientation.
South Africa, Canada and Australia are in the same cluster 4. These countries heavily depend on primary resources.
The BRIC countries, Brazil, Russia, India and China are joining cluster 2. They form the group of globally most important emerging economies. So, the acronym BRIC also gets a significant importance in characterizing the affiliated countries referring to the real sector future-orientation.
Finally, there exists the cluster 1 consisting of the European countries France, United Kingdom and Germany together with Korea and Saudi Arabia. Korea is, besides Japan, the only East-Asian country in which the real sector was able to catch up with highly developed, advanced economies in the West.
Finance Sector Pillar
Cluster Analysis for the Finance Sector Pillar
France 1 Russia 2 Indonesia 2 India 4
Unitedkingdom 1 Mexico 2 Canada 4 Korea 2
China 1 Italy 2 Japan 1 SaudiArabia 4
Brazil 2 UnitedStates 3 Turkey 2 Australia 4
Germany 1 SouthAfrica 4 Argentina 2
Figure 2. The finance sector pillar comprises also four clusters as shown in figure 2: Group1: France, United Kingdom, China, Germany and Japan; Group2: Brazil, Russia, Mexico, Italy, Indonesia, Turkey, Argentina and Korea; Group3: United States; Group4: South Africa, Canada, India, Saudi Arabia and Australia
The United States are forming an own unique cluster 3.That shows the dominance and importance of this country's financial sector in a global future-oriented perspective.
There exists again a cluster 1 of European countries consisting of France, the United Kingdom and Germany. This time Japan joins this European group.
Concerning the BRIC countries, a common cluster doesn't show up anymore. China is now a member of the European group as well as Japan. Brazil and Russia are forming a new cluster 2 together with other emerging countries like Mexico, Indonesia and Turkey which compose the so-called MINT group of countries, without Nigeria. In this cluster, we also find Argentina as an emerging , Korea as a mostly advanced and Italy as a fully industrialized economy.
South Africa, Canada and Australia, economies with a high dependency on natural resources, are members of the same cluster, which is completed by India and Saudi Arabia.
Public Sector Pillar
Cluster Analysis for the Public Sector Pillar
France 1 Russia 3 Indonesia 2 India 3
Unitedkingd om 1 Mexico 3 Canada 1 Korea 1
China 2 Italy 3 Japan 1 SaudiArabia 1
Brazil 3 UnitedState s 1 Turkey 3 Australia 1
Germany 1 SouthAfrica 1 Argentina 3
Figure 3. The Public Sector Pillar consists of three clusters as shown in Figure 3: Groupl: France, United Kingdom, Germany, United States, South Africa, Canada, Japan, Korea,
Saudi Arabia and Australia; Group2: China and Indonesia; Group3: Brazil, Russia, Mexico, Italy, Turkey, Argentina and India
There exists a large group of countries which belong to cluster 1. This group contains countries from Europe (France, United Kingdom and Germany), Asia (Japan, Korea and Australia), completed by United States, South Africa and Saudi Arabia. This result is an astonishing one, because it brings together countries from different economic regions in the world which also belong to different cultures and possess a different status of development. So, one could conclude that the public sector, concerning future orientation, plays the same role in advanced economies as well as in emerging ones. Maybe that in these countries the idea of an "entrepreneurial state" is influencing or even dominating the public activities.
China and Indonesia form an own cluster 2. The public sector there has a special character, if one considers its future-orientation. It looks as if the "authoritarian principle" is governing not only the organization of the state but also its future-oriented activities.
In the third group we find BRIC countries (Brazil, Russia and India) completed by other emerging countries (Mexico, Turkey and Argentina). In this group of emerging countries rules of democracy are already installed, however, to a high degree only in a formal way. That means, the principle of the "majority of votes"
gained by one or more political parties in an election is reigning more or less theoretically, written down on paper, as a basic doctrine of public decision making. But empirically, in political practice, it might be executed in an authoritarian style without fearing to violate the statuary rules of democracy. A very influential and growing bureaucracy is also a typical feature of such an institutional public sector organization.
The only advanced country in this group is Italy.
Conclusion
The study has shown that CNSE can serve as an analytical frame for investigating empirically the future-orientation of countries belonging to different regions and cultures in the world and having attained a different development status. In the last ten years or so statistical sources came up which allow an international comparison based on indicators of innovativeness. This can be done, however, only for a time span of the last five years. If we want to include more time periods in order to get a dynamic analysis, picturing the process of future-orientation in time, we will have to wait for the coming years and the statistics offered then. So, at the moment, because of the data situation, a study of future-orientation can offer only a kind of snapshot for the G-19 countries.
But, even this snapshot can offer a number of new insights and findings. For instance, an interesting result is the extraordinary status which the US-economy holds compared to the other countries especially with regard to its financial and real sector. The USA shows in these fields a singular performance concerning its future-orientation.
Another remarkable result is that the European countries in the G-19 group are characterized by a very high degree of homogeneity. That is true for Germany, France and Great Britain with the exception of Italy. In its features for all three pillars this "advanced" country belongs more to clusters where emerging economies are situated. May be, that this result pictures a situation in statu nascendi where today's so-called economic crisis of the Mediterranean region comes under prospect.
The danger of a "fragile situation" can also be detected if one looks at the financial sector. Here emerging countries like Argentina, Brazil, Russia, Mexico and Indonesia belong to the same cluster. These countries experienced in the last two decades a severe financial crisis and there still exists a certain risk that a critical situation may come up again, if they don't reform their finance pillar according to Schumpeterian criteria of future-orientation.
Interesting are also the results we attained for the public sector pillar. The largest part of the G-19 countries seem to have installed an organizational structure and a spirit in the state sector which might be called "entrepreneurial". In the time period observed, they obviously rely more on a co-evolutionary strategy which connects the state in an intelligent way with the other institutional pillars and which doesn't follow a neo-libertarian credo of "either market or government".
Regarding the public sector pillar, the results shown in cluster 2 and 3 are also stimulating, because they show the importance of an authoritarian government ruling this way either in a direct or an indirect manner.
The proto-type country for acting directly as an "authoritarian state" is China. Here the idea of democracy is still missing, substituted by the paternalistic authority of a political party. In a catch-up development model this concept makes sense. But, future-orientation in a Schumpeterian context needs different attributes, as we know, in order to gain economic growth and progress. So, if China wants to master its future in a successful way, it will have to install institutional reforms which should rebuild the public sector as an ideal partner to the financial and real pillars of an innovative economy.
Partially, that result also holds true for the emerging economies Argentina, Brazil, India, Mexico, Turkey and in particular for Russia, all members of cluster 3. In these countries rules of democracy are formally installed but, at times, even heavily injured in political practice by employing an "authoritarian style" of public sector decision-making.
Appendix
Indicator Set for the Real Pillar
Indicator Sample length Data Source
Technicians in R&D (per million people) 2007-2011 World Bank Database
Ease of doing business index (1=most business-friendly regulations) 2011,2012 Global Competitiveness Report
Start-up procedures to register a business (number) 2007-2011 World Bank Database
Patent applications, residents 2005-2010 World Bank Database
ICT service exports (% of service exports, BoP) 2007-2011 World Bank Database
New businesses registered (number) 2004-2009 World Bank Database
Efficacy of corporate boards, 1-7 (best) 2006-2012 Global Competitiveness Report
Value chain breadth, 1-7 (best) 2006-2012 Global Competitiveness Report
Capacity for innovation, 1-7 (best) 2006-2012 Global Competitiveness Report
Company spending on R&D, 1-7 (best) 2006-2012 Global Competitiveness Report
Availability of scientists and engineers 1-7 (best) 2006-2012 World Bank Database
PCT patents applications/million pop. 2006-2012 World Bank Database
Cooperation in labor-employer relations 1-7 (best) 2006-2012 Global Competitiveness Report
Availability of latest technologies 1-7 (best) 2006-2012 Global Competitiveness Report
Researchers in R&D (per million people) 2004-2009 World Bank Database
Index of Industrial Production(Absolute) 2007-2011 Marketline Database
Labour Cost Index(Absolute) 2007-2011 Marketline Database
Total Number of Listed Compa-nies(Absolute) 2007-2011 Marketline Database
Indicator Sample length Data Source
Brain Drain (aka attract talent) 2009-2013 Global Competitiveness Report
Foreign Direct Investment, Outward 2007-2011 Marketline Database
Internet Users (Absolute Number) 2008-2012 World Bank Database
High Technology Exports (US Dollar) 2008-2012 World Bank Database
Indicator Set for the Financial Pillar
Indicator Sample length Data Source
Availability of financial services 1-7 (best) 2006-2012 Global Competitiveness Report
Total tax rate (% of commercial profits) 2006-2012 World Bank Database
Lending interest rate (%) 2010-2012 World Bank Database
Balance of Payments, Reserve Assets, Net(Absolute) 2007-2011 Marketline Database
Bank Capital to Asset Ratio(Absolute) 2007-2011 Marketline Database
Central Bank, Assets(Absolute) 2007-2011 Marketline Database
Government 10-Year Bond Rate(Absolute) 2007-2011 Marketline Database
Interest Rate Spread(Absolute) 2007-2011 Marketline Database
Market Capitalization, Total(Absolute) 2007-2011 Marketline Database
Net Domestic Credit (Absolute) 2007-2011 Marketline Database
soundness of banks 2009-2013 Global Competitiveness Report
strength of investor protection 2009-2013 Global Competitiveness Report
venture capital avaiablity 2009-2013 Global Competitiveness Report
ease of access to loans 2009-2013 Global Competitiveness Report
Monetary Gold Reserves(Absolute) 2007-2011 Marketline Database
Stocks traded, total value (current US$) 2008-2012 World Bank Database
Indicator Set for the Public Pillar
Indicator Sample length Data Source
Research and development expenditure (% of GDP) 2007-2011 World Bank Database
Urban population (% of total) 2007-2011 World Bank Database
CO2 emissions (metric tons per capita) 2007-2011 World Bank Database
Quality of scientific research institutions 1-7 (best) 2006-2012 Global Competitiveness Report
University-industry collaboration in R&D 1-7 (best) 2006-2012 Global Competitiveness Report
Gov't procurement of advanced tech products 1-7 (best) 2006-2012 Global Competitiveness Report
Quality of the educational system 1-7 (best) 2006-2012 Global Competitiveness Report
Quality of math and science education 1-7 (best) 2006-2012 Global Competitiveness Report
Quality of management schools, 1-7 (best) 2006-2012 Global Competitiveness Report
Legal rights index 0-10 (best) 2006-2012 Global Competitiveness Report
Strength of auditing and reporting standards, 1-7 (best) 2006-2012 Global Competitiveness Report
Public spending on education, total (% of government expenditure) 2005-2010 World Bank Database
Indicator Sample length Data Source
Number of Students in Primary Educa-tion(Absolute) 2007-2011 Marketline Database
Number of Students in Secondary Educa-tion(Absolute) 2007-2011 Marketline Database
Number of Students in Tertiary Educa-tion(Absolute) 2007-2011 Marketline Database
Public Healthcare Expenditure(Absolute) 2007-2011 Marketline Database
Central government debt, total (% of GDP) 2006-2012 World Bank Database
Scientific and technical journal articles 2005-2009 World Bank Database
Quality of railroad infrastructure, 1-7 (best) 2006-2012 Global Competitiveness Report
Quality of port infrastructure, 1-7 (best) 2006-2012 Global Competitiveness Report
Quality of air transport infrastructure, 1-7 (best) 2006-2012 Global Competitiveness Report
Literature
1. Chun L. The Transformation of Chinese Socialism. - Duke University Press, Durham, London, 2006.
2. European Union. Strategy for Smart, Sustainable and Inclusive Growth. -Brussels, 2010.
3. Hanusch H., Pyka A. The Principles of Neo-Schumpeterian Economics // Cambridge Journal of Economics. - 2007а. - Vol. 31(2). - Р. 275-289.
4. Hanusch H., Pyka A. Elgar Companion to Neo-Schumpeterian Economics. -Edward Elgar, Cheltenham, 2007b.
5. Jobson J.D. Applied Multivariate Data Analysis. - Vol. II: Categorical and Multivariate Methods. - Springer, New York, Berlin, Heidelberg, 1952.
6. Mazzucato M. The Entrepreneurial State, Debunking Private Vs. Public Sector Myths in Risk and Innovation. - Anthem Press, London, New York, 2013.
7. Porter M., Stern S. Ranking National Innovative Capacity: Findings from the National Innovative Capacity Index // The Global Competitive Report 20032004. - Oxford University Press, New York, 2004.
8. Sharma R. Breakout Nations // Pursuit of the Next Economic Miracles. -W.W. Norton & Company Inc., New York, London, 2012.
9. Schumpeter J.A. Theorie der wirtschaftlichen Entwicklung. - Duncker & Humblot, Leipzig, 1912.
10. Schumpeter J.A. Capitalism, Socialism and Democracy. - Harper and Brothers, New York, 1942.
11. Vestergaard J. The G 20 and Beyond // Towards Effective Global Economic Governments, DIIS Report 2011: 04.
12. Wallace R. A New Formal Approach to Evolutionary Processes in Socioeconomic Systems // Journal of Evolutionary Economics. - 2013. - Vol. 23(1). -Р. 1-15.
Получено 4.03.2014
Х. Хануш, Я. Хара
ГОТОВНОСТЬ К БУДУЩЕМУ. ЭКОНОМИКА РОССИИ В СРАВНЕНИИ СО СТРАНАМИ G-19
Наше исследование ориентировано на будущее развитие, т.е. касается инновационности группы стран G-19, особенно России. Группа 19 стран мира выделяется в Азии, Европе, Евразийском пространстве, Северной и Южной Америке, Ближнем Востоке, Океании по своим экономическим, финансовым и политическим параметрам. Если добавить страны Евросоюза, то получается группа из 20, которая сегодня представляет собой основной союз экономически богатых наций.
Ориентированность на будущее дает возможность аналитически и эмпирически исследовать особые модели развития стран в сравнении. В данной работе была использована модель, разработанная в 2007 году Х. Ханушем и А. Пика под названием «Концептуальная неошумпетер-ианская экономика» (CNSE).
Главная задача данного исследования - провести на основе концепции CNSE глубинный анализ разнообразия стран группы G-19 с позиции их ориентированности в будущее. Для этого был использован особый индикатор как показатель измерения внутри моделей, исследованы сходства по набору индикаторов, определено, как проявляются эти сходные модели при кластерном анализе, и, как следствие, предложен вывод относительно статуса и разнообразия ориентированности стран группы G-19 на будущее с позиции инновационности.
Ключевые слова: шумпетерианская экономика, развитие, изучение по странам, оценка данных.
Horst Hanusch - General Secretary of the International Society for JA Schumpeter, professor emeritus of the Department of Economics at the University of Augsburg (Augsburg, Germany), e-mail: horst.hanusch@wiwi.uni-augsburg.de.
Yasushi Hara - Researcher, Institute of Innovation Research Hitotsubashi University (Tokyo, Japan), e-mail: hara yasushi@harayasushi1.
