Modern integral development approaches

Modern development approaches and the corresponding means of measurement increasingly consider the complexity of linkages, causalities and interdependences between different social, economic, political and ecological dimensions. Extreme positions of either market and state as the ultimate planner or ‘invisible hand’ of the economy have shifted towards a more intermediate position, drawing on the need

for both forces to work complementarily with one another. Comprehensive taxon-omies have been presented in different fields of research, such as those developed by the comprehensive Neo-Schumpeterian approach (Hanusch and Pyka 2007a, 2007c, 2007d), the systems of innovation and development approach (Cassiolato et al. 2003; Lundvall et al. 2011), the Global Competitiveness Index of the World Economic Forum or the taxonomy proposed by Stiglitz, Sen and Fitoussi (2009) in the Commission on the Measurement of Economic Performance and Social Progress. Modern development approaches have moved beyond all previous dis-cussions on the market and state as either/or solutions. Instead they move towards promoting complementary action, coordination and interaction between the mar-ket and state; facilitating on the one hand the strengths of marmar-ket forces, and on the other promoting the interaction between the different agents of society. This is nec-essary to address properly the need for regulation and strategic interventions by the state and to create the institutional framework, facilitating innovation, economic development and social welfare (e.g. Sen 1999; World Bank 2003; Rodrik 2004).

After decades of ISI policies and government intervention between the 1950s and the 1970s, followed by the subsequent so-called neoliberal ‘counterrevolution’ in the last two decades of the twentieth century, recent development approaches argue in favour of an intermediate position between market and state (e.g. Rodrik 2004).

Furthermore, recent approaches consider various complex factors: the strategic need to promote fertile cooperation patterns between the different agents of the economy (Cassiolato et al. 2003); the ethical and economic need to provide the people with the capabilities to be active agents (UNDP 1990); and the importance of promot-ing the institutional setup and strategic policy processes necessary to overcome failings in coordination and information about potential new sectors and enable economic diversification through self-discovery mechanisms, including finding out which activities work and which do not (Hausmann and Rodrik 2003; Rodrik 2004). Three recent approaches in economics considering the role of multiple influence factors and their interrelatedness are briefly discussed in the following sections.

2.4.1 Comprehensive Neo-Schumpeterian economics

Hanusch and Pyka (2007a) show that the innovation principle can be seen as the Schumpeterian complement of the price mechanism. Companies do not merely compete for lower prices, but also (especially in the long run) for innovations and the introduction of new goods, services, marketing methods and organization models. By focusing on innovation in all economic realms, the Comprehensive Neo-Schumpeterian Economics (CNSE) approach challenges the short-term ori-entation of modern capital market approaches, as well as the market-failure-based approaches to an economic theory of the welfare state.

When considering the future orientation and qualitative composition of an economy, complexity issues combined with true uncertainty (about the optimal choices) enter economic theory and demand a new methodology. The prerequi-sites of long-term prolific economic development and growth depend not only on

entrepreneurship, but also crucially depend on the long-term orientation of capital markets faced with strong uncertainty, and a public sector willing to cope with the strong uncertainties and increasing complexities that confront modern econo-mies (Hanusch and Pyka 2007a; Hartmann et al. 2010). In other words, CNSE argues that innovation and uncertainty matter not just for industrial dynamics (on which most research has so far focused), but are also crucial for future-oriented financial markets and the public sector. The lack of a future orientation in only one of these economic areas could be a bottleneck that hampers all dynamic development processes, balanced growth and prolific development potential.

The empirical application of this approach to industrialized European and OECD countries has shown that there is no one single optimal design; different insti-tutional designs can be found. These different designs (e.g. the Scandinavian model, the Mediterranean model or the Central European model) co-exist and also change over time (Hanusch and Pyka 2007c, 2007d). To apply CNSE to develop-ing countries, specific strengths, weaknesses and structural differences have to be considered (Hartmann et al. 2010). For instance, development economics and global competitiveness research help to provide insights into the specific condi-tions and the range of problems in less developed countries. Several authors show the high cross-fertilization potential between innovation economics and comple-mentary approaches from development economics (Johnson et al. 2003; Arocena and Sutz 2005; Cassiolato and Lastres 2008; ECLAC 2008). Accordingly, the adaptation of CNSE to the specific conditions and challenges of developing coun-tries has to take into account the inability of a large percentage of the population to participate proactively in innovation and development, as well as the serious structural problems relating to economic efficiency and providing the economic opportunities for endogenous learning-by-solving processes (see also Arocena and Sutz 2005). Thus, when applying CNSE to developing countries, the effi-ciency and future orientation of their economic structure must receive greater attention, as should the enlargement of the capabilities of all actors so that they can contribute to innovation and the development of their countries and regions.

Nonetheless, we are still lacking a CNSE development approach able to combine the understandings of all three approaches (knowledge, market and state), con-sider evolutionary change and make individual actors the centre of interest.

2.4.2 Systems of innovation and development

An interesting effort to analyse innovation systems in developing countries has been undertaken by the Global Network for Systems of Learning, Innovation and Competence Building Systems (Globelics). Globelics has sought to engage in a deeper understanding of the interplay between innovation, learning and inequality. Researchers such as Johnson et al. (2003), Arocena and Sutz (2005), Cassiolato and Lastres (2008) and Lundvall et al. (2011) have contributed to the potential for cross-fertilization between development and innovation economics. For example Arocena and Sutz (2005) identified a fertile area for inter-section between Sen’s capability approach and the innovation system approach by

emphasizing that learning-by-solving requires a steady flow of opportunities to solve non-trivial problems. In a similar vein, Evers et al. (2006) pointed to the knowl-edge trap that emerges if the importing of knowlknowl-edge and technology does not foster endogenous learning processes and the creation of non-knowledge, or in other words the awareness of ignorance and of which further problems need or should be solved. Each problem-solving process and research activity intrinsi-cally leads to the creation of knowledge of what we do not know and what still has to be improved or further analysed. A lack of non-trivial technological problem-solving opportunities seriously hampers the capacity for endogenous capability upgrading and innovation (Arocena and Sutz 2005). Srinivas and Sutz (2008) claim that local and national efforts are needed to promote local capacities for endogenous problem-solving and innovation. A better understanding of scarcity induced innovation, however, is required.

To innovate or to solve problems in a technological universe characterized by scarcity requires the development of a series of skills – learnt by doing, by searching, by interacting and by solving – that are idiosyncratic: term them capacities to innovate in scarcity conditions.

(Srinivas and Sutz 2008, p. 135) These innovative capabilities must be understood before appropriate policies can be designed. Arocena and Sutz (2005) argued that a combination of both capabili-ties and opportunicapabili-ties is necessary to open up the way for evolutionary learning in underdeveloped settings. A good formal education is not enough if people do not have opportunities to apply and enlarge their capabilities through learning processes (Arocena and Sutz 2005). It is crucial that we understand that it is not just the lack of skills or capabilities of the agents (e.g. provided and fostered by education, health services etc.), but also the lack of opportunities (access to finance, information flows, a variety of economic activities) that prevents many people in developing countries from advancing through learning-by-doing, solv-ing processes and entrepreneurial action. Johnson et al. (2003) argued that a parallel emphasis on basic needs and innovation is necessary for the long-term development of national systems of innovation and competence building. Couto Soares and Cassiolato (2008) claimed that innovation and social policies need to be integrated to promote socially oriented innovation. Palliative interventions to tackle extreme poverty might not be enough to overcome the systemic reproduc-tion of inequalities. Long-term development requires a fertile nareproduc-tional innovareproduc-tion system (and science, technology and innovation (STI) policies) oriented towards people’s social needs.

Naturally, innovation is not the only factor impacting on inequality and pov-erty, but often it may have decisive feedback loops. Cozzen and Kaplinsky (2009) have shown that the causalities between innovation, poverty and inequality are not unidirectional, but multi-layered and complex. There is no straightfor-ward answer to the questions of whether one causes the other, or they are just coincidental and/or co-evolved. Sometimes innovation reflects and reinforces

inequalities and sometimes it undermines them. More in-depth analysis of the linkages between the different types of inequalities (e.g. horizontal or vertical inequalities), of innovation (e.g. process, product, functional and chain innova-tion) and of competence building is necessary (Cozzen and Kaplinsky 2009). For this reason, inequality research and innovation research can and should learn from each other. Furthermore there is increasing academic interest in the creation of indicators of innovation and well-being (Miller et al. 2008). However, several co-evolutionary and adaptive processes within and between different types of capabilities (Anand et al. 2009; Binder and Coad 2010a, 2010b) and types of inno-vation and innoinno-vation processes (Schumpeter 1912; Fagerberg et al. 2005; OECD 2005; Hanusch and Pyka 2007b) make the interrelations between innovation, ine-quality and well-being very complex (Miller et al. 2008; Cozzen and Kaplinsky 2009). For instance, a new technology or product (e.g. in ICT) could make some competences and products decline, or even become obsolete and hence people lose their jobs; on the other hand new jobs may be created in new sectors, pro-viding people with new choices. The effects may also not be static, but change over time; new demands on the skills of the people and companies may lead to stress and large initial inequalities, but then become more widespread, improving the overall educational level. In the same way, the initial effects of more choices through the creation of new sectors, life style, social security and leisure possibili-ties can be very positive, but without a proper selection and simplification can lead at some point to stress, ignorance within complexity and choices overload (see also Chapter 4). In turn this can trigger the creation of adaptation processes and better choices, such as more user-friendly product designs or services. Hence positive and negative effects may change over time and might not be equally dis-tributed across different people, groups and countries. To promote the positive and reduce the negative effects, the different agents of an innovation system need to constantly interact with each other, to (a) promote the future orientation of their economies, but also (b) prevent exclusion and very high levels of inequality and (c) develop mechanisms that constantly improve the capabilities of people to actively participate in the innovation and development process of their countries.

2.4.3 Modern economic competitiveness approaches

Mainstream economics research has also switched from monocausal analysis of development (emphasizing single factors such as capital accumulation) to a more integral and complex type of analysis (considering a varied set of factors): see World Bank (2003) and Lopez-Claros et al. (2006a, 2006b). Growth has been identified as a necessary but not sufficient element for development (UNDP 1990;

World Bank 2003). For example, in the World Development Report 2003 (World Bank 2003), economists from the World Bank argued that ensuring sustainable development requires that attention should be paid not to economic growth alone, but also to environmental and social issues. Unless the transformation of society and the management of the environment unite with economic growth, growth itself will be jeopardized in the long term. Even the mainstream economic measures

of competitiveness (being developed by neoclassical scholars, who have been so often blamed for their unrealistic world model) consider now a variety of elements, including a series of institutional, social and political domains. For example the Global Competitiveness Index (GCI), developed by Sala-i-Martin (Sala-i-Martin and Artadi 2004) to measure the competitiveness of countries, takes the following factors into account: (a) the fulfilment of basic requirements (e.g. infrastructure, macroeconomic stability, health and primary education); (b) efficiency enhancers (e.g. higher education and training, technological readiness); and (c) innovation and sophistication indicators as key indicators of competitiveness (e.g. in Lopez-Claros et al. 2006b).

Despite the substantial differences between the Neo-Schumpeterian, the human development and the neoclassical approaches behind the GCI index, the necessity of obtaining good values or at least minimum standards in these three dimensions is common sense. Humanity has an ethical responsibility to make human agency and welfare a focus of development policies; however, traditional key con-cepts in economics, such as market efficiency, macroeconomic stability, capital accumulation and economic growth, also remain important factors in economic development. Economic growth does not necessarily bring with it poverty reduc-tion (or higher levels of freedom), but without economic growth, it seems be also very difficult to provide more and better occupational choices.

2.5 Empirical example: Revealing different bottlenecks for