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WORLD BANK, WORKSHOP, November 19th 2010Innovation driven growth. Analytical issues and policy implicationsPaoloGuerrieri, University of Rome, La SapienzaCollege of…
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WORLD BANK, WORKSHOP, November 19th 2010Innovation driven growth. Analytical issues and policy implicationsPaoloGuerrieri, University of Rome, La SapienzaCollege of Europe, [email protected] Carlo PadoanOECD, ParisCollege of Europe, [email protected] . CONTENT The new features of innovation process such as open innovation, global innovation chains and the role of technology platforms such as internet As innovation is changing we ask how and to what extent the way we model innovation, and how we relate it to economic growth, need to be updated. Moving in this direction implies moving away from the traditional, growth accounting, linear relationship towards a systemic approach to modeling innovation. In this perspective we briefly describe the main features of a structural growth model that moves in the direction of a systemic approach
  • Finally, we use this structural model in order to simulate the impact of several policy interventions on countries’ innovation performances and economic growth referring to the case of Europe, that suffered a significant slowing down of its growth and productivity over the past two decades
  • Innovation is radically changing today
  • No longer we do view innovation as a linear progression from scientific research to discovery, to technological improvements, to finished products, to their diffusion across society
  • Today, innovation is regarded as a much broader phenomenon and recognized as comprising more complex and interactive processes
  • And innovation is radically changing today
  • The new innovation paradigm
  • innovation is “open” as we see more collaboration along side with competition among innovative actors;
  • there is a new geography of innovation, where global dimensions and local linkages interact;
  • we have to look beyond R&D, and consider more carefully the role of immaterial assets such as human capital and organizational changes, andthe role of services
  • innovation is increasingly based on technological platforms, such as ICT, that is becoming just as important as, or even more important than, “framework conditions”, in fostering innovation.
  • More collaboration between firms Companies collaborating on innovation, as a percentage of all firms, 2004-2006 Source: OECD based on Eurostat, CIS-2006 (April 2009) and national data sources. Source: OECD, based on CIS and national sources.
  • Global innovation networks
  • are emerging...
  • …with MNEs playing a large role ...that alter the topography of innovation. Broad based Leaders Narrow Leaders / Adopters Adopters / Followers link 8 Innovation is not only about R&D... New to market product innovators with and without R&D, 2004-06 (or latest) As a percentage of innovators ICT and the technological platforms
  • Innovation is increasingly based on technological platforms, such as ICT , that is becoming just as important as, or even more important than, “framework conditions”, in fostering innovation.
  • Internet is the “Great Facilitator” of our times, a General Purpose Technology that has allowed the development of a number of technology platforms.
  • In most cases innovation activities in firms today has a systemic nature since it is a broad, pervasive phenomenon and depends heavily on external sources.
  • Innovation is key to growth... Contributions to labour productivity growth, 1995-2006, in % * Investment in intangibles and multi-factor productivity growth account for between two-thirds and three-quarters of labour productivity growth. Challenges for modelling
  • As innovation is changing we must ask how and to what extent the way we model innovation, and how we relate it to economic growth, need to be updated.
  • It is straightforward to extend the traditional model to take some aspects of new growth theory into account
  • The linear model can be augmented as follows
  • Y=(A K H T I W)
  • The new features of innovation call for further steps.
  • In particular they require to move towards a system approach to innovation where the structure of the system and the linkages among the variables need to be considered explicitly
  • so that they can account better the process of production of ideas which is taken as the major source of growth.  
  • Challenges for modelling
  • We have endogenized (in part) the variables entering of the growth equation.
  • So as to suggest how and to what extent the features of the new innovation paradigm recalled previously can be related to the growth accounting framework.
  • We propose the following set of relationships (1)-(8) that is, at best, a “sketchy system”.
  • Y=(A K H T I W)
  • K=K (H, I, W, F, C, …)
  • H=H(K, I, W, U, E…..)
  • S=S(Y, T, I, H, K, R)
  • T=T (H, RD, IP, W, I, U, F, A ....Y, K, C)
  • I=I (H, K, T, RD, Y, R, C, A, …)
  • W=W(K, H, I, ...T,A, ....F, R, IP...Dist)
  • (8) A=A (T, I, H, K, RD….W, U,C, ….F, R, IP, ...Y)
  • The SETI Model How can we move from a theoretical framework (and still in implicit form) to a system amenable to empirical analysis ? One way forward is through a dynamic system approach that can be modelled and estimated rigorously to capture the systemic nature of innovation In the paper we briefly describe the main features a of a model (Guerrieri and Padoan, 2007 and Guerrieri, Maggi and Padoan 2009) that moves in the direction sketched above. The model develops the system approach including some of the elements of the New Paradigm of innovation discussed above: international dimensions, services and, ICT. Model equations: Output DlogY =f1(T, Sh,Sm,K,L) Domestic Services DlogSh =f2(Y,T,STR,ICT,REG) Imported Services DlogSm =f3(Y,T,STR,ICT,REG) Technology Dlog T = f4 (HK,HKR,Sh,Sm,Y,dist) . The structure of the model(1) The model is specified and estimated as a set of continuous time dynamic equations where Dlog stands for the derivative with respect to time and hence left hand side variables are the rate of change of the endogenous variables.
  • Output growth is a function of (exogenous) labor and capital accumulation as well as of endogenous accumulation of technology and business services.
  • Business services, including communication, financial services and insurance, both domestically produced and imported, grow with output and technology
  • Technology grows with output, services and, through diffusion, with foreign technology, also given the contribution of human capital in both receiving and sender countries.
  • The intangible and information-based nature of services gives the generation and use of ICTs a central role in innovation activities and performance that cannot be captured entirely by patents.
  • . The structure of the model (2)
  • Domestic technology grows also to the extent that it can absorb technology produced in other countries.
  • The amount of foreign produced technology that can be used domestically is limited by distance and absorption capacity in the receiving country
  • The impact of distanceis allowed to vary over time to the extent that technological progress brings forward a reduction in the cost of technology diffusion.
  • Technological accumulationalso depends on imports of services.
  • Regulationimpacts in the production and import of services, and hence on growth in two different ways. A) National regulation intensity depresses the production of services B) Uniform (and low) levels of regulation across countries favor production and import of services.
  • The SETI Model Used for Policy Simulations ICT as a GPT: for Policy Simulationsthe framework for policy simulations with the enhanced SETI model Innovation policy and economic growth for Policy Simulations First, results with the structural model simulation confirm that:
  • innovation and technology accumulation are enhanced especially by human capital accumulation, also because it allows to exploit the benefits of knowledge diffusion across countries; 2) business services are a powerful driver of growth and deeper integration in the European market for producers of services does indeed significantly contribute to growth; 3)delays in implementing policy reforms are very costly;
  • Figure 5. Comparing different policy scenarios for Policy Simulations Blue line = Scenario Investment in ICT; Red line = Scenario Deregulation; Green line = Scenario Human Capital; Cyan line = Scenario Structural Changes. Each line represents the percentage difference with respect to the baseline scenario. Figure 6. The Cost of Delaying Reforms (Deregulation) for Policy Simulations Blue line = Scenario Deregulation; Red Line = Scenario Deregulation in 10 years. Each line represents the percentage difference with respect to the baseline scenario. Innovation policy and economic growth II for Policy Simulations Second, we should promote improvements in economic structure as these are effective in stimulating ICT diffusion and innovations. Precisely because of its GPT nature, ICT introduction requires not only a specific investment in ICT equipment but, even more importantly, a number of facilitating factors that generate the appropriate environment for ICT diffusion. Third, we cannot rely on a single instrument to boost innovation and, through it, productivity and growth since a joint implementation of policies generates effects that are higher than the sum of those obtained by implementing policies separately. For instance our results show that the EU output growth can be significantly increased if the availability of business services and the accumulation of knowledge and ICT diffusion are enhanced. Figure 7. Coordination of policies: the Aggregate Effect. for Policy Simulations Increasing Human Capital and De-Regulating Policy Implications from the broadening of innovation for Policy Simulations
  • A pervasive driver of change: more than R&D, also design, business models, organisational change
  • Importance broad based human capital: hard and soft skills, including entrepreneurship
  • Use of ICT to build networks; informatics as a multidisciplinary field
  • Developing knowledge networks and markets
  • Systemic approach: “push” / supply and “pull” / demand policies
  • Thanks for Policy Simulationsforyourattention Figure 2. for Policy SimulationsDeregulation and/or Harmonization Blue line = Scenario Deregulation; Red Line = Scenario Harmonization. Each line represents the percentage difference with respect to the baseline scenario. Figure 3. A 5% increase in the level of human capital for Policy Simulations Figure 4. The impact of for Policy Simulationsstructural changes *an increase of ICT on service and of service on both ICT and technology Figure 5. Comparing different policy scenarios for Policy Simulations Blue line = Scenario Investment in ICT; Red line = Scenario Deregulation; Green line = Scenario Human Capital; Cyan line = Scenario Structural Changes. Each line represents the percentage difference with respect to the baseline scenario. Figure 6. The Cost of Delaying Reforms (Deregulation) for Policy Simulations Blue line = Scenario Deregulation; Red Line = Scenario Deregulation in 10 years. Each line represents the percentage difference with respect to the baseline scenario. Figure 7. Coordination of policies: the Aggregate Effect. for Policy Simulations Increasing Human Capital and De-Regulating
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