ࡱ> 5@Vbjbj22 sXXsm4(RRRfN)N)N)8)j*lf m*+"+(+f,--- k k k k k k krRuF kRU-"-UU k (2 +pf,Sl`a`a`aURf,Rf, k`aU k`a*`aaVi@RRjf,* >N)]i jl0 m jxUu`Uujff  RRUuRjt- ; `aEM--- k kffJ$>a"ffJ$ CROATIAN INNOVATION POLICY AND ITS EFFECTS Discussion Materials for the GDN Conference Prague, August 14-17, 2004 Draft version - please do not quote without permission - Project coordinator: Domagoj Ra i ( HYPERLINK mailto:dracic@eizg.hr; dracic@eizg.hr) Research team: Zoran Aralica ( HYPERLINK mailto:zaralica@eizg.hr zaralica@eizg.hr) Katarina Ba i ( HYPERLINK mailto:kbacic@eizg.hr kbacic@eizg.hr) Domagoj Ra i ( HYPERLINK mailto:dracic@eizg.hr; dracic@eizg.hr) Dubravko Radi ( HYPERLINK "mailto:radic@wiwi.uni-frankfurt.de" radic@wiwi.uni-frankfurt.de) Consultant: Slavo Radoaevi ( HYPERLINK "mailto:s.radosevic@ssees.ac.uk" s.radosevic@ssees.ac.uk)  HYPERLINK "http://www.gdnet.org/index.html"  INCLUDEPICTURE "http://www.gdnet.org/images/header/GDN_logo.gif" \* MERGEFORMATINET  PART ONE RESEARCH PROJECT DOCUMENT Croatian Innovation Policy and Its Effects - Abstract- Recently, the relationship between innovation and economic growth has become widely recognised. Within transition countries, that is facilitated by both exhaustion of growth and productivity improvements based on non-investment reallocations and the integration into the European Union, which states the development of a knowledge-based economy as a crucial policy goal. The research project demonstrates how a national innovation policy can facilitate restructuring, technological advancement and economic growth in Croatia, and assesses the achievements in that regard so far. The project positions innovation policy within the general economic policy framework and analyses the innovation-facilitating institutional, fiscal and financial mechanisms implemented by the policy makers. Moreover, summary of the level of innovative activities in Croatia, and the evaluation of the effects of the emerging innovation policy are provided. Finally, the project deals with the barriers to innovation, and further challenges and policy options that could lead to a more effective innovation policy. The project involves two papers with different but complementary methodologies. The first one assesses the treatment effects of selected policy instruments and other determinants of innovation activities by using a probit model that estimates their contribution to innovation propensity, controlling for the sample selection problem. The second one involves a descriptive analysis of innovation policy and its basic outcomes, complemented by relevant statistics and indices (some based on the European Innovation Scoreboard, some purposively constructed). Croatian Innovation Policy and Its Effects a) Research questions: 1. What are the key features (scale, patterns, and determinants) of innovative activities of Croatian manufacturing and service enterprises and what are their implications for policy? 2. To what extent and in which ways can an innovation policy facilitate innovative activities and contribute to restructuring, technological advancement and economic growth in Croatia and what have been the achievements in that regard so far? b) The issues addressed by the research project: The relationship between innovation and economic growth Recent years have seen the emphasis of the relationship between innovation and economic growth. At the macroeconomic level, innovation tends to contribute to the accumulation of capital, and growth of employment and multifactor productivity (OECD, 2001). However, the relationship between research and development (R&D) expenditures and growth is not straightforward. Although significant, aggregate R&D explains limited part of variation of growth. This suggests that the factors such as allocation of R&D resources, and the mechanisms of creation, dissemination and commercial exploitation of knowledge matter fundamentally. These factors are significantly influenced by the national innovative capacity (Stern, Porter and Furman, 2000), which covers the ability of a country to produce and commercialise a long-term flow of innovative technology. R&D or ability to generate new knowledge is only one component of broader concept of national innovative capacity. Among other issues, national innovative capacity depends on the strength of a strong common innovation infrastructure, i.e. cross-cutting factors that contribute to innovation throughout the economy. Hereby the crucial factors include the science and technology policy, mechanisms for the support of basic research, and the accumulated stock of technological knowledge including diffusion and utilisation of the existing knowledge. Consequently, government policies can play an influential role in the facilitation of innovation - notably through support for R&D, education and labour market policies, entrepreneurship support, and the promotion of interaction among different organisations within the national innovation system (including the research institutions, business firms and government alike). Innovation policy in transition economies The realisation of the role of innovation policy has traditionally been stronger in more advanced economies. The transitional countries in Central and Eastern Europe (CEE) have initially focused their policy efforts on macroeconomic issues and measures (cf. Bu ar and Stare, 2002). However, the realisation of the importance of innovative activities and innovation policy has recently been facilitated by two key factors. Firstly, there has been an exhaustion of growth and productivity improvements based on defensive restructuring and non-investment reallocation of resources (cf. Mickiewicz and Radoaevi, 2001). Since competition on the basis of low wages is an unfavourable and unsustainable strategic option for most of these economies, their long-term competitiveness requires technological advancement and the development of innovative capacities. Moreover, most of these countries are being integrated into the European Union. The EU not only states the development of a knowledge-based economy as a crucial policy goal for its current members, but also requires from the candidate countries to demonstrate the same orientation. Namely, innovation and increased technological change in new member states are viewed as fundamental to their economic convergence with current members and the cohesion of the enlarged EU. Consequently, maintenance of productivity and GDP growth require new mechanisms for supporting innovation and industrial upgrading (cf. EC, 2001: 11). Furthermore, the EU is already the main foreign trade partner and the source of FDI for transition economies during the pre-accession period, which reinforces the need for maintaining and improving internal and external competitiveness. In terms of relative wages, Croatia is faring badly in comparison to the rest of CEE, which undermined the competitiveness of several traditional export-oriented sectors (e.g. textiles and apparel industries). On the other hand, retarded levels of technological capacity and product and process innovation have not provided an alternative route to competitiveness. The examples of internationally competitive innovations have been sporadic (e.g. the pharmaceutical company Pliva) and they have rarely induced strong spillover effects. Moreover, inadequate factor markets (i.e. inflexible labour market and underdeveloped capital market) and insufficiently supportive policy mechanisms have even encouraged dislocation of certain activities to other CEE countries. Deteriorating export competitiveness has been observed both in the EU and CEFTA markets. Croatian innovation policy within its economic policy Therefore, the necessity for the development of innovative activities supported by adequate innovation policy is paramount for the catching up in terms of technological advancement, product and process developments and the resulting competitiveness of the Croatian economy. However, the realisation of this need by researchers and policy makers and the development of adequate policy mechanisms have been relatively slow and occasionally inconsistent. The economic policies mostly focused on macroeconomic stabilisation, reforms of the financial system, taxation and the pension system, and liberalisation of trade and exchange regimes. When it came to microeconomic issues, the policies have often been related to privatisation and restructuring of existing enterprises; even in these areas the success has been mixed due to political influences and weak institutional frameworks. Consequently, not enough emphasis was given to the issues of new enterprise development, promotion of innovative activities, creation and effective functioning of interfaces between research community and industry, or the facilitation of integration of innovative enterprises into local, national and global industrial networks. Moreover, due to inadequate investment promotion policy, the FDI inflows have predominantly occurred through privatisation of existing firms for market seeking reasons, mainly in three sectors (pharmaceutical industry, banking and retail), and they have not resulted in significant technology transfers or spillovers. More recently, there have been improvements within the area of the issue of enterprise development: new credit lines have been secured, and better technical assistance to entrepreneurs provided, which had noticeable effects on the performance of the SME sector and led to wider acknowledgement of its role in the economic growth and job creation. Institutional and regulatory frameworks: structures, relationships and challenges The project analyses the institutional framework for innovation. The focal institution for science and technology (S&T) and innovation policy issues has been the Ministry of Science and Technology, which has been involved in organisation and financing in the areas of scientific research, technological development, higher education, development of activities related to information technology, as well as international scientific and technological cooperation. The role of other relevant governmental institutions (relevant ministries, implementing agencies etc.) and their stakeholders (entrepreneurship support centres, business incubators, technology parks, professional and business associations) will also be assessed and evaluated. The project also analyses crucial legal, fiscal and financial provisions and instruments that have been established to promote innovation in enterprises, as well as the key business regulatory issues, such as the factors hindering the creation of firms, bankruptcy laws, administrative and taxation burden and intellectual property law. On the basis of analysis of the aforementioned factors, the project identifies the most important barriers to enterprise development through innovation, which are related to the cultural, institutional, economic, managerial/strategic and policy issues. Finally, key challenges and policy options that could lead to a more effective innovation policy are discerned. Determinants of innovation activities and the role of policy instruments A firms propensity to innovate is a complex combination of internal and external factors, which is reflected in the growing econometric and managerial literature concerned with that topic (for a partial overview see e.g. Read, 2000). Despite some occasional regularities, exact innovation determinants that characterise particular firms, industries, regions or countries in particular periods of time may vary and thus need to be discerned empirically on the basis of (periodically) collected and analysed data. The factors that stimulate or hinder innovative activities in particular firms can be firm or market-specific. According to Hujer and Radi (2003), market factors may include, competition intensity, market concentration, exposure to international trade, as well as demand factors like profitability and expectations regarding the future development of business. Firm specific factors can be divided into internal and external technological capabilities. Namely, sectors display different technological opportunities (which are often related to the maturity of the sector), which then affect the innovation behaviour of individual firms. Additionally, innovations can be boosted if firms co-operate with other institutions, but in order to make such co-operation beneficial, the firm must already possess adequate technological expertise, which are related to different forms of investment. External technological capabilities may be captured by variables indicating R&D-cooperation with other institutions like universities, or other firms. Internal technological capabilities may include the state of technology, the existence of an R&D department, the share of highly qualified employees and employees devoted to R&D. Other firm specific factors which are also often included in the estimation are the size of establishments measured by the number and squared number of employees, as well as industrial and regional dummies. Policy instruments such as different forms of R&D subsidies are also an important factor that can facilitate innovation activities (cf. Criscuolo and Haskel, 2003). Formulation, implementation and modification of an effective and efficient innovation policy need to be informed by the relevant research. However, the impact of policy instruments is not unproblematic, for example due to sample selection effects. The evolution (or cancellation) of policy instruments should therefore depend upon their evaluation; where possible, it is advisable to discern their treatment effects (see below). c) Assessing the innovation policy in Croatia: a methodology Outline It is proposed that two papers are produced. The first one assesses the treatment effects of selected policy instruments and determinants of innovation activities by using a probit model that estimates their contribution to innovation propensity, controlling for the sample selection problem. The second one involves a descriptive analysis of innovation policy and its basic outcomes, complemented by relevant statistics and indices (some based on the European Innovation Scoreboard, some purposively constructed), as well as the results of the first paper. The separation of the papers is motivated by methodological and pragmatic considerations. They methodological concerns include the differences in types of data and analyses that are being undertaken, which should be reconciled with the need for focused argumentation and methodological consistency within each paper. Moreover, since the results of the microeconometric analysis will be incorporated into broader evaluation of innovation policy, it will reinforce its validity. The pragmatic concerns justifying the separation of the papers pertain to the maximisation of potential impact within the academic and policy- making communities, given that such analyses have not been undertaken in the case of Croatia so far. Namely, the analytical apparatus (i.e. the microeconometric analysis) will be applied in an academically sound way, resulting in a paper that can be considered by a relevant international economic journal. The paper addressing broader innovation policy issues would be communicated to wider social science audience and the policy-making community in Croatia and abroad, most likely through a social science / policy journal. In addition to the provision of results that can be benchmarked against other transition economies, the paper is expected to contribute (in substantive and methodological terms) to the discussion on innovation policy within the debates on transition and EU accession in Central and Eastern Europe (and Southeast Europe in particular). Data sources: Community Innovation Survey and others The key source of data is being obtained through the first Community Innovation Survey (CIS) in Croatia. In this survey enterprise-level data are collected in accordance with the Oslo Manual (OECD, 1996) guidelines and the available literature on the implementation of CIS III (e.g. Kurik et al.2002; Boia et al., 2003a). The survey covers the period from 2001 to 2003. In addition to general information about the enterprise, the survey includes the data on the following aspects of innovation activities: product and process innovation, expenditures on innovation activities, intramural research and experimental development, innovation cooperation, sources for innovation, factors hampering innovation activities, innovation protection, and important strategic and organisational changes in the enterprise. The survey is based on a stratified representative sample of all Croatian enterprises in relevant manufacturing and service sectors. Consequently, the survey is to provide comprehensive overview of innovative activities in Croatian enterprises, which should form a basis for the formulation of more effective innovation policy. Although the survey provides a fairly comprehensive data set, it also has a number of important shortcomings that can affect the validity and usefulness of the data, which have been tackled, among others, by Archibugi and Pianta (1996), Radoaevi (1998) and Criscuolo and Haskel (2003). However, the shortcomings can be controlled to some extent by careful survey implementation and subsequent application of analytical techniques (for an example, see Boia et al., 2003b). Given the richness of the dataset collected within the CIS, only some of its aspects can be tackled within the proposed project. At the same time, limitations of the data and the discussion of innovation policy issues necessitate the use of aggregate data on R&D and other issues addressed by the European Innovation Scoreboard (see Appendix), available academic literature on national innovation systems, policy documents, reports etc. Paper on the determinants of innovation and treatment effects of policy instruments The first paper will assess the key determinants of innovativeness of enterprises, using microeconometric evaluation methods. Thereby special attention will be spent on selected policy instruments, such as R&D subsidies, using microeconometric evaluation methods. The dependent variable of the probit model will be innovation propensity of an enterprise, measured by the decision to improve existing product/service, or to introduce an incremental or radical innovation within a specific period. As outlined above, explanatory variables might include investment, employees, existence of an R&D department, competition pressure, linkages with external organisations etc. The size-, regional and sector-related dummies are to be included, too. We expect that size, like in other surveys, will be one of the significant variables. When it comes to dealing with treatment effects of policy measures, microeconometric evaluation methods will provide a starting point (cf. Hujer and Radi, 2003). One severe problem which arises in this context is due to sample selection. In recent studies it has been found that establishments which have a higher propensity to innovate are also those which are more likely to receive a public subsidy. In this case a simple mean comparison by treatment status or including such a treatment variable in a regression model will yield an upward biased estimate. Basically there are two ways to overcome this problem: Non-parametrical methods like e.g. matching-methods or parametric approaches, e.g. instrumental variable estimators. Intuitively, matching estimators try to approximate the counterfactual outcome of subsidized establishments, i.e. their outcome under no subsidy, by finding in a large group of non-subsidized those which are similar to the subsidized ones in all aspects except for the fact that they have not received a subsidy. If sample selection is solely due to observables, the difference in the outcome variables between subsidized and non-subsidized is attributable to the subsidy. The various proposed matching estimators differ in the way how the control group is constructed (for an overview see e.g. Heckman, Ichimura and Todd (1998)). The advantage of matching estimators is that they make no functional form assumptions. However, they all assume that sample selection is solely due to observable characteristics which could be a too restrictive assumption in our case. If e.g. management ability or corporate culture play an important role in both determining the innovation behaviour and the decision whether establishments will successfully apply for a public subsidy or not, matching estimators will still be plagued by a hidden bias. Hence, alternative estimation strategies are called for. Examples include the instrumental variable approach (see e.g. Angrist (1991)) which, however, rests on the necessity of finding valid and reliable instruments in the dataset, i.e. variables which only affect the decision to apply for a R&D-subsidy but do not affect the outcome-variable of interest. Paper on broader innovation policy issues The second paper will provide a descriptive analysis and assessment of various aspects of innovation policy (as outlined above) and its basic determinants in terms of structure, levels, and trends of R&D and innovation activities. That will include the use of relevant descriptive statistics and indices. In addition to the indicators within the European Innovation Scoreboard framework (see Appendix), which enable comparison to both the EU and accession countries, some additional indicators will be purposively constructed to address the institutional and technological particularities of the situation in Croatia. Moreover, the data from the Community Innovation Survey (cf. Pianta and Sirilli, 1998) and the results of the first paper will also be used for policy evaluation. The second paper will thus provide an initial assessment of the performance of innovation support mechanisms, fiscal and financial incentives, programs of the Ministry of Science and Technology related to R&D, innovation, and the cooperation between business firms and research institutions (cf. Radas et al, 2002a). In methodological terms, such an approach is built upon the research on the use of innovation surveys for policy evaluation (cf. Pianta and Sirilli, 1998), economic implications of innovation policy (e.g. Archibugi, Howells and Michie, 1999; Bu ar and Stare, 2002; Havas, 2002), national innovation policy profiles (e.g. Bu ar and Stare, 2001) and analysis and management of national innovation systems (e.g. Nelson, 1993, OECD; 1999). Appendix: European Innovation Scoreboard indicators The European Innovation Scoreboard ( HYPERLINK "http://trendchart.cordis.lu/Scoreboard/scoreboard.htm" http://trendchart.cordis.lu/Scoreboard/scoreboard.htm) contains 17 main indicators, selected to summarize the main drivers and outputs of innovations. The indicators are divided into four groups: Human resources for innovation (5 indicators): S&E graduates / 20-29 year old population % economically active population with 3rd level education % working population in life long learning % employment in high-tech manufacturing % employment in high-tech services Knowledge creation (3 indicators, one of which is divided into European Patent Office and United States Patent and Trademark Office patents): -Public R&D funding/GDP -Business expenditure R&D/GDP -EPO high-tech patents/population 3. Transmission and application of knowledge (3 indicators): -% SMEs innovating in-house -% SMEs in co-operative innovation -% innovation expenditure/total sales 4. Innovation finance, outputs and markets (6 indicators): -% venture capital/GDP -% new capital/GDP -% new-to-market products/total sales -Home internet access -% ICT markets/GDP -Change 1993-97 high-tech value added d) Selected bibliography Angrist, J. D. (1991), Instrumental Variable Estimation of Average Treatment Effects in Econometrics and Epidemiology, Discussion Paper. Cambridge: National Bureau of Economic Research. Archibugi, Daniele, Jeremy Howells and Jonathan Michie (eds.) (1999): Innovation Policy in a Global Economy. Cambridge: Sambridge University Press. Archibugi, Daniele and Mario Pianta (1996): 'Innovation surveys and patents as technology indicators: the state of the art', in OECD: Innovation, Patents and Technological Strategies, Paris, pp 17-50. Paris: OECD. Archibugi, Daniele, Bengt-Ake Lundvall (eds.) (2001): The Globalizing Learning Economy. Oxford: Oxford University Press. Arvanitis, S. (1997): 'The Impact of Firm Size on Innovative Activity - An Empirical Analysis Based on Swiss Firm Data', Small Business Economics, 9, pp. 473490. Boia, Manuel Joao, Pedro Conceio and Rui Santos (2003a): 'Implementation and Results of the Third Community Innovation Survey for Portugal'. Working Paper. Lisbon: Instituto Superior Tcnico. Boia, Manuel Joao, Pedro Conceio and Rui Santos (2003b): Determinants of Innovation in Portugal: Designing, Implementing and Analyzing Evidence from the Third Community Innovation Survey. Lisbon: Instituto Superior Tcnico. Bu ar, Maja and Metka Stare (eds.) (2001): Innovation Policy Profile: Slovenia. ADE: Louvain. Bu ar, Maja and Metka Stare (2002):  Slovenian Innovation Policy: Underexploited Potential for Growth , Journal of International Relations and Development, 5(4), pp. 427-448. Cleaver, Kevin (2002): Preliminary Strategy to Develop a Knowledge Economy in European Union Accession Countries. Working Paper. World Bank Europe and Central Asia Region - Environmentally and Socially Sustainable Development. Criscuolo, Chiara and Jonathan Haskel (2003): 'Innovations and Productivity Growth in the UK: Evidence from CIS2 and CIS3'. Discussion Paper. London: CeRiBA - Office for National Statistics. Devai, Katalin, Gabor Papanek and Balasz Borsi (2002): Methodology for Benchmarking RTD Organizations in Central and Eastern Europe, Budapest: Budapest University of Technology and Economics. Dosi, Giovanni (2000): Innovation, Organization and Economic Dynamics, Cambridge: Cambridge University Press. Dunning, John H. (2000): Regions, Globalization and the Knowledge Based Economy, Oxford: Oxford University Press. European Commission (2001): Innovation Policy Issues in Six Candidate Countries: The challenges - Cyprus, Czech Republic, Estonia, Hungary, Poland and Slovenia. Luxembourg: Directorate-General for Enterprise, Office for Official Publication of the European Communities. European Commission (2003): Innovation Policy Issues in Seven Candidate Countries: The challenges - Bulgaria, Latvia, Lithuania, Malta, Romania, Slovakia and Turkey. Luxembourg: Directorate-General for Enterprise, Office for Official Publication of the European Communities. Fornahl, Dirk and Thomas Brenner (eds.) (2003): Cooperation, Networks And Institutions In Regional Innovation Systems. Cheltenham: Edward Elgar. Harris, Mark N., Mark Rogers and Anthony Siouclis (2001): 'Modelling Firm Innovation using Panel Probit Estimators'. Working Paper No. 20/01. Melbourne: Melbourne Institute. Havas, Attila (2002): Does Innovation Policy Matter in a Transition Country? The Case of Hungary'. Discussion Paper 05/2002. Budapest: The Institute of Economics, Hungarian Academy of Sciences. Heckman, J., H. Ichimura And P. Todd (1998), Matching as an Econometric Evaluation Estimator, Review of Economic Studies, 65, pp. 261-294. Hujer, R. and Radi, D. (2003):  Evaluating the Impacts of Subsidies on Innovation Activities in Germany , Discussion Paper. Frankfurt: Faculty of Economics and Business Administration, Johann Wolfgang Goethe-University.  HYPERLINK "http://much-magic.wiwi.uni-frankfurt.de/Professoren/hujer/papers/rd_eva.pdf" http://much-magic.wiwi.uni-frankfurt.de/Professoren/hujer/papers/rd_eva.pdf Kurik, Silja, Rnno Lumiste, Erik Terk and Aavo Heinlo (2002): 'Innovation in Estonian Enterprises 19982000'. Talinn: Estonian Institute for Futures Studies. Lefebvre, E., L. Lefebvre, and M. Bourgault (1998): 'Research and Development- Related Capabilities as Determinants of Export Performance', Small Business Economics, 10, pp. 365 377. Mickiewicz, Tomasz and Slavo Radoaevi (2001):  Innovation Capabilities of the Six EU Candidate Countries . London: School of Slavonic and Eastern European Studies. Nelson, R.R. (ed.) (1993): National Systems of Innovation: A Comparative Study, Oxford: Oxford University Press. OECD (1996): The Measurement of Scientific and Technological Activities: Proposed Guidelines for Collecting and Interpreting Technological Innovation Data (Oslo Manual). 2nd edition. OECD: Paris. OECD (1999): Managing National Innovation Systems. Paris: OECD. OECD (2001): Science, Technology and Industry Outlook: Drivers of Growth Information Technology, Innovation and Entrepreneurship. Paris: OECD. Pianta, Mario and Sirilli, Giorgio (1998): The Use of Innovation Survey for Policy Evaluation. IDEA Paper Series. No.2/98. Oslo: STEP. Singer Slavica et al. (2003): Global Entrepreneurship Monitor (GEM) Croatia. Zagreb: CEPOR. Stern, Scott, Michael E. Porter and Jeffrey L. Furman (2000): The Determinants of National Innovative Capacity . NBER Working Paper No. 7876. Cambridge: National Bureau of Economic Research. Radas, Sonja et al. (2002a): Institutions, measures, mechanisms regarding fiscal and financial incentives instruments for research and development activities, in the purpose of technological development, with a particular emphasis on the cooperation between research institutions and the business sector. Zagreb: The Institute of Economics. Radas, Sonja et al. (2002b): Global Competitiveness Report Analysis of Croatia. Zagreb: The Institute of Economics. Radoaevi, Slavo (1998):  Patterns of Innovative Activities in Countries of Central and Eastern Europe: An Analysis Based on Comparison of Innovation Surveys . Science Policy Research Unit Working Paper No. 34. Brighton: University of Sussex.  HYPERLINK "http://www.sussex.ac.uk/spru/publications/imprint/sewps/sewp35/sewp35.html" http://www.sussex.ac.uk/spru/publications/imprint/sewps/sewp35/sewp35.html Read, Anthony (2000): Determinants of Successful Organisational Innovation: A Review of Current Research', Journal of Management Practice, 3(1), pp.95-119. Symeonidis, G. (1996): 'Innovation, Firm Size and Market Structure: Schumpeterian Hypotheses and Some New Themes', OECD Economics Department. Working Paper No. 161. Paris: OECD. PART TWO ON INNOVATION POLICY - additional materials- 1. Innovation policy - a pivotal strategic tool in achieving competitiveness and growth in the European Union The rise of the new economy formed in the context of globalization and the increasing importance of information and communication technologies (ICT), have pushed European Union (EU) to set a long-term strategic determination to become the most competitive and dynamic knowledge-based economy in the world. The transition towards knowledge-based society is perceived as a way of keeping the pace with EUs global competitors. Within the framework of Lisbon European Council Summit held in March 2000, innovations are perceived as a foundation of the transition to a knowledge-based society. Therefore, innovation policy has become the central strategic tool in achieving competitiveness of industries and consequentially, maintaining and stimulating economic growth in EU. EUs approach to innovation policy is multifaceted. Elements of innovation policy are found both in industrial and enterprise policy. That attitude has reflected itself in the Lisbon strategy (as the official document of the Lisbon Council Summit) that proposes establishing a European Area of Research and Innovation and creating a friendly environment for starting up and developing innovative businesses. Small and medium-sized enterprises are seen as drivers of innovations. As way of ensuring achievement of those goals, EU proposed encouragement of key interfaces in innovation networks: between companies and financial markets, R&D and training institutions, advisory services and technological markets. The conclusions of the Summit do not remain declaratory, but are rather well envisioned in formal documents in terms of financial planning, effective monitoring, assessing and evaluating. The importance of the strategic determination towards strengthening innovation processes in EU is visible in the follow-up events. The Barcelona Summit in March 2002, where the European Council reviewed the progress made on basis of Lisbon Strategy, confirmed devotion to fostering innovation and called for a more significant boost of the overall R&D and innovation activities in the Union. In the conclusions, the Council has expanded requirements for spending on R&D (aimed to reach about 3% of GDP by 2010, with 2/3 of the investment coming from the private sector). Moreover, a call was made to strengthen business R&D through an integrated strategy involving increased competition on product markets, better access to risk capital, as well as better protection of intellectual property rights, and improved networking and technology diffusion. Commissions Communication on Innovation Policy in 2003 also expanded policy conclusions based on the Lisbon strategy. The Communication asked for a broadly defined concept of innovation, so that policy design would not omit less obvious or known types of innovation. It also demanded that innovation policys interaction with other policy areas such as industrial policy be better coordinated and followed up. In the Communication Industrial Policy in an Enlarged Europe innovation is outlined as a key factor of industrial competitiveness together with knowledge and entrepreneurship. The Communication expresses that European industry needs to become more innovative through constant initiating, refining and improving its products, services and processes. Innovation created through developing risk-taking mentality of entrepreneurs is stressed upon. Green Paper on Entrepreneurship considers innovation as one of its key challenges. The Paper stipulates as one of the priorities that a culture of innovation in the business context be promoted. 2. Status of Croatias innovation policy in the light of EU enlargement Croatia has since the onset of its political transition to democracy been oriented towards joining the EU and has throughout that period made serious steps towards achieving its goal. In its answers to the Questionnaire of the European Commission in 2003, which later served as a base for obtaining candidate status for EU accession, Croatia has stipulated among microeconomic and structural priorities establishing a modern innovation system. That should help Croatia create the key condition for achieving long term economic development. The modern innovative system that the country aspires to was defined as a system that encourages cooperation among educational and scientific system, technology development, government institutions and private enterprises. European Commission granted Croatia candidate status in 2004. In its Opinion on Croatias application to the EU membership (CEC, 2004), the Commission regards Croatia as a functioning market economy. However, greater efforts are to be taken in the filed of innovation policy to make it competitive and efficient at the European level. Firstly, as an overall measure, government expenditure on research and development in Croatia (1.09% of GDP) is below the EU average (1.99%) as well as the share of private sectors expenditure on research and development. Secondly, radical changes are needed in the scientific and higher education policies in order to integrate them into the European Research Area. A national industrial strategy, which should incorporate elements of innovation policy in order to raise industrial competitiveness, has yet not been adopted independently of the general economic policy. And lastly, another complement to modern innovation policy, the enterprise policy, is assessed as small and medium-sized enterprise (SME) policy in the formal documents. Innovation policy is integral with SME policy in that it has put forward the Croatian Innovation Technology Development Programme (HITRA) specifically aimed to support technology transfer to SMEs with financial and non-financial incentives. On the national level, a politically independent advisory body that tries to foster and improve Croatias competitiveness National Competitiveness Council, placed development of innovativeness and technology as one of top political and economic priorities. The Council perceives innovation as a permanent basis for maintaining competitiveness through productivity improvements. That view is in line with the EUs strategic determination to become a knowledge based-economy by fostering innovation. The results of the Councils work is a document entitled 55 Recommendations for improving Croatias competitiveness which may serve as a basis for policy formulation. In the document, innovation policy is addressed in terms of what it should become and not in terms of what it is at the moment. Therefore, the Council outlined several principles of modern innovation policy that should help Croatias innovation policy to move towards a modern approach to innovation policy and as an outcome strengthen links among technology, innovativeness and economic growth. Those principles are designed for establishing a market-oriented innovation policy that will: strengthen components of innovation capability (absorptive capacity, demand, innovation diffusion and R&D), lead to productivity growth and strengthen knowledge component in new investments. 3. Importance of innovation for economic growth and competitiveness There is a general consensus among economists that technological innovation plays a central role in the process of long-run economic growth (Radoaevi, 2003a: p. 4). While neoclassical growth theory did not elaborate how the technological progress is achieved, although it perceives it as a source of growth, the following group of models - endogenous growth models have gone further. In the endogenous growth models (models based on externalities, Neoschumpeterian models and AK models) technological progress continues to be the main source of growth, but in the models the technological progress is perceived as a result of activity of an entity firm or individual (Romer, 1986, 1990). In the models based on externalities, learning from other firms on the level of an economic branch leads to new ideas that may result in technological progress. Knowledge, that is considered the same as technological progress, cannot be protected, and is therefore free and can be spilled over. Neoschumpeterian models are based on a belief that research and development can spur economic growth (Grossman and Helpman, 1990, 1991); Aghion and Howit, 1992). These models function under the assumption of imperfect competition. Under that assumption, firms will have interest to innovate because now they can protect the innovation via patenting and earn extra profits. In the AK models growth is a consequence of capital accumulation, while technology is not treated as a special type of good which makes these models less sophisticated from its predecessors. Apart from their concern for growth, transition economies have shifted their focus towards competitiveness and particularly so in the light of catching up with the EU as well as in the light of withstanding competitive pressures with the Union (Radoaevi, 2003a). The role of innovation for success of a nation and industries is discussed in Porter s work embodied in  the Diamond of National Advantage . Porter recognizes that competing revolves around the creation and assimilation of knowledge. For him, a nations competitiveness depends on the capacity of its industry to innovate and upgrade (Porter, 1990: p. 73). Although Porter asserts that national success of various countries can be combinations of different factors, he determinately dismisses widely held beliefs that government policies such as active exchange rate and antitrust policy will spur an economy. Instead he turns to the examples of industries that have succeeded on the global scene and asserts that companies achieve competitive advantage through acts of innovation (Porter, 1990: 74). On a firm level, innovation is not only perceived as introduction of new technology (resulting in new products) but can also be seen as innovation in processes and organization (new in-house processes). However, international dimension of innovation is stressed upon - innovations must be marketed internationally in order for firms to be considered having competitive advantage. Porter believes that successful innovations will arise when companies are under strong competitive pressure and despite the fact that their innovative activity may be faced with criticism and significant obstacles. Keeping competitive advantage is seen as a continuous process of improvement and upgrading. This is due to the fact that competitors may imitate any competitive advantage. 4. The rise of innovation policies in Central and Eastern Europe (CEE) Strategies for achieving and maintaining long term economic growth in CEE during the 1990ties disregarded the role of R&D systems or the role of innovation activities. Public innovation policies only emerged at the end of the 1990ties, while the institutional R&D systems have still not been restructured. Growth and innovating in an economy generally depend on R&D, on capability to absorb and diffuse technology and on the demand for its generalization and utilization-elements which form conceptual framework of national innovation capacity (NIC). CEE is lagging behind EU in all aspects of NIC and most pronouncedly in its capacity to generate demand for innovation which may be defined as level of development of financial system, degree of competition and macroeconomic stability or shares in FDI. Evidence on the state of NIS in former candidate countries pointed to strong disparities (CEC, 2003: 11). In comparison to the former EU-15, the new members (as of May 2004) had pronounced risk aversion, underinvestment in R&D and poorly developed science and research-business links. It appears that all of the new members have a common difficulty in the area under research their innovation policies have yet not become autonomous, full-fledged policies in the modern meaning. The institutional setting for implementing the innovation policy is not well coordinated human and financial resources are scarce, and the capacity of businesses to absorb knowledge and then apply it, is low. Absorptive capacity is the ability to absorb new knowledge and adapt imported technologies. R&D capability is important not only to generate new knowledge but also as a mechanism to absorb it. Diffusion is the key mechanism for reaping economic benefits from investment in R&D and for increasing absorptive capacities. Demand for R&D and innovation is the key mechanism that initiates wealth generation processes in R&D, absorption and diffusion activities. (Radoaevi: 2003a: p. 8) Consequentially, the relationship between domestic innovative activity and economic growth on a sample of eight economies in CEE is unclear (Radosevic, 2003). It appears that frontrunner economies (The Czech Republic, Slovakia, Hungary and Poland) are not countries with the highest number of registered resident patents. That would imply that innovations are not a driving force behind growth in CEE. Also, the causality from economic growth to innovation is not straightforward. Both economic rise and decline have in the past led to decline in R&D, suggesting that higher economic growth may not necessarily lead to higher innovative activity. Improved goods and services demand and supply conditions at the end of 1990ties could have contributed to the larger adoption of new technologies, but that has not happened. Apart from recognizing that domestic firms had difficulty in financing their activity, strong brand competition (though trade and FDI) might have also hindered catching-up in technology. A large base of research scientists and engineers coupled with relatively well educated working force were two strong starting points of NIS in CEE. The institutionalized R&D base has shrunk over the transition period due to, on the one hand, the decreasing share of public expenditures for R&D in GDP and on the other, because there has not been sufficient technological upgrading in firms. The financing of the institutionalized R&D by the industry was quite diverse across the region, ranging from strong connections to utterly weak and the intensity of that cooperation was determined by the countrys industrial structure. Deindustrialization in some countries in CEE was quite abrupt, with services taking stronger shares in the economic structure, and at the same time growing above the industrys average. Overall, partial loss of government funding together with weak demand from the industry have pushed modernization and restructuring of R&D systems into neglect. When examining cost structure of innovative activity in CEE, it seems that R&D is less important than buying new technology, while the trend is quite the opposite in the EU, where R&D has larger share in innovation expenditures than the acquiring of new technology. Business environment is the main source of innovation information, and not information within the firm (which is the case in more developed countries). A part of that business environment are foreign investment enterprises (FIE) - and the world estimates are that most of new innovations occur exactly in multinational companies (MNC). However, it seems that transfer of technology from MNC in CEE was confined to FIE (cf. Biegelbauer, Griebler, and Leuthold, 2001). Transfer of technology from FIE to local firms might have occurred only in the countries that have received the most significant shares of FDI into export-oriented internationalized activities such as automobile or electronic industry and where FIE have worked with local suppliers and contractors (Poland, the Czech Republic and Hungary). Radoaevi (2003a:9) points out that the reliance on external information and setting for firms raises the importance of national innovation system (NIS) - since innovation capabilities of firms are dependent on systemic features of external environment in which they operate. 5. Features and development of Croatian innovation policy The first elements of innovation policy in Croatia have only emerged in late 1990es (varc, 2004). The reason behind marginalization of innovation policy can mostly, on the one hand, be attributed to the importance given to macroeconomic policy, in particular the macroeconomic stabilization and reforms, monetary and fiscal policy objectives etc. On the other hand, the understanding of innovation policy in Croatia was obsolete and traditional in that it perceived that innovation policy should primarily be based on fundamental research. That traditional view was hindering development of applied sciences and its commercial use as well as postponed modernization and reorganization of the general research and science institutional setting and policies. Evidence to that is found in the fact that the Ministry of Science and Technology was the only responsible body for innovation policy, but perceived as technological and science policy from the beginning of the transition to the late 1990es. On the positive side, the traditionalist approach to science and technology in general, prevented the dissipation of the broad knowledge base. The government was mostly focused on modernization of higher education, but with no consequences on science and research system which under Government support remained non-autonomous. National Science and Research Program of 1996 served as a formal base for setting up the first network of institutions for technology transfer. The centers were founded in Zagreb, Rijeka and Split with the mission to serve as interface institutions-technology centers between universities and business community. The Program from 1996 also envisaged creation and implementation of measures for innovation based businesses. The research market was also impoverished with the disappearance of many industrial institutes, which had been the driving force behind technology and innovation development in the past, as they were left to the care of the market and their founding companies. As a result, only a few of those institutes remained alive and successful. The turning point in innovation policy development was in the early 2000, when programs promoting cooperation between industry and research and development system were introduced under auspices of Ministry of crafts, small and medium-sized enterprises. It was then that development of entrepreneurship and technological upgrading of firms was specifically targeted. Introduction of those programs were a step towards a modern approach to innovation policy that is found in the Triple Helix model, consisting of three basic actors intertwined in the their actions: the government, universities and business. The emergence of the program also marked a rise of a full-fledged innovation policy and the establishing of national innovation systems (NIS), which was seen as a system consisting of: policy measures and programs, technological institutional infrastructure and policy control mechanisms. So far, the Croatian national innovation system has been characterized as having a weak sector of industrial R&D and low level of technological capabilities of business. Considering the fact that the innovation policy has been operational in the last four years only, its estimated impact on research and development, as consequentially on economic growth could only have been modest and therefore, not yet visible.  For this purpose innovation is defined as introduction of any new, or substantially improved, product, process or service within a given period.  For example, Harris, Rogers and Siouclis (2001) note that, when it comes to potential covariates of the occurrence of innovation within a firm, empirical research has suggested it is important to take into account the past cash flow, profitability a market structure (Symeonidis, 1996), firm size (Arvanitis, 1997), export activity (Lefebvre, Lefebvre and Bourgault, 1998), as well as inter-firm networking.  In the European context, a key instrument in this regard has been the Community Innovation Survey, whose results will also be used in this research project. Please see below.  To view samples of the CIS questionnaire used in the UK and Estonia, both of which are similar to the one being used in Croatia (which is still not available in English) please visit the following websites:  HYPERLINK "http://www2.dti.gov.uk/iese/cis_quest.pdf" http://www2.dti.gov.uk/iese/cis_quest.pdf (UK) and  HYPERLINK "http://www.esis.ee/ist2004/text/images/128.pdf" http://www.esis.ee/ist2004/text/images/128.pdf or see Kurik et al., 2002 (Estonia).  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This is done following the Estonian example, and anecdotal evidence regarding the innovative micro-enterprises in Croatia. However, it is likely that in the case of micro-enterprises both the response rate and the quality of the data obtained will be lower than in the main sample. These will hence be treated separately (cf. Kurik et al., 2002).  The shortcomings stem from various factors ranging from the sampling procedure to definitional issues, composition of the questionnaire, and the implementation process. Moreover, since CIS is a voluntary postal survey, the results are necessarily subjective.  You may also consult Appendix B in Hujer and Radi (2003).  Most of innovation policy profiles have been developed in the context of EU accession (cf. EC 2001; EC, 2003). PAGE  PAGE 2  European Council has additionally: -noted that measures are to be designed with the goal of improving intellectual property rights, developing and strengthening private investment into research and increasing networking between business and science, -reaffirmed the importance of establishing the Community Patent (as an efficient and flexible instrument obtainable at affordable cost and ensuring a high level of quality).  These changes are defined by the Strategy of development of Science of the Republic of Croatia in the 21st Century and the Act on Scientific Activity and Higher Education.  The Diamond is made of four areas, each of which creates a setting for prospering of certain industries. These four areas are: 1. factor conditions, 2. demand conditions, 3. related and supporting industries, and 4. firm strategy, structure and rivalry.  Ministry of Science, Education and Sports since 2004.  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Paper presented at the conference Knowledge-Based Society A Challenge For New EU and Accession Countries, The Ivo Pilar Institute of Social Sciences, Zagreb, October 23-24. Romer, P. M. (1986). Increasing Returns and Long-Run Growth, Journal of Political Economy, 94/5, 1002-1037. Romer, P. M. (1990). 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