Cooperation and innovative performance of firms: Panel data evidence from the Czech Republic, Norway and the United Kingdom

Using panel micro data obtained from merging several waves of Community Innovation Survey in the Czech Republic, Norway and the United Kingdom, we estimate dynamic random effects tobit models, in which the innovation output given by sales of innovative products is the function of the cooperative behaviour of firms and their other observed characteristics, while accounting for unobserved heterogeneity. The results indicate that the capacity of firms to build on external domestic linkages is what matters most for the innovation output. And that foreign external linkages lead to superior innovation performance only in combination with the domestic ones. Also the results suggest that the positive effect of domestic cooperation is driven by linkages to education, research and scientific institutions, even though these types of partners tend to be used by firms noticeably less frequently for cooperation on innovation than their suppliers and customers.Innovation; cooperation; performance; micro data; Community Innovation Survey

High-tech exports from developing countries: A symptom of technology spurts or statistical illusion?

Specialization in high-tech products is frequently used to capture technology intensity of exports. The literature suggests that developing countries are increasingly becoming exporters of high-tech products, and some may even be among the most deeply specialized countries in the field of high-tech exports. The paper scrutinizes the relevance of the taxonomies that classify exports by technological intensity in this context. It is shown that specialization in high-tech exports typically does not appear in tandem with indigenous technological capabilities in developing countries. The analysis of intra-product imports suggests that the bulk of high-tech exports can actually be attributed to the effect of increasingly international fragmentation of production systems in electronics on trade statistics. It is confirmed in an econometric framework that while domestic technological capabilities have some influence on export performance in electronics, it is the propensity to import electronics components that accounts for by far the largest proportion of cross-country differences in specialization in electronics exports. The paper concludes with some implications for policy and future research.

A Multilevel Analysis of Innovation in Developing Countries

Innovation is a multilevel phenomenon. Not only characteristics of firms but also environment within which firms operate matter. Although this has been for long recognized in the literature, a quantitative test that explicitly concerns the hypothesis that framework conditions affect innovativeness of firms remains lacking. Using a large sample of firms from many developing countries, we estimate a multilevel model of innovation that integrates explanatory factors at different levels of the analysis. Apart from various firm’s characteristics, national economic, technological and institutional conditions directly predict the likelihood of firms to innovate.Innovation, Technological Capability, Multilevel Modeling, Institutions, Developing Countries

Knowledge, Capabilities and the Poverty Trap: The Complex Interplay Between Technological, Social and Geographical Factors

This paper explores the possibility that technological capabilities, to lead to development, need to be accompanied by a broader set of “social capabilities”, reflecting not only the quality of governance but also the spread of values, beliefs and institutions that encourage members of society to actively contribute to the development process. To investigate this issue, a set of empirical indicators, reflecting the capabilities that have been emphazised in the literature as being important for development, was identified. We also take into account the possibility that these capabilities (and their impact) may be conditioned by historically given factors (related to, for example, geography, demography and history). The paper uses factor analysis to analyse the question of how these indicators interrelate and explores their relationship with economic development. We find that technological and social capabilities are indeed strongly related and, moreover, strongly correlated with economic development. The same does not apply for the second factor suggested by the analysis, which mainly reflects the character of countries’ political systems. Thus it is more important economically what countries do than how they decide on it. A strong negative relationship with development was found for the third factor, reflecting the combined effect of high fertility rates, low education and high frequency of serious disease. Arguably, this contributes to a “vicious circle” that makes it difficult for some very poor countries, especially in the tropics, to escape from poverty.

Understanding multilevel interactions in economic development

National framework conditions mediate the effect of technological capabilities of firms on their productivity. Although this has been recognized in the literature for a long time, a quantitative test that explicitly considers this hypothesis has been lacking. Using a World Bank datasets of about 19,000 firms in 42 countries, most of which are developing, we estimate a multilevel production function with effects of firm’s technological capabilities nested in the national framework conditions. Our results confirm that various facets of firm’s technological capabilities and national economic, technological and institutional conditions influence total factor productivity of firms. Furthermore, we find that the effects of the national conditions and firm’s technological capabilities are closely intertwined with each other. Adherence to international standards, formal training of workers and access to technology through foreign ownership make more difference for productivity of firms in less developed countries, while R&D capabilities on the contrary boost significantly more performance of firms in countries at the technological frontier. Different features of the national framework are shown to be responsible for this.Productivity, innovation, technological capability, institutions, multilevel modeling

Technology and development: Unpacking the relationship(s)

Innovation is, as Joseph Schumpeter once pointed out, above all a combinatory phenomenon. Success in accessing knowledge and exploiting it in a way that is beneficial for development depends on the ability to combine many different skills and resources, of which many will be external to the firm. Arguably, political choices, past as well as present, the quality of governance and the business environment, availability of skills, finance and broader social and cultural characteristics may all have a say for how well this combinatory dynamics works. Based on a review of the literature on how technological, economic and social factors interact in the development process this paper sets out to explore these interrelationships empirically. The results, based on data for 75 countries on different levels of development, suggest that there is a strong correlation between technological capability, (innovation-friendly) governance and social capital, confirming, it is suggested, the important role played by politics and deeper social and cultural factors for technological catch-up (or lack of such). This contrasts with the role played by for instance openness to trade, FDI, etc., which - according to the results presented here - hardly correlates with anything.

The Voyage of the Beagle in Innovation Systems Land.Explorations on Sectors, Innovation, Heterogeneity and Selection

The aim of the paper is to assess heterogeneity of the innovation process. Using exploratory factor analysis on micro data from the third Community Innovation Survey in 13 countries, we identify four factors that that can be interpreted as research, user, external and production ingredients of innovation. All too often it is assumed that the differences between the rates at which these factors are found in firms' innovation strategies can be accounted for by differences across sectors and/or countries. To put this proposition under scrutiny, we partition variability of the innovation process into components identified by the different levels. The analysis shows that sectors and countries matter to a certain extent, but far most of the variance is given by heterogeneity among firms within either sectors or countries. On the other hand, a grouping of firms produced by cluster analysis ac-counts for a much higher share of the variance, which implies that the most relevant contextual fac-tors cut across the established boundaries between sectors and countries. We discuss the implica-tions of these findings for the literature on national and sectoral systems of innovation, and for the way in which evolutionary economics has analyzed the role of selection.Technological Change, Innovation, Heterogenity, Variance Components Analysis, Factor Analysis, Systems of Innovation

The Voyage of the Beagle in Innovation Systems Land. Explorations on Sectors, Innovation, Heterogeneity and Selection

The aim of the paper is to assess heterogeneity of the innovation process. Using exploratory factor analysis on micro data from the third Community Innovation Survey in 13 countries, we identify four factors that that can be interpreted as research, user, external and production ingredients of innovation. All too often it is assumed that the differences between the rates at which these factors are found in firms' innovation strategies can be accounted for by differences across sectors and/or countries. To put this proposition under scrutiny, we partition variability of the innovation process into components identified by the different levels. The analysis shows that sectors and countries matter to a certain extent, but far most of the variance is given by heterogeneity among firms within either sectors or countries. On the other hand, a grouping of firms produced by cluster analysis accounts for a much higher share of the variance, which implies that the most relevant contextual factors cut across the established boundaries between sectors and countries. We discuss the implications of these findings for the literature on national and sectoral systems of innovation, and for the way in which evolutionary economics has analyzed the role of selection.Innovation, heterogeneity, sectoral systems of innovation, factor analysis, variance components analysis.

Catching up: What are the Critical Factors for success?

This paper addresses one of the oldest and most controversial issues in economics: Why do some countries succeed in catching up, while others fall behind? In recent years the quality and availability of data on different aspects of development have improved a lot. Attempting to exploit this opportunity for more in-depth research the paper starts with an overview and assessment of the different approaches in the literature and the empirical indicators and methods that these have given rise to. This leads to the formulation of a synthetic empirical model and, with the help of factor analysis on large variable set, to the identification of set of “capabilities” which might be assumed to be of critical importance for catch up. The explanatory power of these capabilities for economic growth is tested on a sample of 135 countries in the 1990s.

ERAWATCH Country Reports 2012: Czech Republic

This analytical country report is one of a series of annual ERAWATCH reports produced for EU Member States and Countries Associated to the Seventh Framework Programme for Research of the European Union (FP7). The main objective of the ERAWATCH Annual Country Reports is to characterise and assess the performance of national research systems and related policies in a structured manner that is comparable across countries. The Country Report 2012 builds on and updates the 2011 edition. The report identifies the structural challenges of the national research and innovation system and assesses the match between the national priorities and the structural challenges, highlighting the latest developments, their dynamics and impact in the overall national context. They further analyse and assess the ability of the policy mix in place to consistently and efficiently tackle these challenges. These reports were originally produced in December 2012, focusing on policy developments over the previous twelve months. The reports were produced by independent experts under direct contract with IPTS. The analytical framework and the structure of the reports have been developed by the Institute for Prospective Technological Studies of the Joint Research Centre (JRC-IPTS) and Directorate General for Research and Innovation with contributions from external experts.JRC.J.2-Knowledge for Growt