Innovation matters for growth. Improving our knowledge of firms’ innovative behaviour and its determinants is crucial for designing effective innovation policies. Data collected through innovation surveys have been increasingly used to explore a number of questions regarding the determinants, the effects and some of the characteristics of innovation. Nonetheless, with few exceptions, almost all such studies have been conducted at the level of individual countries. While valuable, they do not allow for comparing results across countries. Reasons for not exploiting firm-level data at the international level are mainly legal: access to innovation survey data, as for microdata in general, is restricted by laws that protect confidentiality and secrecy in all countries. As a consequence, microdata from different countries cannot be pooled and because different models and methodologies are used, the results are usually not comparable across countries.
As the importance of innovation as a driver of economic and social change grows, its nature, role and determinants are receiving increasing attention. Innovation is a broad concept which encompasses a wide range of activities and processes: markets, entrepreneurship, networks and competition, but also skills and organisations, creativity and knowledge transfers. Statistics covering various science and technology activities have been systematically collected by statisticians and researchers for more than 40 years, but only recently has the broader concept of innovation been formalised in a way that makes it possible to gather information about how firms innovate through large-scale statistical surveys.
Knowledge, research and innovation are of crucial importance for the competitiveness of the modern economy, as well as for high standards of living and welfare. In order to describe and better understand the role of knowledge and its effects, it is vital to have sound statistical information on which to base policy design and evaluation. Indicators to measure research and development (R&D) efforts were first developed and harmonised in the 1960s but it was not until the 1970s and 1980s that researchers started focusing on the development of more complex analytical models and measurement tools to study innovation. In order to understand how innovation occurs and to devise appropriate innovation policies more needed to be known about the process of innovation at the level of individual firms.
Exploring Non-technological and Mixed Modes of Innovation Across Countries
There is considerable evidence that innovation plays an important role in shaping the growth and competitiveness of firms, industries and nations (as well as regions). It is linked to increased welfare, the creation of new types of jobs and the destruction of old ones. At the firm level, innovation is linked to performance and competitiveness.
Innovation and Productivity
Innovation is considered one of the main drivers of productivity growth and economists have investigated both its determinants and its contribution to firm performance, measured as productivity; growth and/or market value. There are several reasons for analysing the link between innovation and productivity at the firm level. First, it is firms that innovate, not countries or industries. Second, aggregate analysis hides a lot of heterogeneity. Firms’ performance and characteristics differ both across countries and within industries; countries’ innovation systems are characterised by mixed patterns of innovation strategies which have an impact on firms’ behaviour; and firms may adopt multiple paths to innovation, including non-technological ones. The advantage of micro-level analysis is that it attempts to model the channels through which specific firms’ knowledge assets or specific knowledge channels can have an impact on these firms’ productivity and therefore shed light on the role that innovation inputs, outputs and policies play in economic performance.
Innovation and Productivity
The OECD core model (see Chapter 3) achieved quite remarkable results even if constrained by international benchmarking requirements (use of a "simpler" model in order to include a number of OECD countries). However, important variables were omitted or simplified to enable international comparisons. Obvious examples are: the use of a sub-optimal productivity equation (value added or total factor productivity variables would have been better candidates for productivity measures than total turnover); omission of important production factors such as measures of human and physical capital; and the use of binary variables when quantitative ones were available for some countries (e.g. exports).
Innovation and Intellectual Property Rights
"Patent regimes play an increasingly complex role in encouraging innovation, diffusing scientific and technical knowledge, and enhancing market entry and firm creation. As such, they should be subject to closer scrutiny by science, technology and innovation policy makers." (Meeting of OECD Ministers of Science and Technology, January 2004).
ANNEX A - Methodology
This section includes methodological notes and metadata concerning the innovation surveys and the definitions used in this project. In particular, it was decided to use CIS 4 as the "benchmark" in terms of sectoral coverage and firm size classes in order to ensure a reasonable degree of cross-country comparability. Known deviations are noted in the country notes section.
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