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3 Measuring science, technology, and innovation
The growing need for R&D and innovation
From macro-phenomena to innovation processes
Towards a worldwide standard for R&D surveys
Quantitative descriptions and qualitative assessments
The overall scope of R&D statistics among developing countries
Has R&D spending by developing countries increased?
In which regions are the world's R&D resources concentrated?
Science, technology, and new economic patterns
Innovation indicators in the making
The "second-generation" statistical manuals
The Earth is round, but it does not appear perfectly spherical if we examine the worldwide distribution of resources devoted to research and experimental development (R&D) - defined to include fundamental and applied research. Far from being evenly distributed throughout the world, these resources are concentrated in a small number of countries. In the early part of the 1970s less than 3 per cent of the world's R&D expenditures were made by the developing countries, and just a little more than 11 per cent of its researchers its R&D scientists and engineers - were employed there .
According to more recent, though less complete, data to be presented later in this chapter, changes influencing this North-South relationship have occurred, but the overall pattern has remained much the same through the 1970s and 1980s until today. The highly industrialized countries have kept their dominant position while strengthening their R&D capabilities. But notable shifts of positions have taken place within the developing world as countries like Brazil, India, and the Republic of Korea have increased spending on R&D, while, in the same period, a number of other developing countries have been forced to reduce their science and technology base.
On the basis of this crude statistical picture, it is no exaggeration to claim that not all countries are able to undertake the scientific and technological activities that they desire. As regards resources, the majority of the nation-states in the world are a research desert, and the remaining countries can still be looked upon as a small number of R&D oases, some of which are very large .
To government policy makers and corporate managers in the highly industrialized countries, the global distribution of R&D resources may appear quite attractive. In their countries resources seem to be abundant. The social production and diffusion of knowledge have turned into specialized professional activities, financed and performed by many different firms, institutions, and other organizations throughout society.
In principle, science and technology could play similar roles in the economies of all other countries as well. Lack of resources, low levels of skills, few training opportunities, inappropriate curricula in higher education, weak technology-supporting institutions, etc., may prevent some of them from exploiting all of the nation's innovative capabilities. "Science and technology can only take root in a given society if their structures and goals are well matched to prevailing modes of thinking and of doing, in particular to local traditional technologies" [20, p. 52].
At the end of the twentieth century only a small number of developing countries have been able to create and maintain comparatively strong national R&D capabilities. Most developing countries do not possess the scientific instruments and other highly specialized equipment needed for advanced research in many fields of study. Instead of scientific research, they have to rely heavily upon other varieties of organized knowledge to better utilize and further develop their productive potential.
Typically, in Africa, Asia, and Latin America, the industrial firm wanting to innovate has no choice but to copy or simply accept incremental technical change for the renewal of its products and manufacturing capabilities. Indigenous technological capabilities at the level of the firm do exist - and local engineering and advanced consulting services are actually expanding in most developing countries but technologically significant inventions are generally generated outside the company or industry. Science-based technical change in these countries is rarely indigenous.
At a lower technical level than in the industrial part of the world, economically significant inventions in the developing countries are more frequent. As these countries innovate, and they certainly change technologically, the sources of innovation seldom include endogenous R&D. There are examples of industrial firms and even branches of industry that have proved their capacities to renew and innovate without access to a specialized and multifaceted scientific and technological base.
Strong R&D capabilities are in fact not the same as strong innovative capabilities at the level of the firm. There may be a correlation, but - apart from scientific results and laboratory practices- it should be emphasized that there are many sources of invention. Nor is the effective diffusion and application of new inventions caused by strong capabilities in R&D. However, since new innovations in industry are increasingly science-based or high tech, the relatively scarce and scattered R&D activities among the developing countries have to be complemented by a steady stream of information and ideas, new goods and services, production methods and "best practices," patents and licences created elsewhere.
The growing need for R&D and innovation indicators
Since the early 1960s, basic data on resources devoted to research and experimental development have been collected by an increasing number of countries. R&D is by far the best measured category of innovation and may even be integrated as such into the UN System of National Accounts (SNA).
Some 140 countries have succeeded in producing statistical maps of their national R&D landscape (Unesco 1991  includes only 128). By no means are all of the maps up to date. A few are just listings of government budgetary allocations for R&D with estimates of other R&D expenditures. We must remember, however, that the majority of today's developing countries have reached independence only since the Second World War; well over 100 nation-states have emerged on the political scene since the late 1940s. When they achieved political independence, most of them had only rudimentary R&D capabilities.
By aggregating national statistics, it becomes possible to make regional and even global aggregates of resources devoted to R&D. But these summaries cannot be better than the often fragmentary data available nationally. In order to produce statistically sound descriptions of the global R&D effort, more detailed and standardized data are needed.
Regardless of their position or general outlook, planners and decision makers in both the industrial and developing countries have a common need of R&D data that are more suitable for fully fledged descriptions and appropriate analyses of the international or global changes in the economy. Less and less are R&D statistics regarded as an independent category of data: since they measure a crucial part of society's innovative activities, they are seen as only one component of several significant sets of data on innovation and economic growth.
At present, and at least for some sectors of society, R&D statistics are being re-examined in a wider context of innovation and adjusted to fit better into national and international surveys of innovation under different socioeconomic circumstances. Especially among the industrialized countries, further details are being asked for, e.g. on the flow of R&D funds between countries - in general and between companies located in different countries but within the same economic zone or region. Given the predominant role in overall R&D activities of large industrial firms operating in several countries, figures describing national R&D resources alone lose some of their value. They are gradually being supplemented by internationally comparable data at the company or industry sector level.
Such general pictures cannot be painted without an extensive use of reliable indicators. It is not enough just to order categories of basic figures and draw simple conclusions from unrefined tables. True, it may be of value to highlight important, though elementary, comparisons between countries and regions, but to become analytically useful, the statistics will have to be shaped into indicators that are defined within - or at least closely related to a specific conceptual framework or analytical model. R&D and innovation statistics may serve several such models; and the models could change over time and still exploit the same series of data. The models may also link data on R&D and innovation with existing statistics on other economic and social activities, thereby creating new, more sophisticated indicators.
Step by step, over the past 10 years, there has been a move from input indicators towards output and impact indicators. Examples from the latter category are combined data on high-technology investments and trade; patents taken out at home and abroad; cooperative agreements on the transfer of know-how; strategic "technological alliances" between firms; and imports or exports of components and services with a significant technology content. For a developing country such output indicators could serve important purposes in the assessment of innovative capabilities and of technology gaps between countries or between branches of industry. Although significant, the move towards output and impact indicators has been slow and the statistics produced are still fragmentary, even among the industrially most advanced nations.
From macro-phenomena to innovation processes
Among policy makers as well as economists and other social scientists there is a widespread consensus that current R&D statistics should be further extended and developed by way of broader "innovation surveys." This widening of the statistical realm should improve the understanding of the role that R&D plays in innovation and help explain differences in performance between firms, sectors of industry, and (even) national economies.
However, differences in the level of development between countries may easily cause measurement problems. The same set of R&D and. innovation indicators could give rise to different interpretations in different economic contexts (see Madeuf ). Probably? as among the industrialized countries statistical analyses within a specific developing country grouping - with common economic characteristics may prove to be more analytically fruitful. For instance, a developing country government that promotes export-oriented industrial strategies may understand technology-transfer data very differently from a government that supports inward import-substitution strategies. Likewise, countries operating similar economic policies are easier to compare.
Until recently, internationally comparable R&D statistics have been collected and processed only for macro-phenomena in the economy. Except for an increasing number of case-studies in industry, relatively little is known about innovation processes at the level of the firm or in subsectors of industry. Now, however, policy interests have stimulated R&D statistical studies of the linkages between the macro- and micro-levels with a view to assessing the flow of resources and evaluating the relative economic impact of investments in R&D and related activities. Ongoing international statistical efforts may help to overcome the current lack of transparency and compensate for the imperfect knowledge of the processes of innovation.
In both government and industry, policy makers and analysts have expressed a growing need for more sophisticated and usable R&D and innovation indicators. Such indicators should reduce uncertainties and help advance plans and decisions regarding national and sectoral science and technology efforts. By way of international comparisons, the specific conditions for innovation in areas such as industry and trade, education and training, public health and social security, could be further elaborated. But we are still far from viable international comparisons even among the highly industrialized countries, e.g. between Germany, Japan, and the USA.
For the developing countries, the relevance of available R&D output indicators varies. Output data commonly used in industrialized countries such as rates of publication and the number of citations in internationally available journals, as well as statistics on patents and licences - are not easy to interpret in a third world setting. This is due to the lack of uniform and nonbiased data in relation to publication and other communication practices. More importantly, the structural features of each developing economy demand a different framework for the analysis. The diversity among developing countries in organizing a national R&D system, in linking endogenous research to international (or Western) science, in improving the techno-scientific infrastructure, in furthering manpower development, etc., make output indicators complicated and even controversial, particularly for comparisons between industrial and developing countries [20, p. 53]. "There are no adequate, comprehensive indicators of development, which can reflect the complex cultural, social, economic, and political factors at play when the concept of 'development' is considered with all of its multidimensional implications. At best, there are some indicators of the penetration of western patterns into different societies" [20, p. 52].
As regards the particular needs of developing countries, R&D and innovation indicators should not only permit systematic international comparisons, but also provide information in order to assess the efficiency of science and technology capabilities, measure the flow of technology through various channels, and help analyse the contribution of both foreign and domestic sourcing of science and technology. Ideally, these and similar indicators should further the analysis of R&D and innovation policies aiming at balancing foreign and domestic sourcing of technology and enhancing the local science and technology base .
There is a general need to develop more sophisticated methods of surveying the diffusion of technology and other kinds of innovative activities, particularly methods to be used for advanced international comparisons.
Towards a worldwide standard for R&D surveys
Since the 1930s, and particularly during and after the Second World War, a dominant attitude among policy makers in the industrialized countries has been that of a necessary mobilization of science and technology for economic purposes as well as for national security and related strategic objectives. In the larger industrialized countries, the building of strong sectoral R&D capabilities responded to the needs of the military and, later, also to the reconstruction and economic recovery during the first 15-20 years of the post-war period . Accordingly, the emphasis by statisticians was very much on the "supply side" of the national R&D system.
The first national surveys were based on approximated expenditure data for science and technology and on crude numbers of scientists and technologists in government and industry. "Looking through the various national statistical yearbooks, one is impressed by how many countries have felt the need to count their donkeys and how few their scientists," Stevan Dedijer wrote in a summary of the 1950s [11-13]. He and other pioneers of R&D statistics had to draw upon all kinds of primary data to quantify the resources devoted to R&D while attempting to make international comparisons. There were, in those early years, no serious attempts by intergovernmental agencies to provide quantifications of the global R&D effort. Instead, examples were set by individual scholars like John D. Bernal, who calculated national "budgets of science (and technology)" for several countries as early as the 1930s . (Dedijer mentions Soviet studies of the mid-1920s with similar ambitions.)
In its study of science policy for the 1960s, the OECD (Organisation for Economic Co-operation and Development) found existing R&D statistics "grossly inadequate. Most countries have more reliable data on their numbers of poultry and their egg production than on their numbers of research scientists and engineers and their output of discoveries and inventions" [24, p. 21]. During the second half of the 1960s and in the early 1970s, the situation improved significantly. This was a period when statistical resources were activated all over the world in the quantitative study of R&D. All tables and charts that quantified the resources of the national R&D systems were dominated by rather simple data on given inputs into science and technology, only rarely supplemented by easily available output data of the system such as scientific papers, patents, licences for technology, etc. But advances were on their way.
Among the industrial countries the interest by the main users of R&D statistics had shifted to the "demand side" as opposed to the "supply side" of the earlier period. The market pull of technology, know-how, and other specialized knowledge was coming into focus after the long period of reconstruction of the national economies. Industrial innovation had become a competitive advantage. Accordingly, several of the national efforts by R&D statisticians were initiated by the drive towards better international comparisons (see, for example, Freeman and Young ). The relative economic performance of the different R&D systems had come into focus along with the growing interest in the role of science and technology for industrial innovation.
Still, while R&D statistics improved in certain highly industrialized countries, other countries approached the tricky problems of sources and methods with "quick-and-dirty" solutions in order to be able to present national R&D statistics with at least some of the required international comparability.
Among the first regionally based organizations to advance R&D statistical methodology and to promote comparative studies of R&D efforts was the OECD. Already in 1963, at Frascati in Italy, the OECD had convened a group of experts that soon developed a standard practice for surveys of research and experimental development, officially termed the Frascati Manual, which has been revised and updated ever since [25, 30].
In line with the Frascati Manual, statisticians of other regional organizations, such as the European Community and the CMEA (Council for Mutual Economic Assistance, formally dissolved in early 1991), have developed separate survey techniques and other analytical tools for national surveys and for cross-country comparisons. With early assistance by OECD experts, the Organization of American States (OAS) specified a standard for Latin America. Over the years, several such statistical endeavours have converged towards an international norm or standard for R&D data. But there is still no detailed, worldwide guide for R&D statisticians. Only a limited number of countries, most of them highly industrialized, have fully harmonized their statistics in this field.
For many years, Unesco (the United Nations Educational, Scientific and Cultural Organization) was a prime mover in the attempts to create a worldwide standard for R&D surveys (a comprehensive version is given in ; see also  and its later versions). Many developing countries have followed the suggestions by the organization not to design their own statistical methodology, but to accept that of Unesco. However, the problem of harmonizing already existing country standards and relating them to internationally accepted statistical methodologies has not been easily resolved. Moreover, the focus by Unesco on developing countries has fostered survey techniques that are not always suited to the specialized policy needs of the highly industrialized countries. These latter countries were discouraged from using the Unesco R&D statistical methodology simply because it produced statistics that were too crude.
Subsequently, during the 1970s and 1980s, the industrialized countries settled with their own standards. In fact there were two: a western one for the OECD member governments (cf. ) and an eastern one for the CMEA members . Nevertheless, without adopting a common standard, the two country groupings came close to matching their R&D statistical methodologies, although some basic statistical categories remained unrelated. Following the changes toward a market economy in eastern Europe and in the former Soviet Union and its successors, it is likely that the Frascati Manual will be adopted by all industrialized countries.
Despite continuous efforts, neither Unesco nor any other international agency has yet been able to implement, through the many national statistical units, a world standard on how to collect R&D data and further specify the kinds of innovative activities that should be measured as well. What has been agreed through Unesco is a general recommendation concerning the statistical categories by which data should be collected, processed, and presented. Agreeing on a general methodology is one thing; implementing it has proved to be quite another.
With or without a worldwide standard for R&D surveys, the majority of countries have regularly provided the Unesco statistical office with basic data on their R&D manpower and related expenditures. Most of this material has been published in the Unesco Statistical Yearbook. Other national data have been further processed for regional summaries and even global estimates of resources devoted to R&D (for the most recent global survey, see ; regional surveys have been conducted for, e.g., Latin America, Africa, and the Arab countries).
Following several revisions of the Frascati Manual over the last 10 years, the OECD secretariat has become a clearing-house for both national and international advances in R&D statistical methodology. Most importantly, the OECD has provided a permanent forum for expert consultations and responded actively to new statistical requirements. Its large unit of professionals engaged in the development of indicators have spent lengthy periods of exploratory work, involving the collaboration of national agencies and international organizations such as Unesco. Consultations and week-long seminars for R&D statistical staff of non-member countries, i.e. from eastern Europe, the former Soviet Union, and selected developing countries, are a relatively new feature among its activities.
For the OECD member countries, the benchmark source of R&D data is the biennial survey, conducted by national statistical agencies using the Frascati Manual's detailed questionnaires. These nationally collected data are fed into a "main science and technology indicators" database containing the variables most widely used over the past 20 years correlated with other data such as that of industry and trade. A data exchange system is operated in collaboration with national agencies and with the "Eurostat" of the European Community. Close relations are maintained with other international agencies as well. To meet specific policy needs, this exchange system should permit the design of special data segments.
Quantitative descriptions and qualitative assessments
Among the industrialized countries, it was not until the second half of the 1970s that the methodological work resulted in a deliberate push towards comparable "science and technology (S&T) indicators." Policy deliberations on industrial competitiveness in a new economic context and conflicts around the place of organized knowledge in society created a strong demand for this kind of internationally comparable data.
More importantly, the specific needs of actual and potential national users were better articulated. For the first time, R&D statisticians were placed in the centre of economic policy-making and forced to produce much more timely and appropriate indicators. In the OECD member countries, comprehensive sets of S&T indicators were generally available already by the end of the 1970s, following national attempts by, for instance, the United States National Science Foundation (NSF). The OECD indicators included inputs to the R&D system and outputs such as detailed patent statistics and the technological balance of payments, as well as impact indicators, which quantify trade in R&D-intensive products and give productivity indices, etc. (Representative indicators can be found in refs. 26, 27 and the STI Indicators Newsletter.) Many more innovative activities than before were brought into the realm of quantitative analysis.
This new type of more comprehensive indicators, produced by national agencies as well as by regional organizations such as the OECD, became more widely used during the 1980s. Nevertheless, the new indicators only pointed out the salient similarities and differences among countries and economic sectors. They made possible a more thorough analysis of patterns and trends in both overall and specific innovative activities. They did not, however, bring about what was later to be called innovation indicators.
According to Christopher Freeman, a participating observer, the first stage in the development of today's variety of R&D indicators emphasized the efforts to expand the national R&D system "without too many questions about output and efficiency" [17, p. . In the second stage "accountants, economists and managers began to ask more awkward questions about performance and responsiveness to the needs of the market," but mainly in terms of controlling expenditure and preventing waste. Now, in the third stage, the focus is put on more direct ways of stimulating economic growth and competition in world markets while combining technical change, industrial modernization, and trade strategies.
Differences between the three stages should not be exaggerated. Elements of both "supply-side" and "demand-side" economics have been present in the policy communities over the last 50 years. "Nevertheless," Freeman claims, "anyone who goes through the various reports of national science and technology advisory bodies - or of parliamentary debates on science and technology or of economic policy documents - cannot fail to be struck by this change in emphasis and focus over the post-war period" [17, p. 115]. The three stages in the production and use of R&D indicators can also be described as a move from quantitative descriptions by way of broad categories of data towards more qualitative assessments of R&D capabilities for industrial innovation and competitiveness.
Lately, and this is a new feature, government authorities in several OECD countries have reduced or even terminated a number of these surveys, while other statistical services have gradually been farmed out [34, p. 25]. The reasons are several. The rising costs of comprehensive statistical analyses have been increasingly difficult to reconcile with the need for budgetary restrictions. And the policy needs for general - or very particular surveys of science, technology, and industrial innovation to be carried out by public agencies are not always clear to top government decision makers.
Although the field of R&D statistics is young, and innovation studies even more recent, routine procedures by government statistical agencies make it difficult to initiate new surveys, implement them, and then rapidly analyse the findings in order to answer urgent questions posed by planners and policy makers. As a result, quite a few surveys and other studies are now being carried out under flexible, short-term contracts by academic institutions or, more often, by companies that operate commercially.
As firms start producing politically and otherwise important analyses based on R&D and innovation indicators, the information may become a private rather than a public good. Availability is restricted or delayed; some statistical studies are made secret to all but those who finance them. This new situation causes problems for the quality and international comparability of R&D and innovation indicators. If the local customers find it more convenient to design surveys for their own particular purposes, the chances are limited that collected data will be processed in a way that would serve other potential users or the international statistical community.
As R&D and innovation indicators develop locally, while the internationally standardized survey techniques change only slowly, some countries have already expanded their range of indicators and adopted concepts and definitions without waiting for improvements at the international level.
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