The Socio-Economic Importance of Scientific Research To Canada

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The Socio-Economic Importance of Scientific Research to Canada Page 11© David A. Wolfe and Ammon SalterMETHODOLOGICAL APPROACHES:There are three major methodological approaches that have been used to study the benefits ofpublicly–funded scientific research: 1) econometric studies; 2) surveys, and 3) case studies.Econometric studies focus on large scale patterns. They have proven to be an effective tool forproviding an aggregate picture of statistical regularities among countries and regions. Allmeasures of the social rate of return to research and development (R&D) have relied oneconometric techniques, for example. These econometric approaches, however, can also bemisleading. They often work with simplistic and unrealistic assumptions about the nature ofinnovation, such as using R&D spending as a proxy for innovation. It is also very difficult totrace the benefits of the publicly–funded bit of information or technology through the processof innovation and commercialization. “Since such transfers are not priced or sold and arerarely adequately recorded by other means, the extent of their application remains unknown. . .. It is therefore very difficult to establish what contribution (government funded R&D) makesto the development of a technology (or product) merely by measuring the total funds spent atthe basic research stage and then looking at subsequent outcomes.” (Martin et al. 1996, p. 7)The use of surveys has opened up a productive line of new research in this area. They offer apicture of the extent to which government–funded research constitutes a source of newinnovative ideas for firms. Surveys have been used to examine how different industries drawupon the supply of publicly–funded scientific research and they have helped researchersunderstand the way in which different industries draw upon the research results of differentscientific fields. In this report, we make reference to surveys conducted in the US, theEuropean Union and Canada (Klevorick et al. 1995, Arundel et al. 1995, Baldwin and Da Pont1996). Surveys suffer several handicaps, as well. Survey respondents, usually industrial andresearch managers, have an innate bias towards the internal activities of their own firms.Respondents often have a more limited knowledge of their sectors, technologies, and even firmhistory. Moreover, survey questions often force respondents to rate different areas of a firm'sactivities against each other, though, in reality, they may be interrelated.Case studies and interviews afford the best tool to directly engage actors in the innovationprocess and to gain a better understanding of the historical roots of a particular technology orgovernment program (Freeman 1984). Case studies generally provide strong support for theresults reached by the econometric studies and survey techniques. For example, the TRACESstudy by the National Science Foundation showed the substantial influence ofgovernment–funded technologies in key sectors of the US economy (Illinois Institute ofTechnology Research 1968). The use of case studies is limited, however, by the factors ofcost, time, and vision. They are expensive to administer; often demand quite extensive11
The Socio-Economic Importance of Scientific Research to Canada Page 12© David A. Wolfe and Ammon Salterinvestments of time for analysis and data collection; and by focusing on a particulartechnology, sector, or group of firms, they depict a narrow picture of reality.THE RELATIONSHIP BETWEEN GOVERNMENT–FUNDED RESEARCH AND ECONOMIC GRO WTHEconometricians have made several attempts to calculate the portion of economic growth thatcan be accounted for by technological innovation, in general, and government–funded scientificresearch, in particular. We first review the attempts to account for the role of technology ingrowth and then focus more directly on the results for government–funded research. Theeconometric attempts to account for the role of technology adopt the technique of ‘growthaccounting’, which focuses on the contributions of various factors of production, such aslabour and capital, to economic development. In these models, growth takes place through thesubstitution of different factors of production for each other. Most growth models focus on thesubstitution of labour by capital, suggesting productivity growth occurs through the steadyreplacement of labour by fixed capital investments.Early growth models said almost nothing about technological change, however. Solow andother pioneers of growth accounting techniques treated technology largely as a residual, or thatportion of growth which could not be explained after labour and capital inputs were tabulated.The residual was labeled ‘technical change’ (Solow 1957, Abramovitz 1986). Technicalchange was deemed to be part of the general productivity increase and played no independentrole in explaining growth. As a consequence, these early models said little if anything, abouttechnology or the economic benefits of publicly–funded research (Martin et al. 1996).Newer models in growth theory have tried to account for technology more directly. PaulRomer's contribution to the field has spawned a new generation of research (1990). Thesemodels remain somewhat simplistic in their treatment of technology, however (Verspagen1993). They suggest that by introducing a variable for ‘technical progress’ into the models, itis possible to directly account for the proportion of growth created by technologicaldevelopment. The models vary in their conclusions, but all suggest a key role is played bytechnology in generating and sustaining economic development (Grossman and Helpman 1991,Aghion and Howitt, 1995, Romer 1994, Lucas 1994). However, they usually rely onsimplifying assumptions about the properties of information or technology, such as itsdurability, and use misleading statistics to measure innovation, such as taking R&D spendingas a cause of innovation. As yet, the models have not been able to develop a reliable indicatorof the benefits derived from publicly–funded basic research. They are more effective in12
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