Political Economy of Science




Science has never been at the forefront of political economy and usually only appears as an ”exogenous shock,” or is suppressed by an assumption within the theory of the firm of a given stock of scientific and/or technological knowledge from which firms make their choices and then employ them in producing a given volume of output. Nonetheless, some theorists and empiricists have explored (in very broad terms) the role of science and technology in economic growth, the relations between science, technology, the state, and capital, and science and development.




From Adam Smith, Charles Babbage (better known as the pioneer of computers) took the idea that invention was a consequence of the division of labor, but his Economy of Machinery and Manufactures went further to explain the implications of the division of labor for science and technology. He saw that the extension of the division of labor and improvements in production technologies would necessarily lead to the establishment of large factories working to economies of scale. Babbage also saw that this progress would come to depend on the deepening relations between science and industry and that, in turn, science itself would become subjected to the law of the division of labor. As science became a full time activity and the costs associated with the discovery of the ”principles of nature” increased, specialization would unavoidably follow.

Babbage’s analysis influenced Marx, who in turn considered science a fundamental factor in explaining the exceptional growth in resource productivity and humanity’s capacity to manipulate the natural environment for human purposes. Marx’s treatment of scientific progress was nonetheless consistent with his broader historical materialism. Just as the economic foundation shapes political, legal, and social institutions, so too did it shape scientific activity. Science did not develop in response to forces internal to science or the scientific community: it is not an autonomous activity, but rather a social one that responded to economic forces. As such, Marx did not see science as a driver of social change. Instead, he thought that specific scientific disciplines developed in response to specific social problems that arose in the sphere of production.

Marx’s central point was that science emerged at a particular point in human history. The marriage of science and industry did not occur with the historical emergence of capital ism, but centuries after when the system of manufacture demanded to be free of human frailty and relied instead on the predictability and impersonality of the machine. It is with the rise of the factory, its organized system of machines, and crucially the point at which machines started to make machines that the application of science became the determining principle everywhere.

Joseph Schumpeter identified with Marx the role played by capitalism in accounting for progress in science and technology. In a direct attack on the rigorously static framework of neoclassical economics, Schumpeter’s Capital ism, Socialism and Democracy drew upon Kondratiev’s hypothesis of long cycles to develop an evolutionary model of economic change within which science (and technology), along with the entrepreneur as innovative agent, plays the most significant role. Like Marx, Schumpeter thought that capitalism was inherently dynamic and the fundamental drive that kept the system in motion came from new consumer goods, new methods of production or transportation to new markets, and/or new forms of industrial organization. These changes incessantly revolutionized the economic structure from within, destroying old ones and creating new ones. This process, which Schumpeter termed ”creative destruction,” was for him the ”essential fact about capitalism.” Innovation leads to the creation of an economic space where swarms of imitators produce other innovations by copying or modifying the new technologies. Thus, in every span of historic time Schumpeter would argue that it is possible to locate the ignition of the process and to associate it with certain industries from which the disturbances then spread over the entire system.

Similar to Marx, Schumpeter also thought that the capitalist system would inevitably self destruct. Unlike Marx though, this destruction would not come about because of the proletarian revolution, but because first, the rationalizing influence of capitalist institutions (which created the growth of a rational science) would eventually turn back upon the mass of collective ideas and challenge the very institutions of power and property. And second, because scientific and technological progress would increasingly become the business of teams of specialists who would create what is required in a predictable way, so leading to the demise of ”the carrier of innovation:” the entrepreneur. The context for this rationalization of innovation was the growth of the large scale enterprise and, with it, the industrial research laboratory: the site of the systematic harnessing of science and technology to corporate objectives.

The rise of the giant corporation and its role in staving off the crisis of capitalism was the central point of analysis for Paul Baran and Paul Sweezy’s seminal work Monopoly Capital. For Baran and Sweezy, capitalism had entered a new stage of development – monopolization – characterized by the domination of massive corporations sharing rather than competing for production and markets. This domination enabled monopoly firms to extract enormous surplus and then absorb it through imperialism and the permanent arms economy. Increased government spending on ever more sophisticated, evermore destructive weapon systems created the demand required to prevent capital ism from falling into crisis.

While neo Marxists forwarded the under consumption argument, another utilitarian argument found strength in Vannevar Bush’s Science – The Endless Frontier and John Maynard Keynes’s General Theory of Employment, Interest and Money, both of which changed the political/ economic landscape and formalized science policies on the assumption that scientific progress would ultimately improve living standards. Bush’s report set the paradigm that influenced both policymakers and academics about the process of science, technology, and economic growth: the so called linear model as represented by Basic Research-Applied Research-Development-Enhanced Production-Economic Growth.

Keynes proposed that the economic function of government was to correct the follies of the market and stave off crisis through the promotion of full employment by means of large public works. Different countries adopted various means to achieve the goal of full employment, but Keynes’s theorem did stimulate massive state sponsored   scientific/technological projects such as nuclear power, supersonic transport, and space programs. ”High technology” and ”Big Science” were seen as politically beneficial in that they not only avoided direct competition with private capital, but they also promoted highly   skilled employment and contributed to the expansion of the industrial infrastructure.

In The New Industrial State John Kenneth Galbraith explored the consequences of these ideas. Following the familiar theme that the dependence of the modern economy on science, technology, and planning necessitated the ever increasing specialization and division of labor, Galbraith added analytical weight to President Dwight Eisenhower’s warning about the inordinate power of the military industrial complex and the scientific technological elite. As science and technology become more complex and lead times between design and production become longer (because of the amount of techno scientific knowledge brought to bear on every micro fraction of the task), the production process becomes inflexible. Increased complexity also leads to increases in capital investment (by orders of magnitude) and increased risk, which in turn leads to more need for control, for planning, and consequently for large organizations. Power, Galbraith argued, had shifted to those with technical knowledge. The scientific, technical, organizational, and planning needs of the ”technostructure” brought into being a large scientific estate, the political consequences of which was that in the modern economy techno logical compulsions and not political ideology drove industry to seek protection from the state. The technostructure extended its influence deep into the state, it identified itself with the goals of the state (economic growth, full employment, national defense), and designed and developed artifacts and systems to meet those goals. But, ultimately, the goals of the state reflected the needs of the technostructure.

Robert Solow’s economic analysis in the late 1950s, however, seemed to confirm and support government involvement in the promotion and production of science and technology when he concluded that capital investment did not deter mine economic growth, but rather productivity investment did (i.e., investment in research and development – R&D). Since Solow, economists have conducted statistical research to find the scientific/technological determinants of economic growth and while many confirmed the high returns from R&D investment, others laid down three very different propositions about the economics of science. First, the economic value of science is difficult to forecast. Second, the realization of profits or property rights from science is intrinsically difficult to determine because of the organizational norms of ”open science.” Third, because private returns to investment in science are highly uncertain, there exists a systematic market failure, which in the absence of government action would result in an underinvestment in science. These propositions have over time served as the basis for treating science as a ”public good” that requires public funding.

The traditional analysis of the efficient production of public goods was for governments to engage directly in the production of scientific knowledge, allow free use of it, and finance that production from general taxation. This was done either through the university or through government R&D laboratories that publicly disclosed their findings. The rise of a new economic doctrine during the 1980s, however (as epitomized by Milton and Rose Friedman’s Capitalism and Freedom), called on governments to reduce both taxation and state expenditure, which led not only to large scale budget cuts, but also to the systematic restructuring and commercialization of public sector R&D laboratories and universities. Accompanying the rise of the new enterprise culture was a range of organizational changes that intended to mimic practice in the commercial sector, in particular a large growth in university companies geared to the commercial exploitation of their staff’s expertise.

Notwithstanding, policymakers have long drawn inference from economic studies on the need to focus on R&D investments in the private sector. The argument underlying such a focus is that, through incentives, firms will continue to invest in additional R&D projects that increase the production of scientific knowledge and thus continue to stimulate economic growth and enhance standards of living. The traditional incentive for R&D investment has been the patent system, which grants monopoly rights over a specified period. Research on the economic role of patents has found a strong positive correlation between R&D expenditure and patents, and a positive correlation between patent activity and various measures of economic performance. However, other research has also suggested that the use of counts of patents as an indicator of innovative output can be misleading.

Finally, the role of science and technology in development has long been a matter of investigation for international political economy. Modernization theorists view science as essentially beneficial, in that both knowledge and technology transfer from the North aids developing nations. The idea rests on the linear model of the relationship between science and economic growth, the basic assumption being that science and technology are autonomous from society -that they are able to produce particular effects regardless of the social or cultural context in which they are placed. The Green Revolution is an illustrative case, whereby widespread food shortages, population growth, and predicted famine in India prompted major international foundations to invest in agricultural research. New types of maize, wheat, and rice emerged from this work, which promised higher yields and rapid maturity. But they did not come without other inputs and conditions such as fertilizers, pesticides, herbicides, fungicides, and even irrigation technologies. Moreover, seeds for these new varieties had to be purchased anew each year.

Dependency theorists, on the other hand, argue that relationships with the North, in particular with multinational corporations, are barriers to development, because outside forces controlled economic growth. As such, science is not viewed as a benign force, but rather as one of a group of institutional processes that contribute to underdevelopment. Because scientific research concentrated in the North, dependency theorists claim that the research is also conducted for the benefit of the North and that knowledge and technology transfer are just another  means  of profit  accumulation for Northern corporations.

References:

  1. Audretsch, D. B. et al. (2002) The Economics of Science. Journal of Technology Transfer 27: 155-203.
  2. Clark, N. (1985) The Political Economy of Science and Technology. Blackwell, Oxford.
  3. Feldman, M., Link, A., & Siegal, D. (2002) The Economics of Science and Technology. Kluwer Academic Publishers, Norwell, MA.
  4. Freeman, C. & Louca, F. (2001) As Time Goes By. Oxford University Press, Oxford.
  5. Rosenberg, N. (1994) Exploring the Black Box: Technology, Economics, and History. Cambridge University Press, Cambridge.

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