Science, Technology, and Economic Growth
Overview of Economic Thinking On Innovation and "New Growth Theory"
The linkages between innovation and economic growth have been subjects of inquiry since economics emerged as an organized discipline.5 In The Wealth of Nations, Adam Smith (1994) observed that invention, growth in capital per worker, and advances in industrial organization were all linked. Recent work in economics reflects a renewed appreciation of Smith's late 18th century insight. Another early economist, Thomas Malthus, predicted that population and progress ultimately would be limited by the scarcity of land. Although strides in agricultural productivity proved Malthus wrong, he did originate an important insight—that the economy and society can be influenced profoundly by different rates of innovation across sectors. Innovation was also a central concern of Karl Marx's, who predicted that competition and technological advance would lead to both rising unemployment and rising productivity.
Interest in innovation among economists, which had waned somewhat during most of the first half of the twentieth century, began to revive in the 1940s. Joseph Schumpeter's writing, particularly the 1943 book Capitalism, Socialism, and Democracy, marked the beginning of a stream of work exploring the links between innovation and industrial structure. Efforts by Solomon Fabricant, Moses Abramovitz, and John Kendrick to quantify the contributions of various factors to
This section draws on the paper by Richard R. Nelson, "Technical Advance and Economic Growth," in Part II of this report.
economic growth launched another important line of inquiry in the late 1940s. That work underlies a number of econometric studies of research and development (R&D) investments that have found that private returns on these investments exceed 20 percent and that social returns exceed 50 percent.6
Over the last three decades, empirical scholarship on innovation and growth has produced several important insights. First, technological innovation involves uncertainty in a fundamental way; winners and losers cannot be predicted, and efforts to plan or predict the outcomes of innovative activity are largely doomed to failure. Second, elements of the optimal environment for innovation—including industry structure, firm size, intellectual property regime, and government role—vary across sectors and over time within sectors. Third, rapid innovation is always linked tightly with underlying scientific or engineering research, although the nature of this linkage tends to vary.
Although empirical research has deepened our understanding of the innovation process, economists working in the field of neoclassical growth theory have begun only recently to incorporate those insights into their macroeconomic models. Their efforts to make technological advance an endogenous factor in the growth equation have been labeled "new growth theory." New growth theory and the economists associated with it are responsible for more closely relating the mainstream of economics with the actual experiences and concerns of entrepreneurs and others involved with high-technology industry.
One key idea associated with new growth theory is the concept of knowledge as a factor of production. Traditional production factors—capital, labor, and land—bring diminishing returns to scale, producing less output per unit as one factor is substituted for others. Some hold that knowledge on the other hand brings increasing returns to scale.7 Research and discussion associated with new growth theory have renewed interest in the science and technology aspects of other fields of economics, such as labor-market economics. This new appreciation for the role of human capital in economic progress could have important policy implications for science and engineering education.8
In short, economists long have agreed that science and technology are essential to economic growth in developed economies, but new growth theory is contributing to wider appreciation and deeper understanding of this connection.
Concepts of Innovation for Policy Making: The Linear Model and Pasteur's Quadrant
At the same time that economists have gained greater understanding of links between innovation and economic growth, the conceptual models used to guide policy making in the science and technology arena have remained rather static. Before World War II, the federal government played only a small role in science and technology. During the war, the United States enjoyed great success in harnessing its science and technology enterprise to develop new weapons and meet other military needs. At the end of the war, Vannevar Bush, who oversaw the wartime R&D effort, put forward his vision of a science and technology policy that would serve peacetime needs. In Science, the Endless Frontier , Bush (1990) proposed changes in government organization aimed at providing sustained federal support for science and technology. Although several of his specific policy recommendations were never enacted, the model implicit in the plan, picturing innovation as a linear process moving from basic research to applied research to development to production and operations achieved pervasive and lasting influence (see Figure 2-1).
With the end of the Cold War, the high-technology success of Japan and other economies that were not performing basic research on a large scale, and other factors, the linear model has come to be seen as less descriptive of real-world relationships, and therefore less useful. Donald E. Stokes has developed a matrix that categorizes R&D activities according to motivation (see Figure 2-2). Stokes was motivated by his observation that many worthwhile advances in fundamental knowledge are generated with some end in mind, contrary to the linear model.
In the Stokes matrix, research that is conducted to advance fundamental knowledge with no thought of practical use, even if insights eventually are utilized, fits in Bohr's Quadrant (BQ), named for the Danish physicist who modeled the basic structure of the atom. Today's research in high-energy physics, astronomy, and mathematics is representative of BQ research. It is conducted mainly in universities and research institutes and funded by the governments of developed countries. BQ appears to be a fertile area for expanded international cooperation. Although progress in this direction has been made in fields such as astronomy, the failure of the United States to develop international support for the Superconducting Supercollider some years ago shows that such efforts are not straightforward or easy.
Work conducted to achieve some practical benefit without consideration of advancing the frontiers of knowledge fits in Edison's Quadrant (EQ), named for the prolific American inventor. The work of most high-technology start-ups and indeed most industrial research today falls into this category. Intellectual property protection appears to be very important for EQ research.
Research conducted to advance knowledge while achieving a practical result is placed in Pasteur's Quadrant (PQ), named for the French pioneer in microbiol-
ogy and public health. It is the absence of this category from Bush's linear model that Stokes was seeking to rectify in developing his matrix. Government funds much of the work in PQ, but the invention of the transistor at Bell Laboratories by Shockley, Bardeen, and Brattian is a good historical example of industrial work. Although the largest industrial laboratories—such as IBM, Du Pont, and Xerox—have done important work in PQ and even BQ, they are shifting their emphasis to EQ.9 These trends and their implications are explored further in Chapter 3.
Figures 2-3, 2-4, 2-5, and 2-6 show broad trends in funding for research. Figure 2-3 shows the U.S. share of world gross domestic product (GDP) for 1950 and 1994, and the U.S. share of world R&D spending for 1960 and 1994. The U.S. share of each has declined over the years, and now, most of the world's R&D is performed outside the United States. Whether investments in fundamen-
tal research (PQ and BQ) are adequate to sustain a global science and technology base for innovation depends not only on the United States but on other countries.
Figure 2-4 shows the trends in government and private support of U.S. R&D. Private support is now predominant. Figure 2-5 shows trends in the federal science and technology (FS&T) budget from 1994 to the proposed 1999 budget. Although spending has increased in current dollars, there has been a slight decline when inflation is taken into account. Finally, Figure 2-6 shows the longer-term trend of decline in federal nondefense R&D funding as a percentage of GDP. Industry and federal funding trends are discussed in more detail in chapters 3 and 4. A key question raised by the broad trends is whether enough long-term investment is being made in PQ work, particularly as industry's focus becomes increasingly short term, and FS&T investments remain relatively flat.
Issues and Concerns
There is wide recognition that science and technology are fundamental wellsprings of economic growth, and the U.S. economy is turning in an excellent performance at the macro level—solid growth and low inflation. However, economists and other experts hold widely different views about key elements of the current economic environment and future trends. Technology is increasingly central to mainstream economic debates about several key issues.
One issue that has received a great deal of attention is the productivity paradox.10 Labor productivity is a measure of output per unit of labor and reflects improvements in capital, technology, and skills. Productivity growth ultimately translates into improvements in real incomes and living standards. Growth in U.S. labor productivity, which averaged almost 3 percent per year during the 1950s and 1960s, slowed to less than half that on the average over the 1974-1997 period. In particular, productivity growth in service industries has been notoriously slow despite large investments by service industry companies in information technology. The Conference Board (1997) reports that labor productivity has increased substantially in manufacturing sectors that use computers intensively but has grown less rapidly in service industries and manufacturing industries that do not use computers.
Some economists argue that mismeasurement of price changes and output makes productivity performance look worse than what it is, especially in the service sector. Others (Roach, 1998) believe that the increase in working hours of salaried employees over the last several decades, which is not accounted for in the statistics, could offset some or all of the sources of possible downward bias in productivity statistics.
A second economic issue of long-term concern is the growth in wage inequality in the U.S. economy over the last several decades. According to some economists, the introduction of technology has played a major role in widening income gaps as technological advance leads to higher returns to education and experience. Under this formulation, the demand for educated workers has gone up and driven up wages in this group because of increased utilization of technology; at the same time, less-skilled workers have seen their wages stagnate. Other economists argue that although technology plays a major role in the skill upgrading of the workforce over the long-term, skill-based technological change has not been the primary cause of increased wage inequality during the 1980s and 1990s.11
Despite the current economic environment of relatively low inflation and unemployment, the U.S. economy faces continuing challenges in delivering sustained growth in living standards for the majority of Americans. Reflecting different perspectives apparent in today's economic debates, experts put forward widely varied visions of the future. Some believe that we are entering a long period of science-and technology-led growth—a rise in living standards in the United States and around the world unprecedented in human history (Schwartz and Leyden, 1997). Others see the U.S. economy providing enormous opportunities to skilled entrepreneurs but middle-class American families increasingly being squeezed by inexorable forces of ''the new economy'' because stable, high-wage employment accompanied by benefits is harder to come by.12 The contribution of science and technology to economic growth must be sustained and enhanced if the actual future is to approximate the first vision more closely than the second.