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Measuring and Sustaining the New Economy: Report of a Workshop Panel I Defining and Measuring the New Economy INTRODUCTION Robert Shapiro U.S. Department of Commerce Dr. Shapiro began by saying that defining and measuring the New Economy is one of the most important questions facing economic policy today. He said that the topic holds special interest for him and for his office, the Economics and Statistics Administration of the Department of Commerce, which oversees two of the nation’s three major statistical agencies, notably the Bureau of the Census and the Bureau of Economic Analysis. He said that the challenge of measuring the New Economy has proven to be a difficult one: “It really is a process of calibrating and recalibrating our understanding of new technologies and new measures in order to slowly construct a picture that makes sense to us and corresponds to the parameters of statistics.” A Critical Question for U.S. Policy The other part of his department’s job is to advise the Secretary of Commerce and the administration on issues of economic policy: whether the performance of the economy since 1995 is a temporary phenomenon, for example, or something more structural and long term. This is obviously a critical question for policy because the growth and productivity gains associated with the New Economy, if sustained, would not only improve the lives of all Americans, but it would also provide the resources to tackle almost any policy task in the next
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Measuring and Sustaining the New Economy: Report of a Workshop decade, from strengthening Social Security and cutting taxes to extending health coverage. An important indicator of the permanence of the economic conditions of recent years will be whether the economy’s extraordinary performance continues in the next business cycle. Another is whether other advanced countries can replicate our higher growth and productivity, since a truly New Economy can hardly be confined to a single country. Defining the New Economy Defining the New Economy by Results Dr. Shapiro noted that it seemed beyond doubt that the U.S. economy entered a period of high performance in the 1990s and that this cycle looks quite different from others in recent memory. As previous expansions of the postwar period aged, productivity and output growth slowed, inflation rose, real wages stagnated, and profits declined. The current expansion has matured and lasted longer than any of its predecessors, and yet productivity gains have accelerated from an average rate of 1.4 percent a year in the early 1990s to 2.9 percent since 1995. Real GDP growth has quickened. It has averaged about 4 percent in years seven and eight of this expansion, as compared to 1.1 percent or less in those years of the long expansions of the 1960s and 1980s. Real hourly compensation has grown after a long period of relative stagnation. The just announced income numbers for 1999 show a record of five consecutive years of income gains for average households. At the same time, profits have continued to grow generally. Moreover, strong output and profits have fueled very vigorous growth in real business investment, producing a record seven straight years of double-digit gains in investment and equipment, most of it for information technology hardware and software. Finally, inflation continued to fall through most of this period and even now, after several years of full employment, remains moderate. Defining the New Economy by Conditions The New Economy could be defined by these results. We could also define it, he said, by its conditions. Behind higher productivity and growth, for example, lie at least three key developments: Capital deepening—the acceleration in the growth of capital stock. Disinflationary forces that have held back price pressures for more than a decade, including more intense competition associated with deregulation and expanding world trade, shifts to tight fiscal policies at home and abroad, and the falling prices of information technology itself. The power of innovation.
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Measuring and Sustaining the New Economy: Report of a Workshop Information Technology and Productivity New Combinations Today, economies grow not by increasing capital or labor but by finding new ways to combine them that are more productive. Because the dominant forms of innovation for the last 20 years have come from information technology, many analysts point to information technology in defining the New Economy. Certainly, a critical factor in the recent performance of the United States has been the convergence of enormous increases in computing power and data storage with similar increases in the speed and carrying capacity of data communications systems, along with the growing power of new software. These advances have produced sharp, steady declines in the prices of computer and communications equipment that have driven both sustained business investment and a surge in Internet activity. In fact, it is the particular character of information technology innovation that may best define what is new about the New Economy. Many of these technologies have qualities that seem to make a real economic difference. Most obviously, they provide a new way of managing a resource common to every aspect of economic life. That is, information technology represents a general-purpose innovation that is being applied to every sector and aspect of the economic process. Network Effects Dr. Shapiro noted that another difference is the network effects that characterize many information technology markets. That is, the more the technology is deployed, the greater its value. If you buy a Saab, the car is worth the same to you whether there are 5,000 other Saabs on the road or 100,000. When you buy Box A: Taking Full Advantage of Information Technology “A growing body of firm-level evidence . . . shows that simply installing advanced information technology, by itself, has little effect. Firms that buy information technology equipment do not raise their productivity unless they also rethink and change their organizations to take full advantage of information technology’s capacities. So organizational innovation may be as important as the technology itself.” Robert Shapiro, U.S. Department of Commerce, 1998-2001
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Measuring and Sustaining the New Economy: Report of a Workshop Windows or a new graphics program, its value may increase as more people buy it, because that increases your ability to communicate and interact. In a certain sense, network effects can bring increasing rates of return; as innovation spreads, its productivity benefits can increase not just arithmetically but quadratically. Cascading Innovation Finally, as industries apply information technology to their businesses, economists see evidence of what might be called cascading innovation. Productivity gains come not just from faster processing of information but also from changes in the way a firm operates and from additional technological advances made possible by the information technology. Moreover, as information technology spreads and its potential is more widely recognized, it generates demand for even faster processing—that is, another round of information technology innovation, which in turn creates the potential for more innovation both organizationally and in the products and services the re-organized and information-technology-enabled firm can create. This demand forms the economic basis for Moore’s Law, under which the computing capacity of chips doubles every 18 months. Moreover, these enormous and regular increases in chip power provided the technological basis for the Internet, which in turn now generates more rounds of cascading innovation in how businesses operate and what they produce. The Network Model Recognizing again that the important factor is not so much the information technology investment but what businesses and workers do with it, we could approach this question of the New Economy from the point of view of the firm. Here one can see the shape of what some call the network model of digital economy firms. The key tasks for these firms are to form a network of special goods and services, enter a network that ultimately will produce or support a final product, or provide the goods and services that support the network itself. A simple example is the “big three” automakers’ project to move their supply chains to the Web, shifting online hundreds of billions of dollars a year in orders from tens of thousands of suppliers. Perhaps a better example of a network model is the Cisco Corporation, which outsources virtually all of its production so it can focus on product design and innovation. Last year Cisco received 78 percent of its orders and handled 80 percent of its customer service issues on the Internet. Substituting Information Technology Capital for Labor Information technology and the network model for the firm may drive other New Economy changes in how we work. Looking into questions of job creation,
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Measuring and Sustaining the New Economy: Report of a Workshop Economics and Statistics Administration researchers ranked U.S. industries according to their degree of information technology intensity, that is, the ratio of information technology equipment per worker. They then divided the list into two groups. One included the most information-technology-intensive industries measured by the ratio of information technology equipment per worker, which produced about 50 percent of all income in the nonfarm business sector. The second encompassed the relatively less information-technology-intensive industries that produced the other 50 percent of total income. They found that most of the employment growth in the last decade occurred in the less information-technology-intensive industries. The more information-technology-intensive half of the economy accounted for only 12 percent of the growth in employment between 1987 and 1998. This may suggest that one of the features of the New Economy is that it substitutes information technology capital for labor in noninformation technology industries, even as it generates jobs in the information technology sector itself at high rates. Nevertheless, within the high-growth information technology sector itself, the Department of Commerce expects employment in the information technology industry to grow 40 percent over the next 8 to 10 years. It also expects the number of workers in core information technology fields, today roughly 2.4 million computer scientists, engineers, systems analysts, and programmers, to nearly double. A Need for More Compelling Evidence Regardless of how this New Economy is defined and measured, he said, not everyone agrees there is anything very new about it. Dr. Shapiro cited Robert Gordon of Northwestern University as one who argues that the increases in productivity have come almost entirely in the 12 percent of the economy that produces durable goods and that information technology has not been very productive elsewhere in the economy. These conclusions have been challenged by economists at the Commerce Department, the Federal Reserve, and others (including the next symposium speaker, Dale Jorgenson). Still, no one knows for certain until the nation has completed this business cycle and until more compelling evidence is developed.5 Dr. Shapiro concluded by saying that a skeptic could maintain that the verdict is still out, and that the skeptic could be right. “But in all frankness,” he said, “we don’t think so.” 5 For more discussion of the views of Professor Gordon and others, see the special section on “The New Economy” in The Economist, September 23, 2000, pp. 5-40.
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Measuring and Sustaining the New Economy: Report of a Workshop DISCUSSION Difficulties in Measuring the Effects of Information Technology A brief discussion period followed, during which Dr. Bresnahan suggested that the Department of Commerce’s framework might offer two challenges to the federal statistical system. One is a wide discrepancy between the department’s greatly improved measures of output in the information technology sector itself and the less effective way it measures the improvement of output when information technology is used in other sectors. The second is that the network model constituted a serious challenge to traditional ways of measuring firm establishment and might require new concepts for capturing the locus of economic activity in the network world. Dr. Shapiro responded to the first question by saying that the difficulty in measuring the effects of information technology in the major service sector reflects a problem in statistical technique. The Commerce Department has made significant progress in financial services and banking, in which the productivity numbers have been revised. Such progress, however, is difficult to sustain without resources: The budget for the Bureau of Economic Analysis had been cut for every one of the last seven years, so that by 2000 the economy was 25 percent larger and the bureau’s real budget to measure the economy was 12 percent smaller. Self-Service “Operators” Dr. Cerf commented that gathering good economic data is important to making good economic decisions and added an anecdote about productivity in the telephone system. Years ago when a person wanted to make a phone call, an operator had to place it. With direct-distance dialing, everyone became their own operator. Given that self-service is similarly becoming an important component in what happens on the Internet, bringing an important impact to the cost of operations, he inquired as to whether economic statistics can take self-service into account. The Need for New Measures Dr. Shapiro answered that the department is currently trying to do this, beginning with the first “e-tail” statistics and proceeding next year with the first annual business-to-business measures. He mentioned a larger conceptual problem, which is to adapt the structural logic of the statistics to large changes in the economy. That is, how can they develop measures that capture new activities and still be able to compare what is happening today with what has happened in previous years. This is particularly difficult when changes in a firm or in the nature of work alter the way the Bureau of Labor Statistics (BLS) needs to measure unemployment and employment. The
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