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The author was Chairman of the Council of Economic Advisers and a member of President Clinton's cabinet from August 1999 until January 2001. This speech draws on joint work with Robert Lawrence and the staff of the Council, especially Kathryn Shaw and Steven Braun. The views expressed are the author's own and do not represent the Institute for International Economics, its staff or Trustees.
The US economy was growing too fast in 1999 and the early part of 2000-around 6 percent a year. The labor market was already tight and getting tighter, as the unemployment rate dipped to 3.9 percent, and wage inflation was creeping up. US stock markets in 1999 and 2000 had moved too high. The rates of growth of corporate earnings built into stock prices, particularly technology stocks, were unrealistic to the point of fantasy.
In recent months, the US slowdown has been harder than almost anyone expected. The manufacturing sector has been hard hit, as has the telecom sector, and the rest of the economy is only just staying afloat. With a bit of luck and good policy, the United States will avoid a recession, but going from a growth of 6 percent a year, down to 1 percent or so, is painful enough. And of course the stock market correction has hit consumers' wallets and their confidence.
Europeans can be forgiven if they feel that the United States is getting its comeuppance for excessive optimism and excessive hype of the "new economy." Some commentators argued that the United States was immune from recessions or that the laws of economics had been repealed. It was thought that the stock market would keep rising to even more startling levels. Clearly, these misperceptions have been exposed over the past year.
In this speech, I will argue, however, that there is evidence of structural change in the US economy. Technologies and innovations that have been developed over many years are coming to fruition and paying off in improved economic performance. (See the discussion in the OECD report on growth [2000a]). In particular, there is now supportive evidence of an acceleration of productivity in service and other industries that are purchasing information technology (IT). This evidence marks a change from what had been observed previously. Until fairly recently we were grappling with the famous Solow paradox. Some years ago, economist Robert Solow noted that while computers seemed to be everywhere, the rate of growth of productivity in US economy remained very sluggish.
The new findings showing productivity benefits in industries using the new technologies are particularly important. In the end, the information revolution will only increase the living standards of consumers to the extent that it increases productivity not just in high-tech industries, but also in the industries producing the goods and services that consumers buy. Moreover the changes taking place go beyond what can be captured in productivity statistics. The benefits of new products and services are captured only partially in standard output and productivity measures.
There may be lessons for other countries from the experience of the United States. All countries must make their own economic policy decisions. There are always tradeoffs and differences in priorities that guide the policy choices of individual countries. But at the same time, there are useful lessons from the long 1990s boom in the United States, notwithstanding the recent slowing of US growth. There is a gap in economic performance between the United States and the European Union and there are steps that Europe can take that would increase its rate of growth over the long term and improve the living standards of its citizens.
The Nature of the Economic Gap
One conspicuous difference between Europe and the United States is that Europe does not have a high-tech sector that rivals the United States. There is no European Silicon Valley. The world's leading companies in the high-tech are heavily US-based companies. According to the OECD (2000b), 36 of the largest IT firms in 1998 were US-based, nine were Japanese and only four were EU-based. Only one European company (Siemens) was in the top 40. This is also reflected in the different proportions of high-tech production in the different regions. The United States has larger production of information and communications technology (ICT) in relation to its GDP than does the European Union (see Figure 1). This is an important difference, as the rapid growth in output and productivity in the US high-tech sector has contributed substantially to overall GDP growth. (Japan is an exception to this rule. Its ICT sector is much larger than that in the United States [5.2 percent of GDP], but economic growth in Japan has been very weak because much of the rest of the Japanese economy is in trouble.)
Another gap between the United States and the European Union is that productivity growth sharply accelerated in the United States in the second half of the 1990s, whereas productivity growth either failed to accelerate or even slowed in the European Union. The acceleration in the United States, of course, is partly linked to the dynamism of the high-tech sector, but now also seems to be occurring also in old economy industries as well. (Productivity growth over time in the United States is measured by the increase in real output per hour worked in the non-farm business sector).
Perhaps the most significant gap overall is in real GDP per capita. With the United States indexed to equal 100, per capita GDP in the European Union in 2000 was only 69, a gap with the United States of 31 percent. Of course the European Union includes some countries that are not yet fully industrialized, but that does not explain much of the gap since France was at 72, Germany at 73, Italy at 70 and the United Kingdom at 69. The large European economies are all pretty close to the EU mean. In order to add to the overall perspective, it is worth including Japan, which, with per capita GDP of 74, is pretty much in line with Europe. In short, the major European industrial countries and Japan are operating at a level of economic activity that is three quarters of the US level, or a bit below.
If we had looked at the same numbers five or ten years ago, a somewhat similar story would have emerged, so this is not a new conclusion. But the striking thing about the past ten years, and particularly the last five years, is that the United States is pulling away. For much of the period after World War II there was rapid convergence taking place, with Europe and Japan growing much faster than the United States with rapid productivity growth and full employment. Per capita incomes relative to the United States were rising rapidly. No longer. In the past five years the United States has experienced both more employment growth and more productivity growth than any of the other countries on the chart.
The fact that per capita GDP in the large industrial countries is clustered in the range of 69 to 74 percent of the United States conceals some sharp differences. GDP per capita can be broken down into two variables: how many hours a country's residents work and how much is produced by each hour (output per hour or productivity). A country can get to a given level of GDP per capita by having a low-employment economy with high productivity or vice versa. Figure 2 plots these two variables with GDP per hour on the vertical axis and hours worked per capita on the horizontal axis. And we see that all the countries except the United States are stretched along a downward sloping curve. To reach roughly the same level of GDP per capita, France has high productivity and low employment, while Japan has low productivity and high employment.
There is one obvious reason why a group of countries would be stretched along a downward sloping curve. If an economy has low employment, this will concentrate economic activity on the most productive workers and jobs. But there is not a fixed tradeoff here. There are other factors at work and the position of the United States on Figure 2 shows it. The United States is far to the northeast of the European Union and Japan on the figure. It has higher employment than any country except Japan and also has the highest level of productivity. The United States is the only large country that has been able to combine full employment with high productivity.
A country's citizens make different tradeoffs between the amount of work they want to perform and the amount of income they want to receive. Europeans may choose more leisure and be willing to accept a lower GDP. Given that unemployment is high in Europe and that early retirement and reductions in work-hours have been imposed, individuals may not be making free choices about their labor-leisure tradeoff. But regardless, any country is better off if it makes its choices along a tradeoff curve that is as far to the northeast in Figure 2 as possible. The challenge for France is to keep expanding employment, but do so by creating high productivity jobs. The challenge for Japan is to raise productivity and maintain a desirable level of full employment. The challenge for the European Union is to increase both productivity and employment. Policies that increase a country's economic efficiency and that encourage the productive use of new technologies will give its citizens the best options, even if it chooses to exercise those options very differently than does the United States. To the extent that the United States has done this successfully, this may provide lessons for Europe.
The United States has made choices in other areas that I disagree with. For example, it is highly unfortunate that 40 million Americans lack health insurance and policies are needed to address this problem. Poverty rates are hard to compare, but it does seem that the United States has more abject poverty than Europe. But those issues are not the focus of this speech. I believe those problems in the United States could be addressed without undercutting the flexibility and efficiency of US markets. This speech is about the generation and use of new technologies-the new economy-where the United States has been strong.
Box: Measurement Issues
Differences in measurement methodology have been suggested as an explanation for the faster growth rate of GDP in the United States in the 1990s. In particular, the United States uses hedonic price indexes for computers and only some European countries do the same. It does not appear, however, that measurement issues are significant or even go in the direction of overstating US relative growth. Gust and Marquez (2000) at the Federal Reserve in Washington reviewed differences in measurement methodology and concluded that, while there are differences in approach, they did not significantly change the growth comparisons. I conducted an alternative check using the OECD's GDP comparisons made with purchasing power parity exchange rates. These comparisons apply a common measurement approach to all countries and determine each country's GDP relative to the United States, measured in a common set of prices in a given benchmark year. By comparing different benchmarks over time, one can see which countries have GDP growing faster than the United States (closing the gap) and which countries are growing slower (widening the gap) and by how much. These comparisons suggested that the domestic measurement methods in Germany and France slightly overstated their GDP growth during 1990-96 relative to the US approach to measuring GDP growth. Italy, Japan, and the United Kingdom slightly understated their growth.
A final measurement issue arises because the international comparisons described above use total GDP rather than the output of the business sectors of the economies. In work carried out at the McKinsey Global Institute (1997), estimates were made of market sector GDP, which suggested that productivity in France and Germany relative to the United States declined roughly 10 percentage points when government and nonprofit sectors were excluded. OECD estimates imply very low relative productivity for health care, education, and other nonmarket segments in the US. Measuring productivity in the nonmarket sectors of an economy is very difficult. If we were to restrict our discussion only to market sector GDP, the productivity gap between the United States and the European Union would widen. (See the discussion in Baily and Solow 2001).
I. The Shifting Productivity Trend in the United States
Estimates made at the Council of Economic Advisers (2001) found that US labor productivity grew at around 3 percent a year from 1995 through 2000, an increase of 1.6 percentage points compared to the growth in the prior period, starting in 1973 (see Figure 3. Labor productivity is measured by output per hour in the nonfarm business sector). This rapid growth is comparable to the rate of productivity growth achieved in the 1950s and 1960s and is a dramatic change compared to the slow growth of 1.4 percent a year achieved from 1973-95. What could be the sources of this rapid growth?
One reason for the strong growth after 1995 may have been that there was strong demand in the economy-it may have been partly a temporary business cycle effect. This is a very hard thing to estimate and economists differ in their conclusions when they make those estimates. Analysis at the Council of Economic Advisers suggested that very little of the increase in productivity growth was cyclical. Robert Gordon (2001) has used a different approach suggesting that as much as half a percentage point a year might have been cyclical. I will use the Council's estimate here, but the general conclusions of this talk stand up either way.
A second reason for the rapid growth is that the computer hardware sector of the United States has experienced an extremely rapid and even accelerated pace of technological advance. Using evidence based on the decline in quality-adjusted hardware prices, the Council estimated that this sector added 0.4 percent a year to labor productivity growth after 1995 (compared to 0.2 percent prior to 1995). It is remarkable that a small sector of the economy can contribute that much to performance in the aggregate. But clearly this sector alone is not the main source of growth or its acceleration. The computer hardware sector itself contributes only modestly to overall economic performance and explains only a small fraction of why US productivity growth was faster after 1995.
The third source of productivity growth comes from increases over time in the amount of capital available to each worker-capital deepening. Using a standard model of economic growth, we found that capital deepening accounts for labor productivity growth of 1.1 percent a year after 1995, an increase from its contribution of 0.7 percent a year in the prior period. And much of this contribution to growth (and all of its contribution to faster growth after 1995) came from investments made in information capital (both hardware and software). This calculation suggests that the purchase and use of information capital has been a substantial contributor to the strong US economic performance of the late 1990s. However, Europe or any advanced country has access to computer hardware and software. Countries do not have to produce IT capital to use it. In fact much of the IT capital used in the United States is not produced in the United States. The United States is a major importer of this equipment.
The remaining contribution to labor productivity growth comes from increases in what is called "total factor productivity" or "TFP" in the broad economy-everything except for the computer hardware sector. TFP increases represent improvements in the efficiency with which capital and labor are used to produce output. They reflect the impact of innovations and new business practice and the growth of more productive firms at the expense of less productive ones. This source of growth contributed 1.2 percent a year to labor productivity growth after 1995, a huge jump from the modest increase of 0.2 percent a year prior to that. Some of this TFP growth surely comes from innovations that were facilitated by developments in the IT sector. Some, however, may come from changes in the economy that are unrelated to IT.
It is hard to resolve definitively the issue of how large the role of IT has been in the TFP growth and acceleration. This contribution to growth is estimated as a residual, not from direct observation. Looking at labor productivity growth by industry can cast additional light on the issue. Where has the productivity acceleration taken place?
II. Faster Growth in IT-Using Industries
Table 1 uses newly available data to show labor productivity growth by industry from 1989-95 and 1995-99. Each industry's output reflects the value added in that industry and labor input is measured by the number of full-time equivalent employees. The table reveals that services (non goods-producing) industries account for much of the acceleration of labor productivity, a finding sharply different from the conclusion reached in earlier analysis by Robert Gordon (2000). (Andrew Sharpe [2000], by contrast, gives results closer to those reported here). Large service industries such as wholesale and retail trade, finance and business services have all had increases in labor productivity growth greater than for the economy as a whole. There has been much discussion of the importance of supply-chain management improvements enabled by IT (see Litan 2001, for example). And it is striking that wholesale and retail trade increased their productivity growth by well over 4 percentage points after 1995. Finance is a sector that has invested heavily in IT. It achieved strong productivity growth pre-1995 and even stronger growth post-1995. Business services, another heavy IT user, has shifted from negative growth pre-1995 to solid positive growth post-1995.
Some claimed that measurement problems explained why pre-1995 productivity growth in services was sluggish. However, as in the years prior to 1973, these problems have not prevented the detection of substantial gains recently.
Durable manufacturing had stellar productivity growth before 1995 and even more stellar growth afterwards (this sector of the economy includes computer hardware production), but other goods-producing industries did less well. Overall, the post-1995 productivity acceleration in goods industries was less that that in the private industry total.
Some service industries might have been expected to show IT-related improvements that did not do so. For example the telecom industry actually shows slower growth after 1995, probably because this industry has been changing so much and investing heavily in developing its networks. Despite these exceptions to the general rule, the last two rows of Table 1 show support for the view that IT has helped growth. The industries were ranked by IT intensity based on their IT spending relative to value-added. They were then divided into two, the less and the more intense IT users. The intense IT-using industries showed much faster labor productivity growth over the entire period 1989-99, and showed about a 50 percent larger acceleration after 1995. (Kevin Stiroh [2001] has analyzed the industry data in more detail and reaches a very similar conclusion. The increase in productivity growth is broad-based across industries and is linked to the use of IT).
It is dangerous to read too much into any one specific number in Table 1, because the price indexes available to translate increases in current dollar output into increases in real output are often inadequate. However the overall pattern of the industry data is important. Prior studies found little evidence of IT's contribution to growth outside of high-tech manufacturing (see for example TFP estimates through 1996 by Dale Jorgenson and Kevin Stiroh (2000)). The results in Table 1 do not prove that innovations enabled by IT are boosting productivity in service industries, but they are certainly consistent with that view.
I do not have a detailed industry analysis of the EU countries to make a comparison like that above. But the recent work of the OECD (2000a, 2000b) concludes that the deployment of ICT hardware and software in Europe lags behind that in the United States (except for cell phones). The OECD provides a variety of different measures of deployment, including use of hardware and software. Figure 3 is typical of the gap that they observe, and shows that the installed base of PCs per hundred white-collar workers is much higher in the United States than in the large European economies.
Results such as these, however, should be interpreted carefully. They reflect symptoms more than causes. If, hypothetically, Europe were to suddenly subsidize PC use, it is not clear that much would happen to overall economic performance. The challenge for Europe is to create an environment in which companies in all industries are looking for ways to improve their performance and they buy ICT to the extent that it helps them succeed in doing this.
III. A Wave of Innovation
It appears that much of the acceleration of US productivity over the past five years is structural. It may last a short time or a long time-that remains to be seen. But regardless of the future of productivity, the economy has changed in this expansion and new technology has played a substantial role in this transformation.
Despite the recent stock market weakness, the overall increase in corporate valuation has been astounding. The market value of US corporations now greatly exceeds what it would cost to replace their physical capital assets. The market is valuing companies that have special technical knowledge, special skills, or other forms or intangible capital.
The improved economic performance and increased valuation of intangible capital has coincided with a wave of both creation and adoption of innovation. One sign of this is the surge in R&D spending. According to data from the National Science Foundation real private R&D has risen rapidly since the mid-1970s, but it took off in the late 1990s, rising 8 percent a year from 1995-99. The fact that patents granted soared after 1995, suggests the growth in R&D has been productive. There has also been a surge in the production of IT, rising by a factor of 13 between 1992 and 2000 in real terms. Employment has also increased sharply in industries providing computer, data processing, and communications services (Figures 4).
What has generated the increased pace of innovation and its translation into improved economic performance? Clearly a necessary condition is that the technological opportunities had to be there, but this is not a sufficient condition. More was needed.
In the US in the 1990s there has been heightened competition in an increasingly deregulated economy faced with strong international competition. IT innovation is driven by the demand for improved technologies in the industries using the IT. The United States has competitive service industries, often on a global scale, and this encourages them to seek out new technologies to improve their own productivity. Almost 70 percent of all IT products are purchased by wholesale and retail trade, finance and telecommunications. The demand for IT products and services drove rapid innovation in the high-tech sector.
Another driver of the wave of innovation and IT investment is that companies are outsourcing parts of the value chain to concentrate on core competencies-extending the benefits of comparative advantage. R&D is an example of this. Large companies can face bureaucratic obstacles to creativity and innovation in their in-house R&D efforts. In response, the amount of R&D done in small companies is increasing, so are technology alliances and acquisitions. Twenty-three percent of all privately employed scientific researchers in 1999 worked in companies with fewer than 500 employees, up from 16 percent in 1993. The number of companies in the IT area more than doubled between 1990 and 1997.
At the same time, IT often involves production with high fixed costs and low marginal costs, so that achieving a large market share in the area of core competence is often essential. Companies are achieving this in different ways, but one sign that it is occurring is that both the number and total value of mergers and acquisitions have exploded.
New forms of financing have contributed to the changes in organization. R&D is risky and historically this made it difficult for small companies to get funding for technology development. The rapid growth of venture capital has alleviated this problem, facilitating the increase in small-firm R&D noted above. The growth of the IPO market has also provided a way for young companies to access the capital market.
One aspect of the wave of innovation involves complementarities among different technologies. When innovations occur in one area, it can bring benefits. But when complementary innovations occur together, the effects can be greatly increased. The combination of rapid advances in computing power, software and communications capabilities form such a set of complementary innovations. Large amounts of data can be processed and presented in a way nontechnical personnel can use and then transmitted to remote locations within the same firm or to other firms.
IV. New Technologies in Practice
In a recent survey, Brynjolfsson and Hitt (2000) review the evidence from case studies and company studies on the ways in which IT affects economic performance. It is difficult in such case studies to find good performance measures, but notwithstanding this limitation, the authors describe results that are very sensible. They point out that companies that simply purchase high-tech hardware and software do not achieve much in the way of better performance. Perhaps this is a reason why early computerization seemed to yield so little in faster productivity growth. Instead, they argue, companies must redesign their business systems to take advantage of what the new technologies offer. I would take one step further and argue that in many cases it is necessary for some companies to die and new companies be born in order for productive change to take place.
Supply chain management is a clear example of how complementary innovations have helped productivity and performance. A retail purchase is the last step in a long chain that includes raw material suppliers, component manufacturers, assemblers, wholesalers and retailers. These are linked in a chain that involves ordering, invoicing, sorting, loading and unloading, and shipping. Each step uses resources and creates potential mistakes, shortages or excess inventories. New management systems, facilitated by IT, have improved supply chain management by eliminating steps and reducing paperwork, fluctuations in production and inventory (see for example, Roy Shapiro (2000) and Richard Wise and David Morrison (2000)).
In manufacturing, increasing computing power and decreasing cost have brought about performance gains through automation, numeric control, computer-aided design, and other channels. Information technology has also facilitated changes in job design, giving manufacturing workers more decision making authority on the shop floor and placing a premium on technical skills. Firms are also relying increasingly on performance-based pay, including profit-sharing and stock option plans.
Supplier and customer relations have also changed. Supplier contacts that were formerly kept at arm's length have become more closely integrated and coordinated, thanks in part to automated procurement systems. Data that used to be kept proprietary are now increasingly shared between business partners. Inventories have shrunk. Firms use databases of transaction histories to target products and services to individual customers, while setting up telephone call centers and other operations to improve service.
The changes witnessed in the steel industry exemplify these changes in production processes and management practices. The fundamental processes forming it into an intermediate product, and shaping and treating that product into final goods. But a number of technological advances, many incorporating information technology to measure, monitor, and control these processes, have affected almost every step in steel production.
As recently as 10 or 15 years ago, steel making involved extensive manual control and setup and relied heavily on operator's experience, observation, and intuition in determining how to control the process. Computer processing of data from sensors, using innovative software, has improved the ability to control processes, allowing faster, more efficient operation, in addition to more uniform product quality. For example, the availability of computing power to quickly process data has enabled steel makers to combine sophisticated software decision making algorithms (called neural networks) with precision sensing devices to continuously monitor and adjust the ever-changing conditions in the electric arc furnaces widely used for melting steel. This closer control reduces both energy consumption and wear and tear on the equipment. The setup to cast the molten steel into an intermediate product has changed from a process in which several operators would "walk the line," setting the controls for every motor and pump, to one in which a single operator uses an automatic control system that synchronizes and sets the equipment. The rolling process now incorporates sensors that constantly inspect for deviations from the desired shape, allowing the operators to make corrections before material is wasted. Operators can remotely control the speed and clearance of the rolls using computer-controlled motors to correct problems as they develop.
The result of this integration of computers into steel making has been a significant improvement in performance. Together with other technological changes, such as larger furnaces and improvements in casting practices, and the closing of older, inefficient plants, the new technologies have contributed to higher product quality and productivity. Steel makers today use less than four worker-hours to produce a ton of steel, down from about six worker-hours in 1990. The best-performing mills have achieved results of less than one worker-hour per ton.
The trucking industry is using the new technology to better serve its customers' logistics needs. To be efficient, trucking firms must satisfy customers with prompt pickup and delivery of loads while minimizing unused capacity in the form of both idle equipment and empty and incompletely loaded trips. By coordinating information from many shippers and consignees in a geographical area, firms can reduce wasted movement. To track and dispatch trucks efficiently, they use sophisticated locating technology, such as the satellite-based global positioning system; real-time traffic, weather, and road construction information; computers on board the trucks themselves; complex software and algorithms; and supporting hardware to organize customers and loads. The ability to effectively use information to manage shipments not only contributes to efficiency but also enables other innovative processes such as automated exchange of information.
Banks have also used new technologies to improve their processes. In the mid-1990s retail banks introduced imaging technology to process checks more efficiently. Digital images of checks are stored on a central computer and scanned by software that reads the amounts on the images. Checks are then balanced against deposit slips automatically. Introducing this technology has freed employees from having to record check amounts manually, lowered transactions costs by eliminating the need to move checks physically, and allowed banks to reorganize their workflow around a more extensive division of labor.
V. The Importance of Competition Against Best Practice
One traditional way of judging whether or not a market is competitive is to compute an index reflecting market shares in relation to number of competitors. On that basis many industries that really are not very competitive may look quite competitive. In retailing, for example, there may be hundreds or even thousands of competitors. In a manufacturing industry, perhaps there are dozens of suppliers of components. But in both of these cases, it is quite possible that the degree of competitive intensity that really matters is rather low. The retail competitors can be mostly small proprietorships or "mom and pop" stores. These stores are protected from competition from highly productive, "best-practice," multinational competitors by laws that prevent price cutting, or zoning rules that make it hard for the most productive retail formats to expand. These high productivity stores include the discounters like Wal-Mart or Carrefour, but also include higher-service specialty chains like the Gap that need shopping malls to gather retail traffic.
Among manufacturers there may be explicit trade barriers that protect less productive companies and there may be more subtle forms of preference, tied to subsidies from regional governments or low-cost financing. Strong ties among companies and local preferences among consumers can also act as barriers to entry and competition against best practice.
Effective competition often involves industry consolidation and a reduction in the number of competitors. Weaker companies disappear, and this in turn often means job losses and dislocations that are painful for workers and communities. The costs of adjustment provoke hostility to the process of "globalization," in which best-practice companies apply their skills in a world-wide context. If this process is impeded, however, economic performance will suffer.
There is substantial resistance to globalization within the United States and trade barriers, including anti-dumping provisions, have protected inefficient producers in the United States. But the US economy has the advantage of being a large single market and has been that way for a long time. When "voluntary" trade restrictions limited auto imports from Japan, the Japanese companies came and set up high productivity plants in the United States, forcing the domestic industry to adjust. Shoppers in New England do not care or even know where the store they buy from is headquartered, and zoning laws are flexible, so high productivity retail formats have spread nationwide. The introduction of trigger prices for imported steel had a limited impact because mini mills sprang up to compete effectively against the established integrated producers. Domestic competitive intensity in the United States is very high, despite some policy lapses.
When competitive intensity is high, companies are constantly forced to find ways to improve their operations or develop new products or services. This encourages the use of new technologies and encourages the search to find productive ways of using these new technologies (see the discussion of the McKinsey Global Institute studies in Baily and Solow 2001). The best policy for encouraging the new economy is to encourage competition and create the demand for the new technology.
VI. The Importance of Labor Market Flexibility
Much has been written about the importance of labor market flexibility in Europe in order to restore full employment and I cannot add much that is new to this discussion. As I think many are aware in Europe, the introduction of new technologies and an accelerated pace of change reinforce the need for labor market flexibility. The European Union must meet the challenge highlighted in figure 2 of this paper, the challenge to increase employment as well as productivity.
One view of the rise in European unemployment in the 1980s is that jobs were lost in traditional or old-economy industries, but new attractive jobs were not created on a sufficient scale. Supported by generous unemployment, disability or early retirement programs, workers who lost jobs, and young people looking for new jobs, remained unemployed or left the labor force rather than accept the jobs that were available. High minimum wages may also have prevented the absorption of low-skill workers.
One solution to unemployment, if this story is correct, is to allow for lower wages for less-skilled workers and to limit the amount or duration of unemployment benefits. This forces workers to take whatever jobs are available. To an extent, the United States has followed this approach and created millions of jobs for those workers, including immigrants, who have limited education or skill levels. On balance, I would rather see people working than unemployed, and with income support provided by programs like the Earned Income Tax Credit, families can achieve reasonable standards of living even when their wages rates are modest (living standards that would be much better with adequate health insurance).
But creating only low-wage or low-skill jobs is not the answer and is not in fact what has happened in the United States. The Council of Economic Advisers (1999) analyzed the nature of the jobs created in the United States between 1993 and 1999 and found that 81 percent of the job growth was in industry/occupation categories paying above-median wages. And there were solid increases in real wages over this period. New technologies and economic change create good jobs in large numbers, including the roughly 1.5 million additional jobs in IT service industries in the 1990s.
Labor market flexibility combined with product market flexibility and competition are consistent with, in fact essential to, a full-employment, high-productivity economy. The fears about job loss associated with competition and new technologies are exaggerated. After all, there has been no shortage of jobs in the US economy. The period of rapid productivity growth in the late 1990s coincided with declining unemployment and faster real wage gains than had been seen for many years. What cannot be guaranteed is that workers will be able to hang onto the same jobs they have now.
VII. The Internet, the Dot.Com Bust and the Slowdown
It is clear in retrospect that excessive optimism about the commercial potential of Internet-based companies resulted in some very foolish funding decisions, where large sums of money were given to start-up companies with little real prospects of success. The Internet spawned a frenzy of activity that fed on itself, following the classic pattern of speculative bubbles. Such an environment fosters bad decisions and outright fraud.
Despite this problem, the fundamental changes in the US economy that are taking place will continue. Estimates made by Goldman Sachs (1999) show that the application of the Internet for commercial purposes has only very recently become important and has not been the main source of rapid economic growth in the 1990s. The volume of Internet transactions was not large enough to have had a major influence over that period. The innovations in supply chain management described earlier were already taking place before the explosive growth of the Internet took place, as companies developed their own internal networks. But the same Goldman Sachs study also suggested that the Internet is a major innovation that will become more important going forward. The Internet lowers the cost of communication and allows small companies to participate in B2B networks and cut costs.
The volatility and disruption in financial markets in 2000 and 2001 has been a barrier for companies that have good business plans and are now looking for funds. And the sharp slowdown in the US economy is hitting the high-tech sector hard. As we go through this period of slowdown or recession, we will learn much about the sustainability of the rapid productivity growth of recent years. High-tech investment has fallen sharply and perhaps this means productivity growth will slow also.
There is no question that the US slowdown will result in at least a temporary slowing of productivity. I stated earlier that estimates made at the Council of Economic Advisers suggested that little of the acceleration of productivity in the United States after 1995 had been cyclical in origin, but this is because demand for goods and for labor was already very strong in 1995. Productivity was already above trend in 1995 and we found no additional cyclical pull on productivity after that. However, the current slowdown is likely to drop the level of productivity down to its trend, or even below trend this year, resulting in at least a temporary slowing of growth. The real question will be how well things go in the recovery.
One view says that the surge in economic performance was driven primarily by superheated investment and since that is now over, the growth is bound to slow. There could possibly be a vicious cycle of slow growth and low investment. My own view is to be cautious, but more optimistic. There has been a huge wave of high-tech investment, some of it creating excess capacity. If businesses can now absorb this investment and grow into the capacity they have created, the prospects for the future are good. A continuation of 3 percent productivity growth will be hard to achieve, but continued growth at over 2 percent is very possible.
VIII. Lessons and Policy Issues for Europe
1. It is not essential to have a Silicon Valley in order for Europe to take advantage of new technologies. The use of new technologies is more important to long-term growth and living standards than the production of high-tech equipment. Silicon Valley and other high-tech centers have created much wealth and many good jobs. Certainly they are assets. But when traditional or old-economy industries innovate and develop better business systems, this benefits consumers, raises real wages for ordinary workers and increases family incomes.
2. The new economy does not mean that old industries will all disappear and be replaced by industries producing high-tech products. It means that the new technologies are altering the way traditional industries operate. It is altering the nature of competition. It is changing the size and scope of companies.
3. In order to take advantage of the productivity gains available from the new technologies, Europe must have policies that will allow structural change. Less productive companies must contract or close down. The labor market must be flexible and provide an adequate supply of skilled workers. Land must be available to build new offices, distribution facilities, and so on. Despite the Lisbon Accord, the competitive intensity in product markets in Europe is far less than in the United States. Competition is the driver of economic efficiency and innovation.
4. There are costs to individuals and communities with the new economy. Silicon Valley and the Dulles corridor are tributes to urban and suburban sprawl. Workers lose their jobs in large and small companies that fail to change or that cannot compete. There are profound social changes that accompany the economic forces driven by the new technologies. However, flexibility and change in the end promote the growth of new jobs.
5. In the mid 1990s, the US economy was growing rapidly and yet there was little sign as yet that there had been any increase in the potential growth rate. Real GDP was rising faster than most estimates of potential growth. One possible course for monetary policy would have been to raise interest rates enough to slow the economy to its estimated potential rate of growth. Any different policy ran the risk that inflation would accelerate and eventually recession would be inevitable. Instead, monetary policy allowed the rapid growth to continue. An accommodative monetary policy did not create the new economy, but a restrictive monetary policy may well have slowed it down.
6. Investing in high-tech capital alone does not provide superior economic performance. But high rates of such investment seem to be an essential part of the success of the 1990s boom. There were two important elements to the financing of that investment in the United States. Fiscal policy and openness. The shift from budget deficits to surpluses helped keep long-term interest rates low, spurred the rise in the stock market and encouraged the investment boom. If budget deficits had continued into the 1990s at the same rate they occurred in the 1980s, it is hard to see how the supply-side boom could have been sustained. But domestic saving in the United States was not enough to supply the needed capital. The United States was able to attract capital from overseas to fund investment. And of course, it used these funds to buy components and equipment from overseas. The engagement of the United States with the world economy was a necessary condition for the rapid growth.
References
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Shapiro, Roy. 2000. "Supply Chain Coordination: The Journey," presentation at the Harvard Business School (1 November).
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Stiroh, Kevin J. 2001. "Information Technology and the U.S. Productivity Revival: What Do the Industry Data Say?" Mimeo, Federal Reserve Bank of New York (January).
Wise, Richard, and David Morrison. 2000. "Beyond the Exchange: The Future of B2B," Harvard Business Review 78, no. 6 (November-December): 86-96.
Tables and Figures
Figure 1: Production of ICT Goods as a Share of GDP is Lower in Europe Percent in 1997
Source: OECD 2000b, IMF: IFS
Figure 2: The Potential to Shift the Economic Tradeoff
Figure 3: US Productivity Growth Increased after 1998
Output per Hour in the Nonfarm Business Sector
Index, 1992=100
Figure 4: A Host of Measures Show a Surge in Information Technology Activity in the US since the Early 1990s
Indicators of Growth in Information Technology Activity
Source: National Science Foundation
Patents Granted for Information Technology Applications
Thousands per year
Source: Council of Economic Advisors, based on data from the Department of Commerce
(Patent and Trademark Office)
Industrial Production of Information
Technology Goods
Index, 1990=100
Note: Information technology goods comprise computers, semiconductors, and communications equipment
Source: Board of Govenors of the Federal Reserve System
Employment in Information Technology Services Industries
Millions
Note: Information technology services comprise computer and data processing services and communications services
Source: Department of Labor (Bureau of Labor Statistics)
Figure 5: The Development of PC's in the Work Place is Lower in Europe
PC's per 100 White-Collar Workers, end 1997
Source: OECD 2000b
Table 1: Labor Productivity Growth in US Industries
GDI Originating per Full-Time Equivalent Employee,
Average Annual Percent Changes, Selected Periods
Commentary Type