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Created 2001-04-04
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The "New Economy," Structural Change, and Macroeconomic Outcomes

J. Bradford DeLong
delong@econ.berkeley.edu
http://www.j-bradford-delong.net/

March 2001


Abstract

Claims that we are in a "new economy" have become less strident over the past year with the collapse of internet-company stock valuations. Nevertheless, the smart way to bet is that the data processing and data communications revolutions have significantly altered and will continue to alter the structure of the macroeconomy and the pattern of the business cycle. The information-technology revolution is the prime candidate for driving the acceleration in aggregate labor productivity growth in the 1990s, and the boom in information-technology investment promises to pay dividends in the form of accelerated aggregate labor productivity growth for at least a decade to come. It is a credible candidate for driving the reduction in the natural rate of unemployment, the NAIRU. It may well promise to diminish the aggregate economy’s vulnerability to inventory fluctuations, which have for more than a century been a principal driving force behind the business cycle.


Claims that we are in a "new economy" are less strident than a year ago. The crash of the technology-heavy NASDAQ market and the end of the tech-heavy IPO boom have quieted voices that used to claim that the old economic rules had been superseded. But in some respects, in the United States at least, the old economic rules have not been superseded but modified, and we can expect the macroeconomy of the next generation to be different in key aspects from the macroeconomy of the past. For, as Steven Cohen, John Zysman, and I wrote two years ago, the "new economy" is "not about… smooth growth, permanently rising stock prices… or permanently low rates of unemployment, interest and inflation." Instead, the "new economy" is about ongoing technological revolutions taht are doing for information processing and organizational control something like what the nineteenth-century industrial revolution did for materials processing and transportation.

The U.S. macroeconomy in the next generation is likely to see:

--Significantly higher productivity growth than in the past generation.
--A significantly lower natural rate of unemployment--and thus a better-performing labor market--than in the past generation.
--A smaller inventory shock-driven component to the business cycle.
--But also more financial market instability.


The information technology revolution has almost surely driven the recent acceleration in American productivity growth. Production per hour worked rose between 1995 and 2000 at 2.5 percent per year, more than double the pace seen in the preceding quarter century since 1970. The case for attributing this acceleration in productivity growth to the technological revolutions in information technology is now very strong. If this attribution is correct, then this reacceleration of productivity growth is the most significant macroeconomic consequence of the "new economy," and one that all by itself justifies focusing much attention on computers and communications.

Back before 1995 critics of visionaries who saw the computer as transforming the world pointed to slow and anemic growth in aggregate labor productivity. The end of the 1960s saw the American economy undergo an aggregate productivity slowdown, in which the trend growth rate of labor productivity fell by more than half. It seemed unreasonable that what computer visionaries were touting as an extraordinary advance in technological capabilities should be accompanied by a record-breaking slowdown in economic growth. As Nobel Prize-winning MIT economist Robert Solow posed the question, if the computer is so important "how come we see the computer revolution everywhere but in the [aggregate] productivity statistics?"

However, as Federal Reserve Board economists Steven Oliner and Daniel Sichel pointed out in the early 1990s, the then-failure to see the computer revolution in the aggregate productivity statistics should not have come as a surprise. In the 1970s and 1980s computers were simply too small a share of the economy and their use was not growing fast enough for it to have a large impact on aggregate productivity. In the 1980s information technology capital–computer hardware, software, and communications equipment–accounted for 3.3% of the income earned in the economy, and the price-adjusted information technology capital stock was growing at only 14% per year. You multiply these two numbers together to get an estimate of the contribution of the information technology sector to economic growth: in this case, a contribution of 0.49% per year.

But in the 1990s things changed. Today, according to Oliner and Sichel,information technology capital accounts for 7.0% of income earned and is growing at 20% per year. Multiply these two sets of numbers together to find that the increase in the economy’s information technology capital stock now accounts for 1.4% per year of economic growth, and this estimate covers only one of the several channels through which information technology is boosting American economic growth.

And beginning in 1992, the American economy began an extraordinary investment boom. Reduced and then eliminated budget deficits combined with foreigners' renewed desire to invest in America and accelerated technological progress in information technology meant that from 1992 to 2000 real business fixed investment grew at 11% per year, with more than half of the additional investment going into computers and related equipment. As the information technology investment boom took hold, productivity growth and growth in real GDP accelerated as well. Real GDP rose by an average of 3.9% per year between 1995 and 2000. Output per hour grew at 2.7% per year.
 
So far, however, this productivity growth boom has lasted only half a decade. In America, productivity growth is extremely volatile from year to year. The boom in productivity in 1992 was a one-time flash in the pan (although it did give rise to a series of articles on the "jobless recovery"). The "Morning in America" boom in productivity growth of 1983-1986 was also not sustained, at least in part because of high government budget deficits that reduced capital accumulation. Is there reason to believe that this boom in the second half of the 1990s is different?

Yes, there is. The rate of growth of the economy’s information technology capital stock will not slow down rapidly or immediately. The same dollars spent on computers today deliver twice as much in the way of real useful capital as they did five years ago because of the extraordinary fall in computer prices. Even simple use of amortization funds to replace obsolete computers will generate enormous rates of increase in the capital stock.

Moreover, there is every reason to think that the fall in computer and communications equipment prices will continue. The pace of technological advance in information technology has been well-described for three decades by what has come to be called "Moore's Law"--the rule of thumb that Intel cofounder Gordon Moore's set out a generation ago that the density of circuits we can place on a chip of silicon doubles every eighteen months with little or no significant increase in cost. Moore's Law has held for thirty years; it looks like it will hold for another ten at least. Moore's Law means that today’s computers have 66,000 times the processing power of the computers of 1975. It means that in ten years computers will be approximately 10 million times more powerful than those of 1975 at roughly constant cost. The installed base of information processing power has increased at least million-fold since the end of the era of electro-mechanical calculators in the 1950s. Such extraordinary increases in productivity in data processing and data communications equipment manufacture have the potential to have a large impact on overall productivity growth as long as the share of total income attributable to computer capital does not collapse.

Will the share of total income attributable to computer capital collapse? The share of total income attributable to computer capital will remain constant only if the productive value of the marginal computer declines no more rapidly in percentage terms than the total computer capital stock increases. In theory there is no reason that the productive value of the marginal computer might not decline very rapidly indeed. But in practice this seems unlikely. Computers appear to meet economists Timothy Bresnahan and Manuel Trajtenberg’s definition of a true engine of growth, a true general purpose technology, because each fall in the price of computers is accompanied by an exponential increase in demand for computers as it makes a whole new set of capabilities and uses profitable. In the 1950s computers went from special-purpose military-use machines to machines useful for organizations like the Census and human resource management departments in keeping track of individuals. In the 1960s computers were transformed into database managers. In the 1970s and 1980s computers came to American business as wordprocessors and what-if machines: devices to answer questions like "what if this paragraph looked like that?" or "what if the growth rate were twice as fast?" Now computers have become embedded into objects as sensors and controllers and have become portals to access and manage the worldwide information systems that are our Internet and our intranets. At each stage, the fall in the price of computers has been marked not by a restricted but by an enormous expansion of the uses to which these machines are put. There is no reason to anticipate that this will change. And so there is no reason to look to a slowdown in the computer-driven component of American productivity growth.

A likely important macroeconomic consequence of the acceleration in productivity growth is the reduced natural rate of unemployment that we are seeing today. Back at the start of the 1990s most macroeconomists estimated that the economy’s natural rate of unemployment was between 6.5 and 7.0 percent. If unemployment fell below that level, it was argued, inflation would begin to accelerate. These estimates were based on long historical experience, dating back to the acceleration of inflation in the late 1960s.

However, just about the time in the mid-1990s when the aggregate rate of productivity growth began to boom the natural rate of unemployment began to fall. The fall in unemployment to 6% in the mid-1990s did not lead to any acceleration in inflation, nor did the fall in unemployment to 5% and then 4.5% in the late 1990s. Only in the last year and a half or so, as the unemployment rate has fallen to 4%, have there been any signs at all of rising inflation. By now the deviation between what inflation is and what one would have predicted inflation would be from the pre-1990s pattern is substantial. If the pre-1993 pattern had continued to hold, we would now expect American inflation to be nearly 6 percent, not the 2.5 percent it is.
 
It is likely that the natural rate of unemployment is linked to the rate of economy-wide productivity growth. If workers' aspirations for real wage growth depend on the rate of unemployment, then a speedup in productivity growth will reduce the natural rate. When productivity growth is slow, then a low rate of unemployment will lead workers to demand real wage increases above the rate of productivity growth that firms cannot grant and remain profitable. Before their profits disappear, firms will begin to economized on--fire--workers. Unemployment will rise until it is high enough to curb worker aspirations for real wage growth to a level consistent with productivity. With a higher rate of productivity growth, firms can afford to pay higher real wage increases without going bankrupt. The unemployment rate consistent with real wage growth aspirations that match productivity is lower. Hence an economy with higher productivity growth has a lower natural rate of unemployment.

Yet another likely macroeconomic consequence of the information technology revolution is a decline in the inventory fluctuation-driven component of the business cycle. True information technologies improve businesses' abilities to know about and manage their goods in the pipeline from initial raw materials to final sales. Individual will make fewer mistakes in forecasting demand for their own products, and in aggregate the total inventories in the economy will be less likely to unexpectedly accumulate or unexpectedly collapse in response to a mismatch between production and demand. This is potentially important for the size of the business cycle. As Alan Blinder pointed out, in a typical recession the fall in inventory investment is between 50 and 100 percent of the peak-to-trough fall in real GDP. To a large extent, post-World War II recessions are episodes in which businesses have decided or have found that their inventories are too large, and have cut back drastically on production in order to liquidate some of these excess inventories. Significantly diminish the amplitude of aggregate mistakes in inventory accumulation, and you promise to significantly diminish the magnitude of fluctuations in aggregate demand, production, and employment as well.
 
For the past two decades, the ratio of inventory-to-shipments in manufacturing has been on a steep decline. Today’s durable manufacturers hold only two-thirds as much inventory relative to their shipments as they held in the 1970s. Today’s non-durable manufacturers hold one-fifth less inventory in proportion to sales as they did in the 1970s. It would be a mistake to attribute all of this relative decline in inventories to the "new economy." But information technology is playing an important part. Thus we can expect that one consequence will be a reduction in the inventory-driven portion of the business cycle.

The news, however, is not all good. The past decade has seen a striking increase in financial market volatility, both within the United States and in international financial markets. If we look far back in history at the long bull market runs of the American stock market in the past, we see that for each 10% rise in the real value of dividends over a twenty-year period the real value of stock prices rises by 15%. Two-thirds of a standard bull market is supported by a proportional increase in dividends and profitability. The most recent bull market since 1982 is the largest ever seen: a more than seven-fold increase in real values. Yet real dividends paid on a pro-rata share of the S&P composite index have risen by less than 30% since the early 1980s. And earnings on a pro-rata share have increased by less than 50 percent.

Any economist examining this pattern must reach one of two conclusions (or hedge his or her bets by taking a position between them). The first is that for a century the stock market has been grossly underpriced–has discounted the risk associated with owning equities at a much too high rate. It is only now that equity valuations are "fair" in the sense of promising expected real returns on stocks akin to those on bonds plus a small extra risk premium. The second is that the stock market today is subject to irrational exuberance on a scale never before seen in America. And in addition there is the extraordinary international asset market volatility seen in the European crisis of 1992, the Mexican crisis of 1994-1995, and the East Asian crisis of 1997-1998.
 
Where does this volatility come from? Writing in the _Journal of Economic Perspectives_, Terrence Odean and Brad Barber have pointed out that our current stock market as it has been fueled by the growth of online trading and online information appears to meet all the conditions that experimental economists have found are likely to make markets most vulnerable to prolonged mispricing and to speculative bubbles. No one claims to understand the situation fully. But there is definitely reason to worry that the extra information about and access to the stock market provided by the information technology revolution has not led to a more informed marginal investor, or to asset markets that are better judges of fundamental values.


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