Section 2:

General economic trends


Robert J. Gordon’s essay, “Secular Stagnation: A Supply Side View,” presents a decidedly pessimistic outlook on our future, arguing that the slow pace of GDP and productivity growth of the past half-decade will not reverse. The information technology revolution, he explains, provided a one-time boost to productivity and now is offering diminishing returns; progress is stalled. Furthermore, this most recent revolution did not give us the same massive productivity gains that the first and second industrial revolutions drove in the twentieth century. He sees slower growth in educational attainment, the decline of marriage, the rise of single-parent households, and the high incarceration rate compounding other headwinds to economic growth, and he believes the United States faces a future of secular stagnation.

Dean Baker, in “Growth and Dynamism of the U.S. Economy in the Recovery,” responds to Gordon, agreeing with his supply-side explanation for the slow and weak U.S. recovery from the financial crisis. Baker, however, focuses on the demand-side factors that compound the supply-side story, but also offer a better opportunity for recovery. He points out that the U.S. economy suffered from an enormous drop in demand as a result of the collapse of the housing bubble in 2007 and 2008. During the recovery, he explains, consumption and business investment were strong contributors to GDP, as were net exports, but there is no source of demand that can replace the role of the housing sector prior to the recession. Baker sees reason to believe that slow productivity growth is related to the demand shortfall, especially according to changing compositions of economic activity across sectors. He concludes, then, that we need higher levels of demand to put the economy back on a higher trajectory of growth and productivity.

Robert B. Cohen presents a more optimistic view of our economic future in his essay, “What’s Going On with Growth and Dynamism in the U.S.?” He acknowledges that productivity growth since 2009 has been lackluster and raises concern about long-term economic health. And, he recognizes that there are concerns that technological progress in automation and artificial intelligence will suppress and even erode employment growth. However, Cohen suggests that technological progress in computing, storage, networking, and virtualization will provide a massive boost to productivity. These changes, he argues, will also be positive for job creation because, even as technological change makes some work obsolete, it is creating new sources of work that didn’t previously exist. Much of this activity, he suggests, may not be captured well by current government statistics, and better measurement tools are needed to depict the effect of new technology, particularly its impact on the services sector.

Secular Stagnation: A Supply Side View

By Robert J. Gordon Stanley G. Harris Professor of the Social Sciences Northwestern University and NBER
Robert J. Gordon
Robert J. Gordon

Introduction

Alvin Hansen (1939) popularized the term “secular stagnation,” and we are now, at the suggestion of Larry Summers (2014), considering the application of Hansen’s term to the current U.S. economy, because the pace of output recovery in the five years since the business cycle trough of 2009 has been so slow. Yet the conditions of aggregate demand and supply in 2015 are the mirror image of those when Hansen wrote. The nation in 1938 faced a crisis of woefully inadequate aggregate demand, but not of aggregate supply, because the underlying rate of productivity growth in the late 1930s was as fast as at any time in U.S. economic history. In contrast, in early 2015 the output gap was small and shrinking, while productivity growth over the past five years has been only a fraction of the rate achieved in the late 1930s.

The supply side of secular stagnation refers to potential real GDP growth, the growth rate of output consistent with steady non-accelerating inflation. During the five years ending in 2014:Q3, actual real GDP grew at 2.4 percent per annum, while the unemployment rate declined from 10 percent to 6 percent, implying that potential real GDP was growing substantially less than actual output. Slow potential real GDP growth matters both because of its direct impact on the standard of living and also because of its indirect effect in reducing net investment, which, in turn, feeds back to slower productivity growth.

Secular stagnation in the form of slow potential output growth over the past half-decade reflects the slowness of growth in both labor productivity and aggregate hours of work, and slow growth in the latter is due both to slowing population growth and a decline in the Labor Force Participation Rate (LFPR). Because the behavior of the LFPR has received ample research attention lately, this paper focuses on the sources of slow productivity growth.1 The central argument is that the digital electronics revolution has begun to encounter diminishing returns. Further evidence is provided that suggests a decline in the “dynamism” of the economy as measured by the rate of creation of new firms. The paper concludes by examining some of the long-term implications of slow potential real GDP growth.

Labor Productivity Growth, TFP Growth, and the Three Industrial Revolutions

The magnitude of the slowdown in productivity growth is shown in Table 1, which displays for five time intervals the annual growth rates of real GDP, aggregate hours of work, real GDP per hour (i.e., labor productivity), and Total Factor Productivity.2 By subtracting the effects on output growth of capital deepening and of improved educational attainment, TFP growth provides the best available measure of the underlying pace of innovation and technological change. TFP growth since 1972 pales in comparison with the middle of the twentieth century (1920–1972). Average TFP growth of 0.70 percent for 1972–2014 was barely one-third of the 2.01 growth rate achieved between 1920 and 1972. Labor productivity growth after 1972 also fell short of 1920–1972 growth by the same difference of 1.3 percent. In the past five years, labor productivity growth has declined further to only 0.87 percent per year, while TFP growth has further slowed to 0.48 percent per year.

Note: 2004 and 2014 data refer to third quarter of each year.

The rapidity of TFP growth during 1920–1972 reflects the dynamics of the industrial revolutions that created the modern economy. The first industrial revolution (IR #1) of steam engines created railroads, steamships, and the transition from wood to metal, with effects felt throughout the nineteenth century. The second industrial revolution (IR #2) combined the nearly simultaneous invention of a host of general-purpose technologies, including electricity, internal combustion engine, telephone, wireless, chemical engineering, and the conquest of infectious diseases. Paul David (1990) has argued persuasively with his “delay hypothesis” that there were good reasons for the long delay between the first electric power station in 1882 and the revolutionary introduction of electric machinery in the early 1920s. A similar argument can be made regarding the internal combustion engine; two decades after its 1879 discovery were required to develop the drive chain that transmitted power to the wheels. The productivity impact of motor vehicles awaited sufficient numbers as the total number of motor vehicles in the United States grew from 4,000 in 1900 to 469,000 in 1910 to 9.2 million in 1920 to 26.7 million in 1929. And, rapid improvements continued after 1920 along every dimension of IR #2, including the electrification of industry, the development of the vertical city, the sensation caused by radio and by motion picture “talkies,” the spread of air conditioning, the development of petroleum-based plastics, the conquest of infant mortality, the invention of antibiotics, and the spread of commercial air transport.

At about the same time as the impact of IR #2 began to encounter diminishing returns after 1970, along came the digital electronic third industrial revolution (IR #3). The benefits of IR #3 began in the 1960s and 1970s with mainframe computers replacing the tedious clerical work of manually preparing bank statements and telephone bills, and continued into the 1980s with the PC, the ATM machine, and retail bar-code scanning. Yet, the growth of output per hour was relatively slow in the 1970s and 1980s, as shown in the middle line in Table 1. Soon David (1990) developed his delay hypothesis and appeared to be prophetic when there was an upsurge of growth in output per hour to 2.51 percent per year during 1996–2004, as shown in Table 1. Productivity analysts have credited the dot-com revolution, which married the computer with communications and developed e-commerce and search engines, for the productivity growth revival of 1996–2004.

As we can see in Table 1, however, the productivity upsurge of 1996–2004 was followed by mediocre productivity growth of only 1.22 percent per year in the decade after 2004. TFP growth barely exceeded 0.5 percent per year during both 1972–1996 and 2004–2014, interrupted by the temporary eight-year upsurge to 1.43 percent (still well short of the pre-1972 rate) during 1996–2004. A comparison of the two intervals with slow productivity and TFP growth, that is, 1972–1996 and 2004–2014, shows that, while both had relatively slow rates of productivity growth (1.38 and 1.22 percent per year, respectively), they differed markedly in their growth rates of output (3.01 vs. 1.58) and of aggregate hours (1.63 and 0.36). When we decompose this 1.27 percentage point slowdown in hours growth, we find that most of it (0.91 percentage points) is due to a shift from positive to negative growth in the LFPR and the remainder (0.39 points) to slower growth in the working-age population.3 For our subject of secular stagnation in potential output growth, a given percentage-point contribution to slowing potential output growth is equally important, whether it originates in labor productivity or in aggregate hours of work.

Could the Third Industrial Revolution Be Almost Over?

To understand the sources of today’s secular stagnation, we need to reflect on the decline in the growth rate of labor productivity in the past decade as displayed in Table 1. What factors caused the productivity revival of the late 1990s to be so temporary and to die out so quickly? Most of the economy already has benefitted from the Internet and Web revolution, and, in this dominant sphere of economic activity, methods of production have been little changed over the past decade. The revolutions in everyday life made possible by e-commerce and search engines were already well established—Amazon dates back to 1994, Google to 1998, and Wikipedia, as well as iTunes, to 2001. Will future innovations be sufficiently powerful and widespread to duplicate the relatively brief revival in productivity growth that occurred between 1996 and 2004?

Stasis in the Office. The digital revolution centered on 1970–2000 utterly changed the way offices function. In 1970, the electronic calculator had just been invented, but the computer terminal was still in the future. Office work required innumerable clerks to operate the keyboards of electric typewriters that had no ability to download content from the rest of the world. Starting from this world of 1970, by the year 2000 every office was equipped with Web- linked personal computers that could do not just word processing without repetitive retyping, but also could download multiple varieties of content and perform any type of calculation at blinding speed. By 2005, flat screens had completed the transition to the modern office. But then progress stopped. Throughout the world, the equipment used in office work and the productivity of office employees closely resembles that of a decade ago.4

Stasis in Retailing. Since the development of “big-box” retailers in the 1980s and 1990s, and the conversion of check-out aisles to bar-code scanners, little has changed in the retail sector. Payment methods gradually changed from cash and checks to credit and debit cards, and the process of card authorization became almost instantaneous by the late 1990s. The big-box retailers brought with them many other aspects of the productivity revolution. Wal-Mart and other big-box chains transformed supply chains, wholesale distribution, inventory management, pricing, and product selection, but that productivity-enhancing shift away from traditional small-scale retailing is largely over. The retail productivity revolution counts as among the many accomplishments of IR #3 that largely are completed and will be difficult to surpass in the next several decades.

Decline in Business Dynamism. Recent research has used the word “dynamism” to describe the process of creative destruction by which new startup and young firms are the source of productivity gains that occur when they introduce best-practice technologies and methods as they shift resources away from old, low-productivity firms. The share of total employment accounted for by firms no older than five years declined by almost half from 19.2 percent in 1982 to 10.7 percent in 2011. This decline was pervasive across retailing and services, and, after 2000, even the high-tech sector experienced a large decline in startups and fast-growing young firms.5

Education and Social Decay Subtract from Future Productivity Growth

What about the future? The historic contribution to labor productivity growth of rising educational attainment has almost come to an end, and the increased number of children growing up in single-parent households is likely to cause further erosion in educational achievement.

The Contribution of Education to Productivity Growth. Growth accounting has long recognized the role of increasing educational attainment as a source of economic growth. Goldin and Katz (2008) estimate that educational attainment increased by 0.8 years per decade over the eight decades between 1890 and 1970. Over this period, they also estimate that the improvement in educational attainment contributed 0.35 percentage points per year to the growth of productivity and output per capita. To the extent that American educational attainment is rising less rapidly now and in the future than in the past, the future growth rate of productivity will tend to be slower.

The surge in high-school graduation rates—from less than 10 percent of youth in 1900 to 80 percent by 1970—was a central driver of twentieth-century economic growth, but the graduation rate has stagnated since 1970. The United States currently ranks eleventh among the developed nations in high school graduation rates and is the only country in which the graduation rates of those aged twenty-five to thirty-four is no higher than those aged fifty-five to sixty-four.6 The role of education in holding back future economic growth is evident in the poor quality of educational outcomes at the secondary level. The 2012 OECD international PISA tests scores ranked the United States among the thirty-four OECD countries as seventeenth in reading, twentieth in science, and twenty-seventh in mathematics.7

At the college level, longstanding problems of quality are joined with the newer issues of affordability and student debt. In most of the postwar period, a low-cost college education was within reach of a larger fraction of the population than in any other nation, thanks to free college education made possible by the GI Bill and minimal tuition for in-state students at state public universities and junior colleges. The United States led the world during most of the last century in the percentage of youth completing college. The percentage of twenty-five-year-olds who have earned BA degrees from four-year colleges has inched up in the past fifteen years from 25 percent to 30 percent, but that is now ranked twelfth among developed nations.

And the future does not look promising. The cost of a university education has risen since 1972 at more than triple the overall rate of inflation. Even when account is taken of the discounts from full tuition made possible by scholarships and fellowships, the current level of American college completion has been made possible only by a dramatic rise in student borrowing. Americans owe $1.2 trillion in college debt, and an increased fraction of the next generation may choose not to complete college as they are priced out of the market for education.

Socioeconomic Decay. The decline of marriage as an institution among Americans who lack a college education is relevant to the future rate of productivity growth, because children—particularly boys—who grow up in households lacking a father are less likely to graduate from high school and complete college and more likely to drop out of high school and become engaged in criminal activity. An important source of this sociological change is the evaporation of good, steady, high-paying, blue-collar jobs. Partly because men without college educations have lacked the incomes and steady employment to be attractive marriage partners, and partly because women have become more independent as opportunities in the labor market have opened up for them, fewer couples are getting married. As a result, an ever-larger share of children are growing up without a father in the household.

Charles Murray (2012) documents changes in social indicators for the bottom third of the white population. His most devastating statistic is that, for mothers aged forty, the percentage of children living with both biological parents declined from 95 percent in 1963 to 34 percent in 2004.8 For white high-school graduates, the percentage of children born out of wedlock increased from 4 percent in 1982 to 34 percent in 2008 and from 21 percent to 42 percent for white high-school dropouts. June Carbone and Naomi Cahn (2014) conclude, “The American family is changing—and the changes guarantee that inequality will be greater in the next generation. For the first time, America’s children will almost certainly not be as well educated, healthy, or wealthy as their parents.9

An obstacle to future employment is the growing share of young men with prison records. A recent study showed that, between 1979 and 2009, the percentage of white male high- school dropouts who had been in prison rose from 3.8 percent to 28.0 percent. For blacks over the same time interval, the percentage that had been in prison rose from 14.7 percent to 68.0 percent.10 Any kind of criminal record and, especially, time in prison severely limit the employment opportunities available to those whose prison sentences are ending. According to the FBI, no less than one-third of all adult Americans have criminal records, and this stands as a major barrier to employment.11

Will the Temporary Productivity Revival of the Late 1990s Be Repeated?

In the productivity history of Table 1, the 1996–2004 revival is notable for its magnitude, but also because it was temporary and could not sustain itself for more than eight years. There are other U.S. economic performance indicators that support the view that the 1996–2004 achievement was unique and will not be repeated anytime soon.

First, the temporary productivity revival of the late 1990s was accompanied by an equally temporary acceleration of growth in manufacturing capacity from 2.5 percent during 1972–1995 to 6.5 percent in 1999–2000. Then there was a collapse in capacity growth to negative values in 2011–2012.

Second, net private investment as a share of the private capital stock, measured as a five- year moving average, fell from 3.8 percent during 2000–2001 to only 1.0 percent in 2013.

Third, the rate of decline of computer prices per unit of performance became steadily more negative, with a peak rate of decline of 14 percent in 1998–1999, followed by a retreat back to a decline of only 1 percent per year in 2014. The waning pace of performance-adjusted price declines for computers was accompanied by the post-2006 demise of Moore’s Law, a relationship that, since 1965, had reliably predicted that the number of transistors on a computer chip would double every two years. But, since 2006, the doubling time has exceeded four years.

Conclusion

Secular stagnation is evident in every measure of economic performance over the past five years, most notably the growth rates of output, labor productivity, and aggregate hours of work, which, during the past decade through 2014:Q3, averaged 1.6, 1.2, and 0.4 percent, respectively. Potential real GDP appears to be running at about half of the actual output growth rate of 3.1 percent achieved during 1972–2004. The repercussions of such slow growth are significant. Growth in real per-capita income over the past ten years has been only 0.6 percent per year, less than one-third of the 2.1 percent achieved from 1890 to 2007. The ratio of net investment to the capital stock has declined over the past five years to 1.0 percent, less than one-third of the average ratio achieved between 1950 and 2007. The Congressional Budget Office estimates that the federal debt-to-GDP ratio in 2024 with current tax and spending policy will be 78 percent, but slower real GDP growth implies that the ratio will instead be 87 percent.

The paper provides three separate arguments to explain slow productivity growth in the past decade. The first is that fundamental changes in business methods were concentrated in the dot-com era of rapid productivity growth and, once new equipment was installed and new business practices were adopted, the impact on productivity growth of the ICT revolution began to encounter diminishing returns. A second argument points to the measures of economic performance that all had the same timing, peaking in the late 1990s and declining to low levels in the last few years, including the growth in manufacturing capacity, the ratio of net investment to the capital stock, the rate of decline in the ICT price deflator, and the speed of improvement of microchip technology. Another measure of waning economic performance includes the rate of new business startups.

Slower growth in potential output from the supply side, emanating not just from slow productivity growth, but also from slower population growth and declining labor-force participation, reduces the need for capital formation, and this, in turn, subtracts from aggregate demand and reinforces the decline in productivity growth. In the end, secular stagnation is not about just demand or supply but also about the interaction between demand and supply.

About the Author
Robert James "Bob" Gordon is an American economist. He is the Stanley G. Harris Professor of the Social Sciences at Northwestern University. He is known for his work on productivity, growth, the causes of unemployment, and airline economics. Gordon graduated Magna Cum Laude with a B.A. from Harvard University in 1962. He then attended Oxford University and received his B.A. in 1964. He received his Ph.D. from MIT in 1967.

Footnotes

  1. On the sources of the decline in the LFPR, see Aaronson et al. (2014).
  2. Real GDP is from the BEA back to 1929 and from Kendrick (1961, Table A-XIX) for 1920–1929. Total economy hours of work are from an unpublished series obtained from the BEA for 1950–2014 and from the same Kendrick table for 1920–50. The TFP growth rates are derived in Chapter 10 of my forthcoming book (2015).
  3. Other components of the ratio of payroll hours of work to the working-age population net out almost to zero.
  4. Using the example of economists, the digital revolution was centered in the decade 1985–1995, by the end of which professors were typing their own papers using math-savvy word-processing software, doing complex statistical analysis on their own PCs rather than on mainframes, and were sharing files with co-authors, no matter how remotely located.
  5. Davis and Haltiwanger (2014, p. 14).
  6. http://globalpublicsquare.blogs.cnn.com
    /2011/11/03
    .
  7. www.oecd.org/pisa/keyfindings/PISA-2012-results-US.pdf.
  8. Murray (2012, Figure 8.11, p. 167).
  9. Carbone and Cahn (2014, p. 1).
  10. Data in this paragraph come from Pettit (2012, Table 1.4).
  11. Emshwiller (2014, p. A1).

References

Aaronson, Stephanie, Tomas Cajner, Bruce Fallick, Felix Gaibis-Reig, and William Wascher. 2014. “Labor Force Participation: Recent Developments and Future Prospects.” Brookings Papers on Economic Activity, No. 2, forthcoming.

Carbone, June, and Naomi Cahn. 2014. Marriage Markets: How Inequality is Remaking the American Family. Oxford and New York: Oxford University Press.

David, Paul A. 1990. “The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox.” American Economic Review Papers and Proceedings 80 (May, No. 2), 355–361.

Davis, Stephen J., and John Haltiwanger. 2014. “Labor Market Fluidity and Economic Performance.” NBER Working Paper 20479, September.

Emshwiller, John R. 2014. “Hiring managers Bedeviled by Flood of Arrest Records,” The Wall Street Journal, December 13, A1.

Goldin, Claudia, and Lawrence F. Katz. 2008. The Race Between Education and Technology. Cambridge and London: The Belknap Press of Harvard University Press.

Gordon, Robert J. 2015. Beyond the Rainbow: The Rise and Fall of American Growth. Princeton, NJ, and London: Princeton University Press, forthcoming.

Hansen, Alvin H. 1939. “Economic Progress and Declining Population Growth.” American Economic Review 29 (March, No. 1), 1–15.

Kendrick, John W. 1961. Productivity Trends in the United States. Princeton NF: Princeton University Press for NBER.

Murray, Charles. 2012. Coming Apart: The State of White America 1960–2010. New York: Crown Forum.

Pettit, Becky. 2012. Invisible Men: Mass Incarceration and the Myth of Black Progress. New York: Russell Sage Foundation.

Summers, Lawrence H. 2014. “Reflections on the ‘New Secular Stagnation Hypothesis.’” Coen Teulings and Richard Baldwin, eds. Secular Stagnation: Facts, Causes and Cures. London: CEPR Press, 27–40.

Growth And Dynamism of the U.S. Economy in Recovery

By Dean Baker Co-director and Co-founder Center for Economic and Policy Research, Washington, D.C.
Dean Baker
Dean Baker

The U.S. recovery from the financial crisis has been considerably slower and weaker than most economists had anticipated. There are both demand - and supply-side explanations for this weakness.

The demand side stems from the difficulty of recovering from a recession caused by the collapse of an asset bubble. These difficulties should not be minimized but, after an adjustment period, the economy should return to a path of healthy growth.

The supply-side explanation paints a considerably more dire picture. In this view, most prominently expressed by Robert Gordon, the U.S. economy now is on a long-term path of slow productivity growth.1

Gordon argues that the period from the middle of the eighteenth century to the end of the twentieth century essentially was an anomaly. Technologies developed during this period allowed for extraordinary gains in productivity and, therefore, rapid increases in living standards. Now that these technologies are largely in place throughout the economy, incremental gains from technology developments likely are limited.

Demand factors make the supply-side story worse. Specifically, if the weak economy of recent years slowed the pace of investment and led many people to drop out of the labor market due to long periods of unemployment, then the growth of our productive capacity would be reduced by an even larger amount than is dictated by technology.

This paper briefly outlines both of these explanations for economic weakness. It:

  • Explains how the collapse of the housing bubble led to a sharp falloff in demand.
  • Shows that this decreased demand is not easily replaced from other sources.
  • Examines evidence that productivity growth now is on a slower track than in the period prior to the downturn.

Assessing whether the economy now is on a slower productivity growth path is a difficult question that will not be answered here. However, it is possible to make preliminary comments based on the evidence to date.

The Collapse of the Housing Bubble and the Gap in Demand in the U.S. Economy

In the years prior to the downturn, the economy largely was driven by demand generated by the housing bubble. This demand came from two channels:

  • Growth in construction due to high house prices. The country was building homes at an extraordinary pace in the years 2002-2006. At its 2005 peak, residential construction accounted for six and one-half percent of gross domestic product (GDP). This compares to an average of just more than four percent 1970-1996, before the bubble began causing an uptick in housing demand.2
  • Consumption, namely the well-known housing wealth effect of between five and seven cents on the dollar. In turn, this means annual consumption increases by between five and seven percent of any increase in house prices. With the bubble generating more than $8 trillion in ephemeral housing wealth at its peak, this translated to between $400 billion and $560 billion a year in additional demand, or as much as four percent of GDP.

These sources of demand evaporated when the bubble burst 2006-2008. Instead of being extraordinarily high, housing construction fell to levels not seen since the early 1960s because the boom had created an enormous oversupply of housing. Similarly, consumption that had been driven by bubble wealth vanished. This created a huge gap in demand that was at the center of the steep 2008-2009 downturn.

During the recovery, the stimulus program originally replaced part of the lost demand, but this spur to growth was pared back sharply after 2011. Housing construction has returned to near-normal levels, but there still is a substantial gap in demand because no component(s) of GDP increased nearly enough to replace demand lost by the collapse of the housing bubble.

As a result, the economy remains well below its potential level of output. According to Congressional Budget Office (CBO) estimates, 2014 gross domestic product was roughly two percentage points below its potential ($350 billion).3

This figure arguably understates the gap because the CBO assumes that the downturn has permanently reduced the size of the potential workforce and led to slower growth in the economy’s productive capacity. The employment-to-population ratio for prime-age workers (ages 25-54) still is down by more than three full percentage points compared with the period before the recession.4 Because many people who have been unemployed for long periods have given up looking for work, they no longer are counted as unemployed. The CBO effectively assumes that a large portion of prime-age people who have dropped out of the labor force either no longer want to work or no longer have the necessary skills to get jobs. If most of these former workers both desire to work and have the necessary skills, then the CBO is underestimating potential GDP.

Another reason for believing the CBO may be underestimating potential GDP is that the current level is sharply below the level that had been projected before the recession. Figure 1 shows the level of potential GDP in 2014 and beyond that is projected by CBO, compared with the path that had been projected in 2008.

Figure 1

Source: Congressional Budget Office and author’s calculations.

Insofar as the 2008 projections were reasonable based on the capital stock, state of technical knowledge, and workforce skills, the economy has much more room to expand — except insofar as the downturn has made the economy permanently poorer. While the downturn almost certainly will have lasting consequences, the gap in CBO projections implies a loss in potential GDP of more than $500 billion compared with the path predicted before the recession. This loss will sum to more than $10 trillion during the next decade, based on the most recent CBO numbers.5

Figure 2 shows the 2007-2014 change in shares of the major GDP components. As can be seen, the largest declines are in residential construction, government spending, and spending on nonresidential structures.6 The one and one-half percentage point decline in the share of residential construction actually understates the falloff in spending on housing. Residential construction peaked during 2005 as a share of GDP; by 2007, its share already had dropped by almost two percentage points of GDP from its 2005 level.

Figure 2

Source: Bureau of Economic Analysis and author’s calculations

The full drop in the housing share of GDP 2005-2014 is 3.3 percentage points. There also has been a substantial falloff in government spending as a share of GDP, with almost the entire decline at the local level. In effect, local governments were forced to cut spending to deal with a revenue shortfall caused by the downturn. Spending on nonresidential structures fell by 0.5 percentage points as a share of GDP. This reversed a brief boom in spending, as current levels are consistent with its longer-term average.

It is worth noting that the share of:

  • Investment in equipment and intellectual property products is virtually unchanged from prerecession levels.
  • Consumption spending actually has increased by more than a full percentage point.

These patterns are worth noting because they refute two common myths about the weakness of the recovery:

  • While corporations do have an unusual amount of retained earnings, this is due to the unusually high levels of corporate profits, not lower-than-normal levels of investment.
  • Investment spending is not unusually weak by any historical standard.

Similarly, there is no evidence that consumers are reluctant to spend. One frequent explanation for the weakness of the recovery is that debt overhang from the housing bubble discourages consumer spending. In fact, consumer spending is quite high by historic standards. While individuals with large amounts of mortgage debt are spending less than if they did not face this burden, there are not enough people in this situation to have a substantial negative impact on overall spending levels.

The final area of spending shown in Figure 2 is net exports. This area has seen the sharpest rise in shares since 2007 due to a decline in the trade deficit from five percent of GDP in 2007 to 3.1 percent in 2014. The drop is even sharper from a peak of 5.6 percent of GDP in 2006. This drop in the size of the trade deficit has provided a major boost to demand during the recovery.

This analysis of the changes in demand since the 2007 business cycle peak points to where we can plausibly look for stronger demand to more fully recover. It is unlikely that consumption will rise beyond current levels as a share of GDP, nor is it clear that a further increase would be desirable. The low saving rates of most households leave them poorly prepared for retirement. It would be desirable to see more investment, but there is not a simple way to spur investment, at least in the short term.

Housing spending is likely to inch up as vacancy rates continue to fall to more normal levels. However, current construction levels are not far below long-term averages. Also, given the current demographic situation—a rapidly growing population of retirees and a much larger share of GDP going to health care than in the past—it is likely that the share of GDP going to housing construction will be lower in the future than during pre-bubble years.

This leaves the government sector and net exports as obvious sources for further increases in demand. Evidence from the experience of other countries before and during the downturn suggests that the United States could easily borrow to finance additional spending.7

The federal government could, in principle, spend more in areas that would promote long-term productivity, such as infrastructure, education, and research and development. However, for political reasons, it does not seem likely that there will be any substantial increase in government spending in the foreseeable future.

This leaves net exports as the one channel where there is a possibility of gaining a substantial boost to demand. The main factor in determining net exports is the value of the dollar relative to the currencies of our trading partners.

U.S. trade deficits had been relatively modest until the East Asian financial crisis resulted in a sharp run-up in the value of the dollar. This caused the deficit to increase from a bit more than one percent of GDP in 1996 to almost six percent of GDP in peak quarters of 2005.

The dollar continues to be sustained at prices far above market level because major central banks, most notably the central bank of China, choose to hold vast amounts of dollar reserves. By preventing the dollar from falling, these central banks ensure that they will run large trade surpluses, and the United States will run trade deficits.

A policy change, either through a process of negotiation with the United States or a decision by these countries, could alter their development policies. In terms of negotiating prospects, if the United States government were to make a lower-valued dollar a top priority in international negotiations, as opposed to other considerations (e.g., market access for financial or telecommunications companies, or patent and copyright protection) then it is likely it could make progress toward lowering the value of the dollar and reducing the trade deficit. However, this does not appear to be the current policy course.  

Alternatively, our trading partners may reverse course and decide that an under-valued currency no longer is in their best interest. In fact, this is the stated policy of the Chinese government, which has made increasing the share of consumption in GDP an explicit policy goal. This would fit with a policy that allows the Chinese yuan to rise, thereby reducing the price of imports. This would encourage households to buy more imported goods, and would be consistent with a shift in demand in China from investment and net exports to consumption. Other developing countries also may choose to follow the same path.

While this policy shift would be beneficial from the standpoint of boosting demand in the United States, the problem is the Chinese government’s timing, which appears to view the shift to a more consumption-oriented economy as a longer-term goal, not something to be completed in the next two or three years. This means that the policy shift is unlikely to boost demand in the United States in the near-term future.

Taking these factors together, there is little basis for expecting much acceleration in economic growth during the next few years. The average growth rate for the 2012-2014 economy was just under 2.4 percent, with no evidence of acceleration. This is roughly equal to or only slightly higher than most estimates of the economy’s potential rate of growth, meaning that it was making up little lost ground. The data for first-quarter 2015 clearly were depressed by worse-than-usual weather, but even the most positive scenarios removing the weather effects would not have raised the growth rate above two percent.

With the weak first quarter, 2015 is not likely to be any better than the average for the prior three years, and could well end up somewhat worse because the recent rise in the dollar is a serious drag on growth.  In short, we are likely to be in a situation where a lack of demand continues to act as a major drag on growth for the foreseeable future.

The Falloff in Productivity Growth: Is It More than Weak Demand?

Perhaps the most important unanswered question about the economy today is whether the slower pace of productivity growth since the downturn represents a long-term shift toward a slower trend pace of growth or if it simply is the result of weak demand due to the recession and slow recovery. This is difficult to answer, not only because we can’t say with certainty what would happen if demand growth were to accelerate and we returned to potential GDP, but we also can’t be certain about the timing of the productivity slowdown.

Productivity pessimists point to the fact that the slowdown appears to have begun before the recession.  The average rate of productivity growth 2004-2007 was just 1.7 percent.8 This is well below the three percent average 1995-2005.

However, this slowdown could be a matter of timing. Productivity growth 2002-2003 was 5.6 percent. If included in a five-year average, growth 2002-2007 averaged 2.5 percent, not markedly slower than the pace of the late 1990s and the earlier part of the past decade.

This shuffling of years is arguably appropriate. There was very little job growth following the 2001 recession. Employment continued to decline long after the recession officially ended, with payrolls not beginning to grow again until September 2003, and employment not surpassing the prerecession level until January 2005.

Until the more recent downturn, this was the longest stretch without job growth since the Great Depression. Employers clearly were reluctant to add new workers during this period, meeting growth in demand by getting more output from the same number of workers. When they did start adding workers at a more normal pace 2004-2006, it should be not surprising that productivity growth might have been weak. Obviously, the 5.6 percent productivity growth rate for 2003 was not sustainable; it was effectively borrowed from future growth. Supporting this view, during the last full year before the recession—third-quarter 2006 to third-quarter 2007— productivity grew by a healthy 2.7 percent.

While there are grounds for questioning whether the productivity slowdown began before the recession or was a result of the downturn, there is no doubt that productivity growth has been considerably slower since the recession began. Fourth-quarter 2007 to first-quarter 2015, the annual rate of productivity growth averaged just 1.2 percent. Past recoveries have been associated with a sharp upturn in productivity growth, but that has not been the case with this recovery. In fact, the strongest productivity growth occurred 2008-2009, while the economy still was contracting. In contrast to patterns in prior recessions, employers were quick to lay off workers, with hours worked falling even more rapidly than output.

Moreover, the weak productivity growth during the recovery has been broadly based across sectors. Figure 3 compares average productivity growth in six major sectors for 1995-2007 and 2007-2015, or the most recent year available.

Figure 3

Source:Bureau of Labor Statistics and author’s calculations

As can be seen in each of these sectors, there has been a slowing of productivity growth compared to the prerecession period. In manufacturing, the growth rate fell from 4.4 percent in the twelve years before the recession to just 1.4 percent in the years since 2007. Annual productivity growth in retail fell from 4.1 percent in the first period to 1.7 percent in the post-recession period. Productivity growth in air transportation fell from 5.9 percent to 1.2 percent, and in air travel from 3.9 percent to 1.2 percent. In restaurants, productivity actually fell at a 0.5 percent annual rate compared to a 0.8 percent growth rate during the earlier period. Among this group of industries, only trucking saw little change, with a modest decline from a 0.8 percent growth rate to a 0.5 percent growth rate.

It is not likely that a single factor can explain the declines across these industries and in other sectors of the economy. In several sectors, it is possible to identify factors that were major contributors to growth during the earlier period but likely were less important during the post-recession era.

In retail, the spread of major retail chains, such as Walmart, undoubtedly was a major factor in boosting productivity growth in the earlier period. The expansion of these chains has been much slower in the years since the recession.

Similarly, online booking services, such as Travelocity, likely helped to increase productivity in the airline industry by raising capacity rates. However, with airlines now averaging well above 90 percent capacity and many flights completely booked, there is not much room for further productivity gain through this channel.

In these and other sectors, there were one-time gains associated with technologies put in place 1995-2007 that will not allow for future gains of the same magnitude. However, it is wrong to conclude that further productivity gains are not possible. Trucking is notable in this respect. It had weak productivity gains in both the pre- and post-recession periods, indicating that information technologies have not yet provided much benefit to this sector.9  Nonetheless, it is virtually certain that, at some point in the not-too-,distant future, it will be economical to have self-driving trucks transport goods. This should lead to substantial productivity gains in the sector, although the exact pace and timing is uncertain.

There also clearly is an important demand component to the slowdown in productivity, both within and between sectors. The restaurant industry probably shows this most clearly. It is not plausible that technology for serving people in restaurants has deteriorated since the recession or that the people working in restaurants are less skilled now than they were during 2007. The decline in productivity is almost certainly attributable to the fact that restaurants can take advantage of the weak labor market to hire people at very low wages, including many people with substantial education and skills. The availability of low-cost labor makes restaurants willing to keep excess staff on the payroll to ensure good service and be prepared for any unexpected surge of customers.

This logic would apply to other sectors, as well. For example, the number of greeters at a Walmart who are there to guide shoppers to the correct aisle almost certainly will be lower in a tight labor market than in a labor market that still is far below full employment.

The slack in the labor market also makes firms less interested in adopting labor-saving technologies. If labor were again to become as scarce as it had been at the end of the 1990s business cycle, companies would be more interested in technologies that would allow them to conserve labor.

In addition to this within-industry effect of demand on productivity, there also is substantial between-industry effect. The lowest productivity sectors have seen the sharpest gains in employment since the recession. Table 1 shows the shares of employment of each major sector during 2007 and 2014, along with the average hourly wage.

Source: Bureau of Labor Statistics and author’s calculations

If the average hourly wage is used as a proxy for productivity within an industry, the shift in 2007-2014 composition would imply a reduction in average productivity of 1.1 percent in total, or a bit less than 0.2 percentage points annually. Clearly, this composition shift is not the main source of the productivity slowdown. But in the context of annual productivity growth in the neighborhood of one percent, a decline of 0.2 percentage points due to changing industry composition is worth noting.

At this point, it is not possible to determine the extent to which this shift would be sustained, even in a stronger labor market. But it is reasonable to assume that the rapid relative growth of low-wage sectors is at least in part attributable to lack of employment opportunities in higher-paying sectors. 10 This would imply that a stronger labor market would at least partially reverse the extent to which the changing composition of employment has been a drag on productivity growth. 

Conclusion

It is clear that the continuing weakness of the economy stems to a substantial extent from inadequate demand. There currently is no source of demand to fully replace the demand that was generated by the housing bubble before the recession. It is not clear how far the economy remains below its potential level of output, but few economists dispute that there still is substantial room for increased demand to boost output.

A major complication is that a longer period of below-full-employment output reduces potential GDP. This is, in part, due to the fact that lower levels of output are associated with lower levels of investment, which implies a smaller capital stock and lower potential GDP. There also is the concern that workers who remain outside the labor force may end up unemployable as they lose work-related skills. For this reason, a lengthy period of high unemployment may reduce the size of the potential labor force.

Apart from the demand-side problems, there also are important supply-side issues facing the economy. The rate of productivity growth has slowed markedly from its 1995-2007 pace. There is no simple way to determine the extent to which this slowdown is cyclical or structural. The productivity-enhancing potential of many innovations that allowed for large increases in 1995-2007 productivity has eroded as these innovations have been widely adopted. Nonetheless, it is possible to identify many technologies that seem to offer possibility for large gains in the not-distant future.

Higher levels of demand in the economy likely will provide a productivity boost as firms look to increase output and, presumably, also increase investment. They also will feel more need to economize on labor if workers start finding themselves with many job options. In addition, in a tighter labor market, the composition effect should go in the opposite direction we have seen since the downturn. Workers will leave lowest-paying and least-productive jobs, and will move into sectors with higher productivity. Until we see levels of demand that are sufficient to reach the economy’s potential, we will not know for certain whether these effects will be large enough to restore most or all of the falloff in productivity growth since the downturn.  

About the Author
Dean Baker is co-director and co-founder of the Center for Economic and Policy Research in Washington, D.C. He received his B.A. from Swarthmore College and his Ph.D. in Economics from the University of Michigan.

Footnotes

  1. Gordon, Robert. 2015. “Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds,” National Bureau of Economic Research Working Paper # 18315, available at http://www.nber.org/papers/w18315.
  2. Calculation based on data in the Bureau of Economic Analysis, National Income and Product Accounts, Table 1.1.5.
  3. Congressional Budget Office, “Economic Data and Projections: January 2015 Baseline, Table 26”.
  4. Bureau of Labor Statistics data portal, available at http://www.bls.gov/data/#employment.
  5. Projections for 2008 assume the same difference in the growth rate of potential GDP from 2018 persists for the later years after the 2008 projection period ends.
  6. It is not generally recognized, but there also was a bubble in nonresidential construction before the recession. Nonresidential construction rose from an average of 2.5 percent of GDP 2003-2005 to 3.8 percent of GDP at its peak during third-quarter 2008. This increase in shares of 1.3 percentage points (more than 50 percent) was in response to a surge in prices for nonresidential structures. The building boom led to considerable overbuilding and a spike in vacancy rates for most categories of nonresidential structures.
  7. Herndon, Thomas, Michael Ash, and Robert Pollin. “Does High Public Debt Consistently Stifle Economic Growth: A Critique of Reihnart-Rogoff,” Political Economy Research Institute, University of Massachusetts, Amherst, Working Paper #322.
  8. Data from Bureau of Labor Statistics data portal for productivity in the non-farm business sector, accessed May 26, 2015, available at http://data.bls.gov/cgi-bin/dsrv?mp
  9. It is worth noting that productivity gains often are assigned to the wrong industry. The growth of just-in-time deliveries, where trucks are expected to show up at factory gates just as the material is needed—instead of unloading and keeping the goods stored at the factory—would show up as an increase in productivity for the manufacturing sector. Conversely, it might appear as a decline in productivity for the trucking sector, since the premium placed on being at the factory at the necessary time might mean that the trucker spends extra hours waiting at a loading dock to reduce the risk of being late. There are many other such situations where one industry is able to increase its productivity by imposing additional burdens on its customers or suppliers.
  10. A simple test showed a strong positive relationship between state unemployment rates and the percentage of job creation attributable to the restaurant sector, available at http://www.cepr.net/blogs/beat-the-press/

What’s Going on With Growth And Dynamism in the United States?

By Robert B. Cohen, Ph.D. Senior Fellow, Economic Strategy Institute
Robert B. Cohen, Ph.D.
Robert B. Cohen, Ph.D.

Executive Summary 

The U.S. economy’s current state reflects a long and tedious path to recovery. Growth has restarted, and unemployment has dropped significantly. Corporate profits have recovered, although new investments have been modest. The extended upswing came after one of the most daunting and disastrous recessions of the twenty-first century. While measures to reverse the decline cut unemployment and resulted in modest growth, investment has been slow to recover, and consumer spending is only beginning to show signs of life.

The first part of this review suggests that the recovery is likely to continue, and that some sectors, such as housing, could provide a short-term boost for the rebound. The second part of this paper argues that an important, but unexpected, source of growth is likely to come from innovation related to Internet technologies, and in the management of new infrastructure based on innovations that have emerged during the past few years. Many analysts are convinced that the consequences of artificial intelligence (AI), and automation discussed in the The Second Machine Age will impact job growth.

This part of the paper suggests that progress in technologies linked to the Internet and infrastructure produce very different outcomes than advances in automation and AI. Although advances in computing and software are likely to displace jobs that played a role in traditional information technology during the past two decades, there is a second, parallel path in technology and innovation that contains a story The Second Machine Age does not tell.

This second path is based on advances in the Internet that have reshaped computing, storage, and networking. These innovations are built on cloud computing, and the virtualization of machines and networks, i.e., the use of software to manage hardware in new and more efficient ways. The evidence in this part of the paper suggests that virtualization of devices (computers and switches) already has begun to transform the way businesses use computing and networking infrastructure. Netflix, Twitter, Walmart, Bank of America, Facebook, Gap, and other firms already are speeding and refining the creation of new services for customers.

While these new developments in the economy are not very visible in economic data, a number of observers, including Enrico Moretti from Berkeley and Cesar Hidalgo from Massachusetts Institute of Technology, have argued as I do here that we are on the way to creating a knowledge economy. This part of the essay argues that Internet and infrastructure innovations will create a large part of the new knowledge economy. Enterprises are rapidly implementing these innovations. I expect they could appear in productivity and growth figures quite soon, much to the surprise of many economists and forecasters.

A View of the U.S. Economy and Dynamism

There are divergent views about where the U.S. economy is going. The view I hold is that the economy is recovering slowly, but gradually, from a rather disastrous financial crisis spurred by a major collapse in the housing market. That implies that the economy is still very fragile and vulnerable to unforeseen crises, such as a Chinese economic slowdown, a Greek default, or a credit crisis due to something like a failure of the United States to pay its debt due to Congressional inaction. The crisis of 2007–2008 had many similarities to the 1929 crash, with the collapse of “unsinkable” institutions such as Lehman Brothers and the U.S. housing agencies. Its severity—at 18 months, longer than any since World War II—made the recovery far more difficult.

A more conservative view of the U.S. economy is that the country’s debt must be reduced, and the budget must be balanced to promote growth. This view has dominated Europe’s response to the recession. U.S. efforts, which stand in stark contrast to Europe’s, represent a more traditional Keynesian approach—namely, a sizable stimulus during the early stages of the downturn, as well as Federal Reserve policies to promote lending and consumption

Another view,1 espoused by Professor Robert Gordon, is that the economy has headed into such strong “headwinds” that the potential for future growth is very limited. In this view, a lack of innovation will curtail both productivity growth and consumption. In this scenario, U.S. gross domestic product (GDP) will fall to about 1 percent during the coming decades, and productivity growth will be almost nonexistent for perhaps the next 100 years—similar to what it was during the Victorian Age.

Let’s look at some of the data. First, what has been happening with GDP? Instead of accelerating to a 2.5 percent to 3 percent growth rate as in other, shorter recoveries, growth has been sluggish. One way to characterize the recovery is that it was “jobless” until the past year, when new jobs grew at nearly 300,000 a month. But, in December 2009, three years after the recession started, employment was still 4.5 percent below what it was at its peak; no other post-1946 downturn was so severe (see Table 1). This occurred in spite of a substantial economic stimulus at the beginning of the Obama Administration (see the chart below for government spending—in green—as well as GDP growth during the recovery period.)


Gerald P. Dwyer James R. Lothian, “The Financial Crisis and Recovery: Why so Slow?” Federal Reserve Bank of Atlanta, Center for Financial Innovation and Stability, (September/October 2011).

Structural Changes in the Economy

So what is happening to the economy? Among economists, there is general agreement that there was a period in the late 1990s and early 2000s when productivity rose to nearly twice the 1.5 percent year-to-year rate of the 1970s and 1980s. There was hope that the economy might begin to grow more than modestly.

I plan to address this growth question later in looking at innovation. But first, I’d like to explore the economy’s health and recovery from one of the worst downturns in recent history.

The State of the U.S. Economy during 2015

Let’s look at some of the main indicators for the economy to see how they are doing. As we saw from the chart above, the recovery has been quite slow compared to other downturns, possibly because the recession was so closely linked to the financial services sector and was preceded by a large decline in housing values. The former squeezed lending to businesses, while the latter dramatically cut consumer spending.2

To facilitate the recovery, the Federal Reserve adopted a policy of “quantitative easing,”3 in which it actively purchased government bonds. While this had the aim of promoting lending, it actually created far more stability in the bond markets, while interest rates also dropped to their lowest points in years. The creation of this stability in the bond markets did much to speed the recovery. Consumer spending accounts for about 70 percent of GDP growth, so its recovery is entwined with overall economic health. As is clear from the figure below, consumer spending has rebounded nicely. This is one factor helping GDP growth recover.

The identity for GDP is that GDP = C + I + G + Net Exports, where C is consumption spending, I is investment, and G is government spending. As can be seen from the first graph above, government spending rose during the recession as part of the stimulus program, a Keynesian effort to promote growth. According to Keynes, government spending is a key way to reverse the economic effects of a downturn. In contrast to Keynes, many conservatives argue that tightening government spending would promote growth by reducing taxes and lowering debt. Governments in the UK, Germany, and Europe adopted this policy soon after the crisis, but it now has been reversed.

Source: http://www.numbernomics.com (May 29, 2015)

Although we identified overall patterns of investment in the first figure above, both investment and consumer spending had a difficult time during first quarter 2015. The decline—as well as the decline in overall GDP of 0.7 percent during the first quarter—was due to the sharp downturn in oil prices and a subsequent drop in investment in structures that include oil drilling and wells. This latter component fell 21 percent during first quarter 2015.

Source: http://www.numbernomics.com (May 29, 2015)

On the trade side, the United States has been doing well after the recession. But the recent increase in the value of the dollar has made imports cheaper and U.S. exports more expensive overseas. One consequence of this was that GDP growth was 1.9 percent less during first quarter 2015 due to the increase in imports. The euro was one key currency that fell in value relative to the dollar, dropping from $1.32 at this time last year to $1.09 May–July 2015. This made U.S. imports more expensive in Europe and U.S. imports from Europe less expensive. This is one reason why the U.S. trade deficit has increased and growth has slowed.

Source: http://www.numbernomics.com (May 29, 2015)

Source: http://www.x-rates.com

Somewhat compensating for these negative impacts on the economy, the housing market has been on fire in recent months. Household formation (people purchasing their first houses) has only recently risen above the trend line of the past fifteen years. In part, this is due to the long period of low household formation following the 2007 crisis, but also is due to continuing low mortgage interest rates.

Source: http://www.numbernomics.com

Growth, and the Productivity and Employment Debate in the United States
Several writers have argued that U.S. growth will remain rather modest—at 2 or 2.5 percent per year due to a lack of improvement in productivity. One common view4 is that the U.S. economy has entered a stage in which investment has slowed and, without a surge in new investment—capital and “software” now defined as capital—productivity growth will remain low, and overall economic growth will slow.

The following chart shows that, with a few exceptions during the early 2000s, productivity growth for the United States has been roughly 1.5 percent for the past fifty years. One factor that has slowed growth has been the fall of capital investment, which is shown in the next chart.

Source: Andrew Smithers, “U.S. Labor Productivity: Key to Lasting Growth” 

Investment slowed after the recent crisis. It fell below the long-term, post-World War II trend line of 22 percent of GDP. The slowdown is more apparent in the second chart, which shows net additions to the U.S. capital stock as a percentage of GDP. After the recent financial crisis, this share has dropped below the trend line of 3.3 percent.


Source: Andrew Smithers, “U.S. Labor Productivity: Key to Lasting Growth” 

There is another debate that is influencing thinking about productivity growth. Using evidence based on a study of the likely economic impact of automation and “thinking machines,” Erik Brynjolfson and Andrew McAfee have argued in The Second Machine Age that “computers and other digital advances are doing for mental power – what the steam engine and its descendants did for physical power.” Reinforcing this analysis, quantitative modeling described in The Future of Employment, by Carl Frey and Michael Osborne at Oxford University, uses a ranking of occupational characteristics to determine how vulnerable specific jobs are to automation during the next twenty years. Frey and Osborne’s main conclusion is that only the most creative and labor-intensive jobs at the extremes of the job scale are likely to survive the trend to automation. The U-shaped chart below was developed from the Frey and Osborne data.

In their analysis of U.S. employment, Frey and Osborne find that “47 percent of total U.S. employment is in the high-risk category, meaning that associated occupations are potentially ripe for automation during some unspecified number of years, perhaps a decade or two.” They postulate two “waves” of automation, with the first affecting “most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations. Those jobs likely are to be substituted by computer capital” [p. 38]. In the second wave, after a technological plateau, jobs in “services, sales and construction occupations” [p. 38] are automated.

Source: Carl Benedikt Frey and Michael A. Osborne, “The Future of Employment: How Susceptible Are Jobs to Computerisation?” Oxford Martin School, Programme on the Impacts of Future Technology (September 17, 2013). Also cited is John McDermott, “Is your job safe in the second machine age?”  (Feb 10 2014).

Furthermore, Frey and Osborne argue that, during the coming decades, even non-routine jobs will be automated. The main constraint on automation will be if the positions require “fine arts,” “originality,” “negotiation,” “persuasion,” “social perceptiveness,” and “assisting and caring for others.” Jobs with these variables all exhibit relatively high values in the low-risk category [p. 40], which means they are likely to survive.

“By contrast, we note that the ‘manual dexterity,’ ‘finger dexterity,’ and ‘cramped work space’ variables take relatively low values [in the low-risk category]. Hence, in short, generalist occupations requiring knowledge of human heuristics, and specialist occupations involving the development of novel ideas and artifacts, are the least susceptible to computerization” [p.42].

A similar concern about productivity growth has led Robert Gordon5 of Northwestern to argue that “innovation does not have the same potential to create growth in the future as in the past.” [p. 11]. Gordon’s key thesis about innovation and the Internet is:

“The computer and Internet revolution began around 1960, and reached its climax in the dot-com era of the late 1990s. But its main impact on productivity has withered away in the past eight years. Many of the inventions that replaced tedious and repetitive clerical labour with computers happened a long time ago, in the 1970s and 1980s. Invention since 2000 has centered on entertainment and communication devices that are smaller, smarter, and more capable, but do not fundamentally change labor productivity or the standard of living in the way that electric light, motor cars, or indoor plumbing changed it” [emphasis added].

Gordon expects that, when successful innovation occurs, it will be discrete and very similar to successful innovation during the nineteenth-century industrial revolution. This was true of electricity and machine power. He argues that “it is useful to think of the innovative process as a series of discrete inventions followed by incremental improvements, which ultimately tap the full potential of the initial invention. For the first two industrial revolutions, the incremental follow-up process lasted at least 100 years” [p. 2]. Lacking evidence for any innovation of this type during the twentieth century,6 he expects that the economy will be unable to regain much dynamism during the coming two to three decades, and probably longer. In his view, growth could fall to just 0.2 percent in 2100, as shown in Figure 2 below. This implies almost no productivity growth whatsoever by that time.

Source: Robert J. Gordon, “Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds,” p. 4

Is there another way to think about the outlook for productivity, growth, and jobs? There may be.

Since we are entering a services-oriented world, it’s possible that innovation will not be discrete, as Gordon argues it should be. If the Internet and networking benefits proposed here are not discrete, but occur in a “software and services chain,” important benefits may occur as new innovations improve the chain, and are used to create new services. In the next section, we explore data about the growth of “unicorns,” Internet-connected firms that rapidly reach a $1 billion valuation. This data begins to suggest that today’s situation may require new thinking about how innovation occurs and what needs to be measured.

Innovation in the U.S. economy
I would like to argue that innovation in software—particularly software that runs computing and networking in large enterprises, and that constitutes the infrastructure for firms such as Facebook and Twitter—is establishing a base for substantial new growth. This provides a dramatic contrast to the analysis of artificial intelligence, which is one part of the story of emerging technology and innovation.

The fundamental case I put forward is that enterprises are only now shifting from the initial efforts they have made to put much of their computing activity into the cloud. They are undertaking far more substantial transformations for several reasons:

  1. The Internet of Things is being implemented much more rapidly in the auto industry due to the introduction of driverless car technology. Without human intervention, you already can call a BMW from a spot in a parking lot using “valet assistant” and have it drive to the entry to pick you up. Mercedes has a “stop and go” autopilot, and Cadillacs soon will have an autopilot that manages lane changes. This effort will help similar initiatives, which are changing health care delivery and retailing.
  2. Pressed by the need to include mobile devices in the way they operate, and to connect with consumers, corporations are ripping out their old infrastructure. They are introducing a type of agile “chained software” to create new services and applications faster than was previously possible. With 70 percent of all purchases coming from mobile devices, Facebook, Twitter and others, firms such as Walmart must be agile, or they will lose out to more innovative and nimble competitors. The old infrastructure will not meet such new demands. So twenty-first century firms are ripping out their traditional infrastructure and replacing it with software-defined and “chained infrastructure”—virtualizing7 not only computing, but also networking—that creates new types of pipelines for continuous service delivery.
  3. New networking technologies are solving the problem of how to function in a 24-hour-a-day world. This is a shift to a global view that many scholars have not appreciated. It also has been facilitated by technologies derived from the Internet. This change is essential for financial, logistical, and transportation firms. Once they adopt it, other firms are likely to follow.

In sum, these changes are likely to revitalize a number of firms and alter their business models.

They also will create a shareable, often “open source,” software that is published on easily accessible websites, such as GitHub. In essence, innovations that larger firms initiate can provide the foundation for smaller, innovative firms. Subsequently, this can open the way for entirely new industries to develop, including the mobile financial technology firms I mention below.

To offer more information about the types of innovations that are the basis for these changes, I have created the chart below to identify the main innovations in different aspects of the Internet and enterprise computing, storage, and networking.

I also have drawn upon studies to illustrate the early economic benefits associated with such changes. This information is provided in the following chart:


I think these innovations will serve as fundamental building blocks for the knowledge economy, creating entirely new areas for economic activity. From recent investments by venture firms, we can identify a number of “emerging” growth sectors. Writers, including Cesar Hidalgo in Why Information Grows? and Enrico Moretti in The New Geography of Jobs, have espoused views very similar to my own.

If we are on the verge of a big shift in innovation, it is possible that traditional measurements have been unable to decipher what is actually happening. Several analysts have argued that young firms are declining in importance to the U.S. economy. One study that compiles data showing this trend is by Decker and others.

Source: Ryan Decker, John Haltiwanger, Ron Jarmin, Javier Miranda, “The Role of Entrepreneurship in U.S. Job Creation and Economic Dynamism,” Journal of Economic Perspectives, Vol. 28, Number 3, pp. 3–24 (Summer 2014).

Katherine Kobe8 finds a similar decline in the share of GDP produced by small business 2002–2010, but finds that “small businesses continue to be incubators for innovation and employment growth during the current recovery. Small businesses produced 46 percent of the private non-farm gross domestic product (GDP) during 2008 (the most recent year for which source data are available to make these estimates). That is down from the 48 percent share of GDP produced by small businesses during 2002. Preliminary information indicates that the weak business conditions through early 2009 affected small businesses about as much as large businesses, resulting in only a minor change to the shares.” While acknowledging a decline in the small business contribution during 2010, she finds that small businesses held their own for much of the recovery, although large firms recovered more successfully, as shown in the figure below.

Source: Kathryn Kobe, “Small Business GDP: Update 2002-2010,” Economic Consulting Services, LLC, Washington, DC, prepared for the Office of Advocacy, United States Small Business Administration, p.15 (January 2012).

What might suggest that innovation is making more positive contributions to the economy? I would argue that venture capitalists’ recent funding for new businesses identifies a vibrant core of new firms in some key sectors. Quite a number of these firms are connected to the growth of infrastructure and the Internet.

Venture capitalists have named firms that rapidly attain a valuation of $1 billion or more “unicorns.”9 The explosive growth of unicorns may say more about innovation and growth than do the aggregate statistics presented above. Research from CB Insights indicates that the pace of unicorn creation is ramping up rapidly during 2015, likely to double the 2014 pace.

Source: https://cbi-blog.s3.amazonaws.com

CB Insights also provides data about investments in emerging industries. A good example is mobile financial technology. In this sector, funding has supported more than twenty firms each quarter during the past three years, with investments almost twice the size during second quarter 2015 compared with three years earlier.

Source: CB Insights, “The Mobile Fin Tech Landscape,”  (May 28, 2015).

In a similar manner, CB Insights notes that investment in on-demand firms such as Uber is quite strong. These firms are Internet-based, largely implementing new techniques to develop software, such as Microservices,10 and able to keep up with spikes in demand while creating innovative new services. Although this area is dominated by Uber, which raised 39 percent more funding during 2014 than all other on-demand startups combined, it is still interesting to see the rate at which funds have focused on startups in this area.

In addition, the accompanying figure on funding for on-demand startups shows that they are maturing and receiving funds in follow-on rounds beyond the initial round of angel/seed funding. The shift in later-round funding 2010–2014 illustrates this trend.


Source: “The On-Demand Mobile Industry in Nine Charts


Conclusions

While the U.S. economy appears to be recovering well, it has taken a while to get to a more dynamic state. Unemployment remained high long into the recession, and business profits did not recover until recently.

There is an open question about what happens next. Some economists believe that automation will destroy a large number of jobs during the next two decades. Others are concerned that sluggish productivity gains will dampen growth and result in a return to an economy similar to that of the Victorian era, with few productivity gains and very modest growth.

I have suggested that there is a dynamic group of firms that already is exploiting new Internet and networking technologies to operate in far more dynamic ways than its competitors are. This trend is apparent in many of the more infrastructure-oriented firms that are “early adopters” of the technologies I mentioned above.

In addition, another group of startup firms is exploiting many of the same technologies to build new markets and create new services in industries such as finance. These firms, the most successful examples of which are called “unicorns”—firms that have attracted $1 billion in financing very rapidly—have potential to change investment patterns as well as productivity growth.

These two types of firms, rapidly adjusting older firms and highly innovative new ones, indicate that a brighter future for innovation and growth in the U.S. economy is a possibility. For it to come to pass, there would have to be more evidence that firms in emerging industries will attract large new investments. If this happens, it could raise investment trends above the levels in the data presented here. It also probably would contribute to a rise in productivity.

As the U.S. economy becomes more service-oriented, U.S. government statisticians may need to develop better tools to measure what is happening. One reason to do this is that innovations in services may not be as discrete as they were during the industrial revolution, when electricity and machine power were new. Rather, there may be incremental but significant innovations that we do not yet know how to measure very well.

If we can move productivity estimates higher based on the emerging industries of the Internet, I think we can revise Gordon’s forecast to be more optimistic.

About the Author
Robert B. Cohen, is a senior fellow at the Economic Strategy Institute. Dr. Cohen has been the Director of the Enterprise Cloud Leadership Council of the TM Forum. He has worked for the European Commission’s Directorate General XIII and served as chair of New York’s High Tech Council. He holds an MA and Ph.D. in economics from the New School for Social Research and a BA from Swarthmore. He is the author, co-author or co-editor of five books.

Footnotes

  1. Gordon, Robert J. “Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds.” www.cepr.org.
  2. Using data from the Florida Department of Taxation, I tracked consumption of consumer products during the months following the collapse of housing prices within several counties that were the focus of the state’s housing crisis. This data shows a rather dramatic decline in consumption spending within a few months of significant declines in housing prices.
  3. Blinder, Alan S. “Quantitative Easing: Entrance and Exit Strategies.” Federal Reserve Bank of St. Louis Review, pp. 465–480, (November/December 2010).
  4. Smithers, Andrew. “U.S. Labor Productivity: Key to Lasting Growth.” 
  5. Gordon, Robert J. “Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds,” Centre for Economic Policy Research, CEPR Policy Insight No. 63 (September 2012).
  6. I provide a counter view that cites a number of examples of innovation in the Internet-related economy in a paper, “A Software-Defined Economy: Innovation, the Internet and Future Growth,” Columbia University CITI Conference on Internet and Employment (June 5, 2015).
  7. See Intel IT Center, “Virtualization and Cloud Computing.” (August 2013).
  8. Kobe, Kathryn. “Small Business GDP: Update 2002–2010,” Economic Consulting Services, LLC, Washington, DC, prepared for the Office of Advocacy, United States Small Business Administration, p.3 (January 2012).
  9. CB Insights, “Unicorns Are Breeding Like Rabbits: Set to Double 2014′s Record Pace.” (May 21, 2015).
  10. Cockcroft, Adrian. “Creating Business Value with Cloud Infrastructure.” Open Networking Users Group conference, May 13–14. 

Session Summary:


New Entrepreneurial Growth Conference Debate on the proposition: The best is yet to come

As the foregoing essays demonstrate, there is considerable disagreement and uncertainty about the fate of the U.S. economy over the next few decades. At the conference, participants engaged in an Oxford-style debate on a straightforward proposition: “The best is yet to come.” Two panelists were charged with arguing for the proposition, and two were charged with disagreeing. The larger conversation that followed included discussion of historical patterns, technological determinism, and the role of public policy in determining our future.

The weight of history. Both sides cited history as evidence, suggesting that how we view our history and the narrative we tell is an important part of how we perceive our present and future. Those who argued the optimistic case—that the best is yet to come—pointed to the continuation of positive trends. They looked forward to continuing improvements and innovations, including the democratization of health care, better work-life balance, and a stronger safety net that is separate from employment. Peer-to-peer economies, the Internet of Things, exciting new technologies, and the emerging digital economy that offers the potential to disrupt traditionally stable industries also were mentioned. These changes will perpetuate broad historical trends of greater opportunity and equality.

One participant explained that we are seeing greater inclusivity that improves our capacity to use new products and services. While innovation in the past was limited to a few specific individuals (such as those who invented the phone, or the automobile, or the airplane, for example), innovation today is more broad-based. No single person is responsible for the invention of the personal computer or the Internet, even if some individuals are more celebrated than others.

A brief debate regarding education ended largely in favor of the proposition. One participant noted that educational attainment rates have leveled off, but they are at their highest levels ever. We hear a great deal about falling behind internationally, he said, but actually we’ve maintained the same level while other countries have increased faster. We’re in the century of human capital, and we’ve seen improvements in our ability to build human capital that bode well for the future. While one participant argued that we already have realized the gains to education, others said that just because the college revolution is behind us doesn’t mean that gains from an increase in human development are also behind us.

Those in favor of the proposition also said that markets are working internationally much better than before, promising that the best is yet to come for the world, which will benefit the United States, too. Globally, more people have come out of poverty in recent decades. While some acknowledged that the rate of improvements in some areas has slowed, they maintained that our state has not become worse over time. They allowed that there are some disappointing historical trends, such as the diminution in U.S. productivity and increasing inequality, but they argued that these trends aren’t a reason for pessimism. History, they said, rarely proceeds in a linear fashion.

Those arguing against the proposition also cited historical evidence, arguing that the 1950s and 1960s were the pinnacle of growth and prosperity in the United States (although not, they acknowledged, for racial and gender equality), and that it has been downhill since. The middle five decades of the twentieth century, from the 1930s through the 1970s, were when innovation created the biggest growth in total factor productivity. The late 1990s saw a sudden, surprising jump in productivity, which a contributor attributed to the boom in dot-com, Internet-related capital investment. But productivity growth, he said, has largely slumped since the 1970s and has slowed in stages since 1999. We have seen a decline in business dynamism, a decrease in investment in capital, a declining rate of net investment, a decline in labor market fluidity, and a collapse in manufacturing capacity growth. Furthermore, the innovation we are seeing today is more incremental or evolutionary than revolutionary, and inequality is worse today.

While we have seen many important innovations in business practices in the last forty years, and we may see exciting new technologies in the future, participants opposed to the proposition suggested that we won’t achieve this kind of peace and prosperity again, and new technologies may bring increased risk. We now face terrorism and cyber-security concerns that could become only direr with the advent of more chemical and biological weapons. Changes in family structure, including an increase in families with single parents, are contributing to an ongoing decline in social mobility and an increase in inequality. Climate change has resulted in natural disasters that become worse each year, and we are not taking sufficient action to mitigate the environmental damage we incur or to insure against the risks it poses. Businesses face greater challenges from more severe competition within the American market and from international markets. And, finally, one contributor suggested that the challenge of ongoing growth increases keeps getting bigger. An increase in the percent change of growth over time requires ever-bigger performance, requiring more growth to generate it, to the point that it is hard to manage in a sustainable way.

The reasons for the strong growth and prosperity we experienced after World War II were discussed at some length. One participant explained that the physical destruction and loss of lives in Europe after the flu epidemic and the two world wars created this exceptional era for the United States in the 1950s and 1960s, as our economy could move ahead while other countries were struggling to recover. While Europe was distracted by the world wars, the United States enjoyed a peacetime economy by 1950, and we had already put into mass production inventions with European origins that couldn’t be implemented in Europe due to the post-war chaos. While one participant suggested that the reason for the slowdown in productivity growth since the 1970s is that we ran through these great accomplishments from the earlier period, others argued that this period was an anomaly and so cannot be used as a comparative baseline.

Another contributor responded that U.S. prosperity in the 1950s and 1960s was due as much to U.S. policy as it was to events in Europe. In addition to avoiding the chaos of war, we had policy decisions that were inspired by the Great Depression—specifically, the series of competition policy decisions between 1912 and the late 1960s that supported the healthy economy we saw during that time, including the Sherman Antitrust Act, the Clayton Antitrust Act, and other efforts to outlaw price discrimination and create an environment of healthy competition. A 1965 Supreme Court case ruling against monopolies further supported this environment. These policy decisions, the participant said, were largely responsible for the unprecedented growth we experienced during that time.

Policy decisions may help explain why the distribution during that time period was more equal than it is today. Participants explained that policies regarding labor unions, the minimum wage, the lack of imports, and the lack of immigration all contributed to greater economic equality. The decline in this economic equality, participants suggested, is partly due to globalization, immigration, and the erosion of unions and minimum wage in the United States. We have made policy decisions since the 1960s that have worked against inequality, in part because they were predicated on inflated ideas of how well off our children would be today. As policymakers since the 1960s assumed we would have made even more progress by this time, they created policies that don’t give us the support we now need. After the 1960s, in fact, life became tougher for ordinary people than experts promised. People made decisions about having children and purchasing houses based on the belief that their wages would improve, but the modest rate of productivity growth we have experienced hasn’t been shared equally with the middle class.

Technological determinism and the power of policy. Many participants agreed that society can choose how to use and regulate technology. Public policy, they said, has the power to determine our future and make positive changes; technology changes aren’t deterministic. The central disagreement between the two sides, however, hinged on participants’ confidence in our society’s ability to create the policy we need to achieve a brighter future. Those who disagreed with the “best is yet to come” proposition believed that we don’t have the political will to change our policies; that political polarization, apathy, and the media environment make it difficult to make good policy, or that human nature is fundamentally opposed to making the necessary changes. A participant opposed to the proposition explained that there is no reason to expect a fundamental change in human psychology or human politics that will allow us to get better at identifying problems and resolving them. And the problems we face, they said, are only getting more difficult as technology brings us more risks, more quickly, with more complexity, and in a more interconnected environment. Indeed, one person suggested, it’s human nature to believe that technology will bring us something better, but not to see the risks. We never anticipated the cyber-security risks we now face, for example, and the government has not sufficiently addressed them.

In contrast, those in agreement with the proposition believed that we can step up to make the changes we need. While some of them acknowledged that our current regulations are artifacts from a past economy and are creating rigidities in our market, they had confidence in our ability to challenge these structural rigidities – to adapt to our new, more global, interconnected environment, decide what kind of future we want, establish specific and well-articulated goals, and use policy once again to create that future. The key to success, they cautioned, is that policy can help us only if we think carefully about the future we want in order to make it happen. Focusing on achieving unprecedented economic growth, increased entrepreneurship, or outstanding innovation may be too limited, as improvements in technology alone, for example, may not improve our national employment picture or the quality of human life. Technology, innovation, and entrepreneurship, the participant pointed out, are not ends in themselves, nor should they be means simply to acquire vast wealth. Rather, they represent opportunities to achieve greater prosperity, increase the quality of life, lessen human suffering, and help people reach their potential throughout the economy. If we are thoughtful about what we actually want and make sure that we are creating the incentives that will get us to that end, we can design policy to achieve these things and to help us endure the wars, epidemics, and other disasters we may face in the future. We cannot hope for greater prosperity and equality, the participant emphasized, while creating incentives that work against these goals.