Automation and New Tasks

February 22, 2019

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Daron Acemoglu and Pascual Restrepo, “Automation and New Tasks: The Implications of the Task Content of Production for Labor Demand.” Prepared for Journal of Economic Perspectives, November 6, 2018.

This paper really helped me think more systematically about the impact of automation on the demand for labor, something I’ve been thinking a lot about lately. My last post on the subject, which also featured a paper by Acemoglu and Restrepo, is here.

Technology and labor demand

One of the key issues is how to reconcile the recent concern that robotics will destroy too many good jobs with the traditional optimism of economists about the effects of technology. Throughout most of U.S. history, new technologies like farm machinery or industrial assembly lines have not stood in the way of economy-wide gains in labor demand, as reflected in real wages per capita. And yet, too many workers today are experiencing unemployment or wage loss because of automation. How do we sort this out in a way that enables us to anticipate where we may be headed and formulate sensible policy responses?

Acemoglu and Restrepo conceptualize the labor demand of an industry as a product of “value added” and “labor share”:

Labor demand = Value added x Labor share

Value added is an industry’s addition to economic output and income. Labor share is the portion of that added value that is received by labor. Labor demand is the resulting wages per capita.

The authors say that economists have primarily conceptualized technological progress as “factor-augmenting.” That is, new technologies increase the productivity of labor or machinery or both. More productive factors of production mean more value added. Assuming that labor’s share doesn’t decline, labor demand as reflected in real wages ought to increase. “Factor augmenting technologies affect labor demand mostly via the productivity effect and have a small impact on the labor share of an industry.” That was the experience, for example, of manufacturing industries in the mid-20th century.

However, an analysis that focuses on value added while holding labor share constant is not complete. Technological change can also effect how much labor is needed in a particular process of production, and how much of the income from that process goes to workers.

The task content of production

The authors’ key concept is the task content of production, which involves the allocation of tasks between labor and capital (the latter including machines and software). Focusing on the potential of new technologies to add value “often misses the major implications of technological changes that directly alter the allocation of tasks to factors.”

What makes the implications of automation hard to assess is that it has contradictory effects on labor demand–a productivity effect and a displacement effect. By raising productivity and increasing value added, it increases the potential income to be distributed to the human workers who remain. But by replacing labor with machinery, it reduces labor’s share of income. Whether wages actually rise or fall depends on the relative strength of the two effects.

To complicate things further, displaced labor does not necessarily go missing from an industry, let alone the economy as a whole. The introduction of new tasks for humans to do has a reinstatement effect that raises the labor share of production and therefore labor demand. (Personally, I’m not too fond of the term “reinstatement”, since it sounds as if workers are getting their old jobs back, which is not at all what is intended. I would prefer the term “redeployment”.) But whatever term is used, the point is important. As machines take over familiar tasks, humans can move into new economic activities where they have some advantage over machines, especially because of their general intelligence, flexibility and creativity. This has been true in the past, and how much it remains true in the robotic age is an important question for the future of work.

Labor demand in a multi-sector economy

When the authors move from discussing individual industries to discussing the entire economy, they introduce an additional effect on labor demand, the composition effect. This occurs when labor moves from one economic sector to another, and the sectors differ in labor demand. If workers move out of a sector where wages and labor’s share of added value are falling, and into a sector where they are higher, that contributes positively to labor demand.

The classic example of this process is the mechanization of agriculture, “which started in the first half of the 19th century with the cotton gin and continued with horse-powered reapers, harvesters and plows later in the century and with tractors and combine harvesters in the 20th century.” That process displaced massive amounts of farm labor and reduced labor’s share of agricultural activity and income. Much of that displaced labor went into manufacturing. Manufacturing was mechanizing too, but it maintained labor demand by increasing output and creating new manufacturing tasks. “The composition and reinstatement effects explain why, despite the mechanization of a sector making up a third of the economy [agriculture in 1850], labor demand increased and the share of labor in national income remained stable during this period.”

Labor demand 1947-1987

For two recent periods, Acemoglu and Restrepo analyze changes in labor demand, measuring the relative contributions of the effects they have discussed. They chart developments in six industries: agriculture, mining, manufacturing, construction, transportation and services.

The postwar era of 1947-1987 was a period of strong labor demand and rising real wages, which grew at an average rate of 2.4% per year.

Nothing comparable to the displacement of labor by the mechanization of agriculture occurred during this time. The only industries to suffer a loss of labor share were the relatively small industries of mining and transportation.

There was some displacement of labor due to automation in the large manufacturing industry, but it was offset by the creation of new manufacturing jobs, such as managerial and clerical jobs in corporate bureaucracies, as well as jobs in the expanding service industries. “[T]here was plenty of automation, especially in manufacturing, but this was accompanied with the introduction of new tasks (or other changes increasing the task content of production in favor of labor) in both manufacturing and the rest of the economy that offset the adverse labor demand consequences of automation.”

With displacements due to automation balanced by reinstatements due to the creation of new tasks, labor’s share of output and income remained steady. The increase in actual real wages that occurred is accounted for almost entirely by the other effect that supports labor demand, higher productivity. New technologies added value, and labor got its share of that added value in the form of higher real wages.

If technological change always worked that way, we wouldn’t be so worried about the future. But there was trouble ahead. In their data for those years, we can already see labor’s share within manufacturing peaking around 1980 and starting downward.

Labor demand 1987-2017

In this more recent period, wage growth was slower, averaging only 1.3% per year.

Labor demand suffered in both ways suggested by the same formula:

Labor demand = Value added x Labor share

Value added increased more slowly because of slower growth in productivity. In addition, labor’s share of value added declined in manufacturing, construction and mining. That was because labor displacement due to automation accelerated, while labor reinstatement due to new task creation slowed down.

Deeper explanations for these trends are harder to agree on. One puzzle is why the accelerating automation hasn’t done more to raise productivity. The authors point out that productivity gains from automation depend on the actual superiority of machines over humans for a given task. A rush to automate because a company gets caught up in a wave of technological enthusiasm or receives a tax break on new equipment may not be that helpful.

This analysis clarifies that automation will reduce labor demand when the productivity effect is not very large. Contrary to a common presumption in popular debates, it is not the “brilliant” automation technologies but those that are “so-so” and generate only small productivity improvements that will reduce labor demand. This is because the positive productivity effect of so-so technologies is not sufficient to offset the decline in labor demand due to displacement.

Favoring machines over human workers may also result in a lack of investment in education and training:

…[T]here may be a mismatch between the available skills of the workforce and the needs for new technologies, which could further reduce productivity gains from automation and hamper the introduction of new tasks—because the lack of requisite skills reduces the efficiency with which new technologies can be deployed.

The future of work

By considering a variety of things affecting labor demand, Acemoglu and Restrepo avoid a simple preoccupation with a positive factor like the productivity effect or a negative factor like the displacement effect. “Our evidence and conceptual approach support neither the claims that the end of human work is imminent nor the presumption that technological change will always and everywhere be favorable to labor.” It will be the balance of the various effects that will matter.

The authors don’t make specific policy recommendations, but some very general prescriptions follow from their analysis. We shouldn’t be afraid to automate tasks where machines have a clear advantage, since the gains in value added are too good to pass up. But we should also enhance the value of human labor, both by giving the workers who remain in automating industries their share of the gains, and also by investing in the education and training workers need to perform new tasks that humans can do better than machines. Where private employers don’t find it profitable to nurture and reward human labor, government must play a strong role for the general good.

As it stands now, too much displaced labor is crowding into low-skill, low-tech, low-wage work. That is a waste of both our human and technological resources. A jobless future where robots work, their owners get rich, and most people live off public assistance is also a dismal prospect. If we are to have a hi-tech economy, let it be one where the average worker can reap the benefits in creative work, good pay, and rewarding leisure.


Effects of New Technologies on Labor

January 4, 2019

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David Autor and Anna Salomons, “Is automation labor share-displacing? Productivity growth, employment, and the labor share.” Brookings Papers on Economic Activity, Spring 2018.

Daron Acemoglu and Pascual Restrepo, “Robots and jobs: Evidence from US Labor Markets.” National Bureau of Economic Research, March 2017.

I have been interested in automation’s effects on the labor force for a long time, especially since reading Martin Ford’s Rise of the Robots. Ford raises the specter of a “jobless future” and a massive welfare system to support the unemployed.

Here I discuss two papers representing some of the most serious economic research on this topic.

The questions

To what extent do new technologies really displace human labor and reduce employment? The potential for them to do so is obvious. The mechanization of farming dramatically reduced the number of farm workers. But we can generalize only with caution. In theory, a particular innovation could either produce the same amount with less labor (as when the demand for a product is inelastic, often the case for agricultural products), or produce a larger amount with the same labor (when demand expands along with lower cost, as with many manufactured goods). An innovation can also save labor on one task, but reallocate that labor to a different task in the same industry.

Even if technological advances reduce the labor needed in one industry, that labor can flow into other industries. Economists have suggested several reasons that could happen. One involves the linkages between industries, as one industry’s productivity affects the economic activity of its suppliers and customers. If the computer industry is turning out millions of low-cost computers, that can create jobs in industries that use computers or supply parts for them. Another reason is that a productive industry affects national output, income and aggregate demand. The wealth created in one industry translates into spending on all sorts of goods and services that require human labor.

The point is that technological innovations have both direct effects on local or industry-specific employment, and also indirect effects on aggregate employment in the economy as a whole. The direct effects are more obvious, which may explain why the general public is more aware of job losses than job gains.

A related question is the effect of technology on wages, and therefore on labor’s share of the economic value added by technological change. Do employers reap most of the benefits of innovation, or are workers able to maintain their share of the rewards as productivity rises? Here too, aggregate results could differ from results in the particular industries or localities experiencing the most innovation.

The historical experience

American history tells a story of painful labor displacement in certain times, places and industries; but also a story of new job creation and widely shared benefits of rising productivity. Looking back on a century of technological change from the vantage point of the mid-20th century, economists did not find negative aggregate effects of technology on employment or on labor’s share of the national income. According to Autor and Salomons:

A long-standing body of literature, starting with research by William Baumol (1967), has considered reallocation mechanisms for employment, showing that labor moves from technologically advancing to technologically lagging sectors if the outputs of these sectors are not close substitutes. Further,…such unbalanced productivity growth across sectors can nevertheless yield a balanced growth path for labor and capital shares. Indeed, one of the central stylized facts of modern macroeconomics, immortalized by Nicholas Kaldor (1961), is that during a century of unprecedented technological advancement in transportation, production, and communication, labor’s share of national income remained roughly constant.

Such findings need to be continually replicated, since they might hold only for an economy in a particular place or time. In the 20th century, the success of labor unions in bargaining for higher wages and shorter work weeks was one thing that protected workers from the possible ill effects of labor-saving technologies.

Recent effects of technological change

Autor and Salomons analyze data for OECD countries for the period 1970-2007. As a measure of technological progress, they use the growth in total factor productivity (TFP) over that period.

They find a direct negative impact of productivity growth on employment within the most affected industries. However, they find two main indirect effects that offset the negative impact for the economy as a whole:

First, rising TFP within supplier industries catalyzes strong, offsetting employment gains among their downstream customer industries; and second, TFP growth in each sector contributes to aggregate growth in real value added and hence rising final demand, which in turn spurs further employment growth across all sectors.

To put it most simply, one industry’s productivity may limit its own demand for labor, but its contribution to the national output and income creates employment opportunities elsewhere.

With regard to labor’s share of the economic benefits, the findings are a little different. Here again, the researchers find a direct negative effect within the industries most affected by technological innovation. But in this case, that effect is not offset, for the most part, by more widespread positive effects.

The association between technological change and labor’s declining share varied by decade. Labor’s share actually rose during the 1970s, declined in the 1980s and 90s, and then fell more sharply in the 2000s. The authors mention the possibility that the newest technologies are especially labor-displacing, but reach no definite conclusion. Another possibility is that non-technological factors such as the political weakness of organized labor are more to blame.

The impact of robotics

Autor and Salomons acknowledge that because they used such a general measure of technological change, they couldn’t assess the impact of robotics specifically. They do cite work by Georg Graetz and Guy Michaels that did not find general negative effects of robots on employment or labor share in countries of the European Union. That’s important, since many European countries have gone farther than we have in adopting robots.

The paper by Acemoglu and Restrepo focuses on the United States for the period 1990-2007. (They deliberately ended in 2007 so that the impact of the Great Recession wouldn’t muddy the waters.)

The authors used the definition of robot from the International Federation of Robotics, “an automatically controlled, reprogrammable, and multipurpose [machine].” Over the period in question, robot usage increased from 0.4 to 1.4 per thousand workers. “The automotive industry employs 38 percent of existing industrial robots, followed by the electronics industry (15 percent), plastic and chemicals (10 percent), and metal products (7 percent).”

Adoption of industrial robots has been especially common in Kentucky, Louisiana, Missouri, Tennessee, Texas, Virginia and West Virginia. As Thomas B. Edsall titled his recent New York Times column, “The Robots Have Descended on Trump Country.”

Acemoglu and Restrepo classified localities–technically “commuter zones”–according to their “exposure” to robotics, based on their levels of employment in types of jobs most conducive to robotization.

Their first main finding was a direct negative effect of robotics on employment and wages within commuting zones:

Our estimates imply that between 1990 and 2007 the increase in the stock of robots…reduced the employment to population ratio in a commuting zone with the average US change in robots by 0.38 percentage points, and average wages by 0.71 percent (relative to a commuting zone with no exposure to robots). These numbers…imply that one more robot in a commuting zone reduces employment by about 6 workers.

The workers most likely to be affected are male workers in routine manual occupations, with wages in the lower-to-middle range of the wage distribution

In the aggregate, these local effects are partly offset by “positive spillovers across commuting zones”–positive effects on employment and wages throughout the economy. With these spillovers taken into account, the estimated effects of robotics on employment and on wages are cut almost in half, dropping to 0.20 percent and 0.37 percent respectively.

The authors state their conclusion cautiously, as “the possibility that industrial robots might have a very different impact on labor demand than other (non-automation) technologies.”

Summary

While there is little doubt that new technologies often displace labor in particular industries and localities, the aggregate effects on employment and wages are less consistent.  Historically (late 19th and early 20th centuries), employment and labor share of income held up very well. For developed countries in the period 1970-2007, Autor and Salomons found a mixed picture, with robust employment but declining labor share after 1980. With respect to robotics specifically, Graetz and Michaels did not find declines in employment or labor share in the European Union, but Acemoglu and Restrepo found some decline in both employment and wages in the U.S.

It seems fair to say that the jury is still out on the effects of automation on the labor force. It may be that automation has no inevitable effect, but that it depends on how we as a society choose to deal with it. We shouldn’t assume a world of mass unemployment and widespread government dependency on the basis of recent, preliminary results from one country. Authors such as Thomas Friedman, who are more optimistic than Martin Ford about the long-run effects of new technologies, have yet to be proved wrong.


Thank You for Being Late (part 2)

November 15, 2018

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Today I’ll discuss two chapters of Thomas Friedman’s Thank You for Being Late that I found especially insightful: Ch. 8 on the implications of new technologies for employment, and Ch. 9 on the problem of global order.

The future of work

Friedman begins his discussion of work with a bold pronouncement: “Let’s get one thing straight: The robots are not destined to take all the jobs. That happens only if we let them–if we don’t accelerate innovation in the labor/education/start-up realms, if we don’t reimagine the whole conveyer belt from primary education to work and lifelong learning.”

I was pleased to find that Friedman’s position is similar to the one I laid out in my critique of Martin Ford’s The Rise of the Robots Ford predicted a future of massive unemployment, with millions of displaced workers relying on government for a minimal income. We could get a taste of that during a transitional period, but I don’t think that’s a very good description of where we are ultimately headed.

Friedman doesn’t deny that smart machines can now perform many tasks currently or formerly performed by humans. But he makes a sharp distinction between automating tasks and automating whole jobs so as to eliminate the human contribution altogether. The upside of automation is increased productivity. Workers aided by new technologies can produce more per hour, reducing the unit cost of what they produce. That can create a larger market for the product, increasing the demand for labor in a given occupation. A car was an expensive luxury item before the assembly line cut costs to create a mass market and a booming industry. Friedman reports that “employment grows significantly faster in occupations that use computers more,” as in banking and paralegal work.

To give an example from my own experience, financial planning software has automated many of the most tedious tasks involved in preparing a retirement plan, such as mathematically projecting future income from savings rates and asset allocation choices. But that hasn’t resulted in a reduced need for financial planners. On the contrary, it has made the services of a planner affordable for more people. Planners can spend less time doing calculations but more time relating to their clients.

Friedman says, “Jobs are not going away, but the needed skills for good jobs are going up.” What are disappearing are well-paid jobs with only modest skill requirements, like twentieth-century manufacturing jobs.

Retooling education

In general, today’s good jobs require more education; yet it does not follow that a college education necessarily qualifies a person for a good job. That’s not because a liberal education is a waste of time, but because it is only a foundation that must be built upon with lifelong job-relevant learning.

Friedman quotes MIT economist David Autor, who stresses the need for more than one kind of learning: “If it’s just technical skill, there’s a reasonable chance it can be automated, and if it’s just being empathetic or flexible, there’s an infinite supply of people, so a job won’t be well paid. It’s the interaction of both that is virtuous.”

Friedman is a strong believer in a broad, basic education that includes “strong fundamentals in writing, reading, coding, and math; creativity, critical thinking, communication, and collaboration; grit, self-motivation, and lifelong learning habits; and entrepreneurship and improvisation….” Even a robotics enthusiast like Martin Ford acknowledges that humans surpass robots in general intelligence, as opposed to specialized task capabilities.

However, recipients of this basic education will also have to cope with rapidly changing workplace requirements. Technology will play a central role here, both in creating the automated systems with which workers interact, and in enhancing learning processes themselves. Friedman wants to “turn AI into IA,” by which he means turning artificial intelligence into intelligent assistance to support lifelong learning. “Intelligent assistance involves leveraging artificial intelligence to enable the government, individual companies, and the nonprofit social sector to develop more sophisticated online and mobile platforms that can empower every worker to engage in lifelong learning on their own time, and to have their learning recognized and rewarded with advancement.” When the time comes to pick up a new skill, you can probably find an app to help you learn it.

Friedman describes AT&T as one company that is demanding more lifelong learning of its employees, but supporting it with measures like tuition reimbursements, online courses developed in collaboration with online providers, and promotions for those who acquire new skills. This represents a new social contract between employer and employee–“You can be a lifelong employee if you are ready to be a lifelong learner.”

Every major economic shift has involved the rise of a new asset class, such as land in the agrarian economy and physical capital in the industrial economy. The rising asset class today is human capital, and that is where society’s investments must be increasingly concentrated.

The threat of global disorder

In the immediate aftermath of the Cold War, after the collapse of the Soviet Union, The U.S. remained the only superpower and the most obvious model for other countries to emulate. Many thinkers expressed the hope that the world could move faster in the direction of American-style democracy and capitalism. But then the interventions in such places as Iraq and Afghanistan failed to produce stable democracies, the Great Recession called into question capitalist progress, and Americans lowered their expectations for world leadership.

What Friedman calls the post-post-Cold War world is characterized by shrinking American power, especially in the Middle East, and new challenges arising from the accelerations in technological change, globalization and environmental degradation.  In large areas of the less developed world, the danger is that states will fail and societies will sink into disorder, dragging the global political order and economy down. Environmental disasters like deforestation in Central America or drought and desertification in sub-Sahara Africa are uprooting people from their traditional relationship to the land. And while some poorer countries are advancing by providing cheap labor to the global economy, the future may belong to those who can provide smarter labor, and that requires greater investments in human capital.

Friedman says that during the Cold War, superpower competition gave America a reason to assist developing countries, in order to keep them in our camp. The mid-twentieth century economic boom also gave us the means to do so. While many Americans are now inclined to turn their back on the rest of the world, Friedman makes a case for renewed global involvement: “While we cannot repair the wide World of Disorder on our own, we also cannot just ignore it. It metastasizes in an interdependent world. If we don’t visit the World of Disorder in the age of accelerations, it will visit us.” The dislocated people in failed states can become refugees or terrorists. The same technologies that can empower people to learn and produce more can empower them to build improvised explosive devices triggered by cell phones, or perhaps a weapon of mass destruction.

In Friedman’s view, the best thing the U.S. could do to “help stabilize the World of Disorder and widen the islands of decency” would be to help fund schools and universities. He would also like to see us help the poorest people make a living in their own villages by assisting them with their environmental problems. He points out that it costs only 100-300 dollars to restore a hectare of degraded land.

In a world of enhanced interdependence, the haves would do well to invest in the development of the have-nots, domestically and globally. If we do not rise together, we will very likely fall together.

Continued


Thank You for Being Late

November 13, 2018

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Thomas L. Friedman. Thank You for Being Late: An Optimist’s Guide to Thriving in the Age of Accelerations. New York: Farrar, Straus and Giroux, 2016.

This book is New York Times columnist Thomas Friedman’s latest reflection on social change–technological, global and environmental. The title refers to his experience of having someone show up late for an appointment, and then realizing that the extra few minutes provide a time for reflection in an otherwise busy day.

Friedman’s basic premise is that “the three largest forces on the planet–technology, globalization, and climate change–are all accelerating at once. As a result, so many aspects of our societies, workplaces, and geopolitics are being reshaped and need to be reimagined….In such a time, opting to pause and reflect, rather than panic and withdraw, is a necessity.”

Technological acceleration

In chapters 2 through 4, Friedman pulls together a wealth of examples to provide a fine overview of developments in digital technology. I can’t do justice to all the detail, but here are a few highlights.

Remarkable breakthroughs have affected all five of the basic components of computing:

(1) the integrated circuits that do the computing; (2) the memory units that store and retrieve information; (3) the networking systems that enable communications within and across computers; (4) the software applications that enable different computers to perform myriad tasks individually and collectively; and (5) the sensors—cameras and other miniature devices that can detect movement, language, light, heat, moisture, and sound and transform any of them into digitized data that can be mined for insights.

The result is “one of the greatest leaps forward in history.”

All this computing power is not just on a desktop or a laptop, but in the “cloud”, or what Friedman calls the computing “supernova”. The ability to tap into this universal information-processing capacity is deeply empowering to individuals, groups and organizations. The challenge is to use that power constructively and not destructively, for collective liberation and not just for domination or other selfish purposes. One downside is that technological innovation is occurring faster than “the average rate at which most people can absorb all these changes.” For example, we are not yet accustomed to the kind of lifelong learning that the information age will require.

Friedman also asks why it’s taking so long for technological change to raise economic productivity. In The Rise and Fall of American Growth, Robert Gordon argued that the extraordinary productivity gains of the “special century” from 1870 to 1970 are unlikely to be repeated. Friedman is more optimistic, pointing out that productivity gains from electrification took several decades to materialize. New factories and business processes had to be designed, and a new generation of managers and workers had to emerge. Many technological breakthroughs are far too new–a number of them emerged in 2007–to assess their effects on social institutions. I find it exciting to imagine a new era of rising productivity and wage gains, which might go a long way to alleviate class, race and gender tensions.

Global acceleration

Electronic connectivity is one of the main factors accelerating human interactions across vast distances. The total value of global flows of goods, services, and finance increased from 24 percent to 39 percent of world GDP between 1990 and 2014.

William H. McNeill, the historian noted for The Rise of the West, argues that “the principal factor promoting historically significant social change is contact with strangers possessing new and unfamiliar skills.” People may perceive such contacts as either a threat or an opportunity, but in the long run they provide societies with more solutions to human problems. Friedman believes that “those societies that are most open to flows of trade, information, finance, culture, or education, and those most willing to learn from them and contribute to them, are the ones most likely to thrive in the age of accelerations.” Although Friedman has little to say about the Trump presidency in this book, we know from his columns that he has little use for nationalism or isolationism.

Friedman does recognize that people whose lives are vulnerable to disruption by globalization will need help coping with this new world. “If a society doesn’t build floors under people, many will reach for a wall–no matter how self-defeating that would be.” Nevertheless, his chapter on globalization contains his most optimistic statement:

[I]f there is one overarching reason to be optimistic about the future, and to keep trying to get the best out of digital globalization and cushion the worst, it is surely the fact that this mobile-broadband-supernova is creating so many flows and thus enabling so many more people to lift themselves out of poverty and participate in solving the world’s biggest problems. We are tapping into many more brains, and bringing them into the global neural network to become “makers.” This is surely the most positive—but least discussed or appreciated—trend in the world today, when “globalization” is becoming a dirty word because it is entirely associated in the West with dislocations from trade.

Environmental/demographic acceleration

The human impact on the planet is increasing, as a result of both our dramatic population growth and our intensive use of the Earth’s resources.

Here Friedman is most concerned with global climate change, and he does not explain demographic trends as much as I would like. Human population growth accelerated especially in the twentieth century because of progress in reducing mortality rates, especially for infants and children. Just between 1900 and 2000, world population increased from 1.65 billion to 6 billion. Smaller families and declining birth rates have reduced the rate of growth somewhat, but the world population is now 7.7 billion and expected to add a couple billion more before leveling off.

A team of scientists specializing in Earth systems identified “nine key planetary boundaries we humans must make sure we do not breach.” Unfortunately, we have already breached four of them. We have put more carbon dioxide into the atmosphere than we should, if we want to hold average global temperature rise since the Industrial Revolution to 2 degrees Celsius. In some places, biodiversity is already below 90 percent of preindustrial levels. The portion of the earth’s original forests that remain has fallen below 75%. And we have been poisoning the earth by adding far too much phosphorus, nitrogen and other elements.

Other boundaries that we are currently staying within, but not by much, involve how much we are acidifying oceans, using freshwater, loading the atmosphere with microscopic particles, and introducing other novel entities into nature, like plastics and nuclear wastes.  One area where we are moving in the right direction is in restoring the thickness of the ozone layer that protects us against dangerous radiation.

Technological breakthroughs–especially in clean energy–are helping. But we also need to change our behavior more rapidly, in order to apply known solutions on a large enough scale.

Continued


Solving the Productivity Puzzle

February 27, 2018

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McKinsey Global Institute, “Solving the Productivity Puzzle: The Role of Demand and the Promise of Digitization,” 2018. 

This report discusses why the rate of growth in economic productivity has been so low in recent years, and how it might improve in the future.

Productivity: Why it matters

The report makes a fundamental assumption: “Productivity growth is crucial to increase wages and living standards, and helps raise the purchasing power of consumers to grow demand for goods and services.” That’s basic economics, but worth remembering at a time when people in many countries have grown accustomed to minuscule productivity growth.

Production and consumption are, of course, two sides of the same economic coin. The most obvious way for the average worker to receive more goods and services is for the average worker to produce more goods and services per hour of work. People can also get ahead by working more hours, but then they are paying for their economic gains with reduced free time.

The benefits of high productivity may not be distributed evenly, but that’s another issue. Workers may not receive their fair share of the benefits when productivity is rising, but they are even less likely to get ahead when productivity is not rising. Then the competition for benefits is more of a zero-sum game, and the haves will be especially resistant to redistributing benefits to the have-nots. The widespread assumption that anyone’s gain must be someone else’s loss is a big reason why our politics have become so ugly. (That last point is mine, not the report’s.)

Sagging productivity

The report is based on data from seven countries: France, Germany, Italy, Spain, Sweden, the United Kingdom, and the United States. Productivity is defined simply as Gross Domestic Product per hour worked.

The data show these trends for recent decades:

  • Productivity growth was strong during the postwar economic boom
  • In general, productivity growth has been much slower since the 1970s
  • A brief productivity boom occurred from about 1995-2005, especially in the United States, associated with applications of information and communications technology (ICT)
  • Productivity has stagnated since then, with near zero annual growth in both Europe and the U.S.

The report identifies three main reasons for low productivity growth, describing them as waves passing over the economy one by one.

First, the rate of innovation associated with ICT slowed after 2005. For example, big retailers like Walmart had used the new technologies to make their supply chains more efficient, but the biggest changes had already occurred by then.

Second, the financial crisis of 2007-08 ushered in a period of “weak demand and uncertainty.” Businesses were reluctant to make costly changes in production without confidence that the market could absorb the additional goods or services produced. Companies held back on new investments and held the line on wages. The economy recovered from the recession, but it was a “job-rich” and “productivity-poor” recovery. As long as there were people wanting to return to work, “companies met slowly rising demand by filling excess capacity and adding hours,” not by raising productivity and wages. Hopefully, the economy can now move beyond recovery into a new period of productivity growth and wage gains. The danger is that the economy becomes stuck in a vicious cycle, in which workers earn too little to raise demand, and businesses fail to invest in higher productivity because they can meet existing demand with low-cost labor.

Third, a revolution in digital technology is underway, but “the impact of digital is not yet evident in the productivity numbers.” Many sectors of the economy, such as education, health care and construction, are only beginning to digitize their operations. Transition costs can be high, including not only the costs of equipment and training, but the disruptive impact on existing operations. A retailer that adds an online store may suffer offsetting declines in business at its brick-and-mortar stores.

Prospects for digital-based productivity growth

As of now, the economy is in a paradoxical position: “…In an era of digitization, with technologies ranging from online marketplaces to machine learning, the disconnect between disappearing productivity growth and rapid technological change could not be more pronounced.” How long can it be before technological know-how actually translates into productivity gains and higher wage potential for the average worker?

The authors of this report see “the potential for at least 2 percent [productivity] growth a year over the next ten years, with 60 percent coming from digital opportunities.” But they also see some potential problems that need to be addressed if that potential is to be realized.

One of their concerns is the market power that digital technologies may bestow on a few hugely successful companies:

Various digital technologies are characterized by large network effects, large fixed costs, and close to zero marginal costs. This leads to a winner-take-most dynamic in industries reliant on such technologies, and may result in a rise in market power that can skew supply chains and lower incentives to raise productivity.

To put it more simply, once a company has made a large initial investment in new technologies, it may be able to turn out products so cheaply and maintain such a locked-in customer base, that it may no longer have to raise productivity to dominate a market. It might just become fat and lazy. I doubt if this phenomenon is unique to the digital age. It may be part of the dynamics of capitalism, helping to explain why productivity-based economic change comes in cycles of growth, maturation and stagnation.

Demand-side constraints on productivity

Another big concern is that weak economic demand may continue to exert a drag on investment and productivity growth. Some of the weak demand may be just cyclical, a normal after-effect of recession. But the authors of this report join other economists in worrying that some of it may be structural–that is, built into today’s economy. They express concern that “declining labor share of income and rising inequality are eroding median wage growth, and the rapidly rising costs of housing and education exert a dampening effect on consumer purchasing power.”

How digital technologies affect jobs also has implications for the demand side. In theory, the benefits of higher productivity could appear in the form of higher wages and shorter work weeks, as they did in the postwar era. If, on the other hand, a large segment of the labor force is simply replaced by smart machines, their loss of purchasing power could reduce economic demand and nip economic growth in the bud. “Unless displaced labor can find new highly productive and high-wage occupations, workers may end up in low-wage jobs that create a drag on productivity growth.”

This line of reasoning leads the authors to recommend public policies that focus on the demand side. That is in contrast to conservative policies that focus on helping the supply side (businesses and their investors) with tax cuts and looser regulations. The implicit assumption (perhaps rarely stated since it seems so counter-factual) is that the poor capitalists don’t have enough capital to raise productivity and grow the economy. If, however, the problem is more on the demand side, then the economy may be helped by government spending to supplement the purchasing power of low-income consumers, invest in public works like infrastructure repairs, make education and health insurance more affordable, and support worker retraining for new jobs.

The report also recommends that companies “rethink their employee contract in order to develop a strategy, potentially together with labor organizations, where people and machines can work side by side and workers and companies can prosper together.” If that sounds like pie in the sky in this era of anti-labor capitalism, we should remember that it is a pretty good description of the business-labor understanding that existed during the last great era of productivity growth. More of us knew then what many of us seem to have forgotten recently, that the economic engine runs best when its benefits are widely shared. In the 1950s, the “widely shared” part mainly applied to white men. Now we must learn to be even more inclusive.

Overall, the report is an optimistic, yet not unrealistic vision: “A dual focus on demand and digitization could unleash a powerful new trend of rising productivity growth that drives prosperity across advanced economies for years to come.”