Power and Progress (part 3)

August 28, 2025

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Acemoglu and Johnson argue that the link between technological progress and general prosperity is not automatic. It depends on other variables, especially how well new technologies sustain the demand for labor and how much workers share the benefits of rising productivity. Having supported their argument with historical examples, they now apply it to the more recent economy, especially the period since 1980.

The “graveyard of shared prosperity”

At the height of the postwar prosperity, believers in the “productivity bandwagon” expected further technological breakthroughs to raise productivity and wages, continuing and even surpassing the postwar prosperity. Digital technologies, like the mainframe computers already in use in the 1960s, looked very promising. As the digital revolution took off, the rate of innovation soared.

“Digital technologies, even more so than electricity…are general purpose, enabling a wide range of applications.” They have the potential not only to replace human labor with smart machines, but also to complement and enhance human labor. During my university career, I used computers to enhance my teaching, research and administrative work in numerous ways, but they never replaced me in any of those roles. Many manufacturing workers weren’t so lucky, as new technologies were used more to replace labor than to augment it. As the authors put it, “Digital technologies became the graveyard of shared prosperity.” I would emphasize the word “shared” in that claim, since no one disputes that digital technologies have created great riches for some and modest gains for others.

The authors attribute much of the decline of shared prosperity to a more conservative vision of progress that developed in the 1960s and 70s and became dominant after the “Reagan revolution” of 1980. In this vision, the path to prosperity started at the top, with wealthy investors, high-profit corporations, and well-rewarded shareholders. If left alone by government, they would create more wealth and income for all. But to maximize investment, the rich needed low taxes; and to maximize profits, corporations needed low taxes, minimal regulation, and low labor costs. “Many American managers came to see labor as a cost, not as a resource…This meant reducing the amount of labor used in production through automation.”

Americans may place most of the blame for lost manufacturing jobs on foreign competitors like China, but automation is responsible for more job losses and downward mobility. While foreign workers and immigrants did take many of the of the low-wage manufacturing jobs, automation destroyed more of the jobs that had been paying good wages.

The workers who remained in manufacturing were more productive, but the demand for additional workers fell. In addition, total factor productivity grew at a much slower rate after 1980 than in the previous four decades. Median wages grew even more slowly, less than 0.45% per year.

Inequality increased in a number of ways:

[T]he share of the richest 1 percent of US households in national income rose from around 10 percent in 1980 to 19 percent in 2019…Throughout most of the twentieth century, about 67-70 percent of national income went to workers, and the rest went to capital (in the form of payments for machinery and profits). From the 1980s onward, things started getting much better for capital and much worse for workers . By 2019, labor’s share of national income had dropped to under 60 percent…

What income did go to labor was divided more unevenly across educational levels, with college-educated workers gaining some ground, while less educated workers saw actual declines in real earnings. Rather than train less educated workers, employers more often replaced them with fewer but more educated workers. Along with the destruction of manufacturing jobs came the decline of unions and the reduced power of workers to fight for good wages and job training.

The value of the five biggest corporations—Google, Facebook, Apple, Amazon and Microsoft—grew to about 20 percent of GDP, twice as much as the value of the five biggest corporations at the height of the Gilded Age in 1900.

Artificial intelligence

Acemoglu and Johnson see artificial intelligence making matters worse, since so many employers are using it to replace human labor rather than augment it. Rather than ask how machines can be useful to workers, proponents of new technologies ask how machines can equal or surpass human workers. Taken to an extreme, the goal of AI enthusiasts is to achieve a general machine intelligence that can make any decision as well as a human. From a business standpoint, it is the ultimate way of cutting labor costs, by replacing educated as well as less-educated labor.

So far, the results have been a lot of what the authors call “so-so automation,” with only modest gains in productivity. The reason, they think: “Humans are good at most of what they do, and AI-based automation is not likely to have impressive results when it simply replaces humans in tasks for which we accumulated relevant skills over centuries.”

What makes us think that the way to prosperity is to devalue the human capacities of the workers who are trying to prosper? That may generate short-term profits for the owners of the machines, but not shared and sustained prosperity. The authors warn that “infatuation with machine intelligence encourages mass-scale data collection, the disempowerment of workers and citizens, and a scramble to automate work, even when this is no more than so-so automation—meaning that it has only small productivity benefits.”

The threat to democracy

The part of the book I found most disturbing was the chapter, “Democracy Breaks.” It describes what some have called a new “digital dictatorship,” most evident in China. With the help of some of the world’s largest AI companies, the Chinese government has turned the data-crunching capacities of new technologies into tools of mass surveillance and control. The aim is to monitor, rate, and sanction the behavior of any citizen. Forty years after Orwell’s imaginary 1984, Big Brother is watching more efficiently than ever. Other authoritarian governments—Russia, Iran, Saudi Arabia, Hungary, and even India—are developing similar capabilities.

In the United States, “The NSA cooperated with Google, Microsoft, Facebook, Yahoo!, various other internet service providers, and telephone companies such as AT & T and Verizon to scoop up huge amounts of data about American citizens’ internet searches, online communications and phone calls.”

Digital media have also played a role in polarizing Americans and debasing civil discourse. Media companies whose business model was based on selling ads, such as Facebook, wanted to keep their users as engaged as possible. “Any messages that garnered strong emotions, including of course hate speech and provocative misinformation, were favored by the platform’s algorithms because they triggered intense engagement from thousands, sometimes hundreds of thousands, of users.”

The hope that digital media would—like the printing press of an earlier era—empower citizens and strengthen democracy has not been fulfilled. The underlying problem, according to Acemoglu and Johnson, is that technology companies prefer a more “technocratic approach, which maintains that many important decisions are too complex for regular people.” In the economy, that encourages the devaluation and replacement of human  laborers and a flow of economic rewards to the rich. In government, it enables the surveillance and control of citizens and a flow of political power to authoritarian leaders.

Redirecting technology

In their final chapter, Acemoglu and Johnson describe a three-pronged formula for redirecting technology: “altering the narrative and changing norms…cultivating countervailing powers…[and] policy solutions.”

The new narrative would reject “trickle-down economics” and shift the emphasis back to shared prosperity. It would encourage decision-makers to address the wellbeing of ordinary people, instead of assuming that what’s good for corporate profits or large fortunes is good for everybody. Hopefully it would influence how business managers think and what they learn in business school.

Countervailing power against self-serving technocrats and corporations can come from many directions—government, civic organization and online communities. Now that blue-collar manufacturing workers are a smaller part of the labor force, organized labor should grow to embrace many occupations. Workers should organize on a broader level than the plant or the firm and play a major role in national politics.

Here are some of the policy changes they recommend:

  • Subsidize socially beneficial technologies, especially those that augment human labor rather than replace it
  • Support research on such technologies, especially in education and health care
  • Break up technology companies that have become too monopolistic
  • Reform tax policies that favor investments in equipment over hiring of workers
  • Increase tax incentives for worker training
  • Repeal the law that exempts internet platforms from any accountability for what they post
  • Tax platforms that rely on advertising in favor of those with alternative revenue streams, such as subscriptions or nonprofit contributions
  • Raise the minimum wage, but do not provide a Universal Basic Income

The authors regard a Universal Basic Income as “defeatist,” since it “fully buys into the vision of the business and tech elite that they are the enlightened, talented people who should generously finance the rest.” What they support instead is a new vision committed to seeing the value and productive potential in all of us and investing accordingly.

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Power and Progress (part 2)

August 24, 2025

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In general, over the last millennium, technological advances have raised living standards. But this broad generalization obscures important historical variations. At least two conditions must be met if new technologies are to contribute to widespread prosperity. First, they must sustain labor demand by augmenting and not just replacing human labor. And second, high labor demand must generate high wages. According to Acemoglu and Johnson’s Power and Progress, directing new technologies toward these ends is a social choice, and the distribution of social power affects how that choice is made.

Even when couched in appeals to the common good, new technologies do not benefit everybody automatically. Often, it is those whose vision dominates the trajectory of innovation who benefit most.

An important implication of this argument is that the path to prosperity leads through democratization as well as through technological innovation. The middle part of the book supports their argument with many historical examples.

“Cultivating Misery”

The history of agriculture reveals that a positive relationship between technology and prosperity is mostly a modern urban phenomenon. For much of history, people who have worked the land have received little benefit from their own increased productivity. In Medieval Europe, the problem was not a low demand for labor, but the power of landowners over workers. England after the Norman conquest “was a dark age for English peasants because the Norman feudal system ensured that higher productivity would accrue to the nobility and the religious elite.” Farming methods gradually improved, but a coercive social system enabled the elites to claim the surplus product, while keeping the peasants at a subsistence level.

Beginning in the fourteenth century, this social order was disrupted by the high mortality rates of the Black Death. For a time, the demand for labor exceeded the supply, putting the surviving workers in a stronger bargaining position.

By the eighteenth century, agricultural laborers faced a new threat. The expansion of commercial agriculture led landowners to reorganize their holdings, throwing out peasants who worked the land for their own subsistence and replacing them with fewer workers producing commodities for the growing market. In the name of progress, “It was acceptable to strip the poor and uneducated from their customary rights and common lands because the new arrangements would allow the deployment of modern technology, hence improving efficiency and producing more food.”

Through much of history, therefore, agricultural systems have “cultivated misery.” When masses of farmworkers were in demand, they were usually dominated by more powerful landowners. When technology improved productivity, they were either worked harder so that others could profit, or else thrown off the land.

Acemoglu and Johnson worry that if the latest technologies replace too many workers and empower the few rather than the many, “our future begins to look disconcertingly like our agricultural past.”

Industrialization

The shrinking demand for farm labor would not have been an obstacle to prosperity if good jobs awaited the displaced peasants in the manufacturing sector. But in the early days of manufacturing, the factory system offered an alternative form of misery.

The Industrial Revolution was preceded by what the authors call a “middling sort of revolution.” By the mid-eighteenth century, a rising class of innovators, inventors and entrepreneurs were starting to reshape the economy. Innovations like the steam engine and the spinning frame appeared at this time. Just as important was a social transformation that weakened the power of the landed aristocrats and modestly expanded democracy.

As the rising entrepreneurs reorganized production and applied new technologies, productivity rose rapidly, especially in the textile industry. But the authors’ theory explains why this “progress” did not initially improve living conditions for the workers. The first reason was low labor demand. Because early industrialization emphasized the mechanization of existing tasks, notably spinning and weaving, the factory system created new jobs by destroying old ones.

The second reason was the power imbalance between entrepreneurs building capital and impoverished workers desperate for work. As the rising middle class expanded their wealth and political influence, their vision of progress increasingly dominated public discussion. The “industrial entrepreneurs’ choices of technology, organization, growth strategy, and wage policies enriched themselves while denying their workers the benefits of productivity increases—until the workers themselves had enough political and social power to change things.”

The result was that early factory workers—despite their high productivity—were made to work very long hours under dismal working conditions for very low wages. They were also crowded into urban factory districts plagued by coal-dust pollution, poor sanitation, unclean water, and related diseases.

As the rising middle class gained wealth and political power, their vision of progress dominated public discourse. Obsessed with how industrialization created new wealth—for them—they had little sympathy for those who earned too little to share in the benefits of their own productivity.

Conditions improved in the second half of the nineteenth century. New technologies like railroads and the telegraph created more jobs than they destroyed. Workers began organizing to exert countervailing power against employers. Social critics and reformers scandalized by social conditions began to challenge the dominant vision of progress. Governments took a few steps to improve public health and other urban conditions. With labor demand and labor power rising along with productivity, real wages could increase.

In the United States, conditions were generally better than in Europe because land was more abundant but labor was more scarce. That combination put workers, especially skilled workers, in a position to command a higher wage.

Rising real wages in Western Europe and America did not stop the rich from getting richer even faster, so that economic inequality increased during the Gilded Age. It also increased globally. At a time when the fruits of technological progress were starting to benefit more Europeans and Americans, colonialism impeded that process in many other places. The large flow of manufactured textiles from Britain to colonial India destroyed indigenous textile jobs, retarded industrialization, and confined a greater proportion of Indian labor to rural occupations.

A formula for prosperity

The time and place best characterized by a “productivity bandwagon” was the mid-twentieth century in Western Europe and the United States, especially the three decades after World War II. It had all the elements of an economically successful application of technology: Sustained growth in productivity; high labor demand in expanding occupations, and institutional structures supporting a more egalitarian distribution of power.

In the twentieth century, the proportion of the workforce needed in agriculture dropped sharply, but that was offset by a rising demand for labor in manufacturing and services. This was due to a better balance between labor replacement and labor augmentation. “The reduction in labor requirements driven by automation was offset, sometimes more than one for one, with other aspects of technology that created opportunities for workers.” Large-scale manufacturing needed not only blue-collar workers to run the assembly lines, but engineers to create them, technicians to repair them, and white-collar workers for managerial, clerical and sales jobs.

Operating the machinery of modern manufacturing required some skill, but the skills were not too hard to learn. Union contracts stipulated that employers would train their union employees. Rapid expansion of formal education provided qualifications for higher-level jobs.

Public policy supported broad-based prosperity in several ways: protecting the right of workers to organize and bargain collectively, spending tax dollars on public works and income support, and regulating business to place limits on corporate power.

The results were spectacular. Real wage growth averaged almost 3 percent per year for both more educated and less educated workers. The income distribution became more egalitarian, with labor’s share of national income rising and the share of the richest 1% falling.

Acemoglu and Johnson emphasize how exceptional the link between technology and prosperity was during this period:

In the long sweep of history, the decades that followed the end of World War II are unique. There has never been, as far as anyone knows, another epoch of such rapid and shared prosperity.

Even as they celebrate the accomplishments of the twentieth century, the authors are careful to acknowledge those who were left behind. Black Americans and immigrants were excluded from many of these gains. As individual earners, women were too, although they benefited indirectly as wives and daughters of upwardly-mobile men.

Despite these failures, we can understand why so many of the people who lived in that era—including many economists—came to accept the “productivity bandwagon” as a normal and natural phenomenon. That may have left them unprepared to appreciate the challenges of our new technological era. That is the issue for the last four chapters of the book.

Continued

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Power and Progress

August 21, 2025

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Daron Acemoglu and Simon Johnson. Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. New York: Hachette Book Group, 2024.

Daron Acemoglu and Simon Johnson won the 2024 Nobel Prize in Economics for their research on how political and economic institutions shape national prosperity. In this book, they tackle the relationship between technological innovation and prosperity.

No one doubts that new technologies have the potential to boost productivity and raise living standards. How and when they actually accomplish this is a more difficult question.

In the introduction and first three chapters, the authors lay out their general theory of technology and progress, considering the role of variations in labor demand, wages, and social power. The next four chapters discuss how these variations have played out in various historical situations, ranging from the failure of innovation to benefit farmworkers and early manufacturing workers before the late nineteenth century, to the more widespread prosperity of the mid-twentieth century. Armed with insights from economic theory and history, the authors then address the more recent revolution in digital technology. Readers who follow the argument all the way through should come away with a better understanding of our current technological age and its discontents. I know I did.

The productivity bandwagon

The conventional wisdom in economics, as well as a lot of public discussion, is that technological advances raise productivity, and higher productivity raises living standards. The authors cite Gregory Mankiw’s popular undergraduate textbook, which says that “almost all variation in living standards is attributable to differences in countries’ productivity.”

But the productivity gains from new technologies can only raise living standards if they improve real wages. What about labor-saving technologies that lower the demand for labor, causing unemployment and lower wages? Mankiw acknowledges the problem, but minimizes it by claiming that “most technological progress is instead labor-augmenting.” Most workers find some way to work with new technologies, and their increased productivity enables them to command a higher wage.

Acemoglu and Johnson call this optimistic view the “productivity bandwagon.” They argue to the contrary:

There is nothing in the past thousand years of history to suggest the presence of an automatic mechanism that ensures gains for ordinary working people when technology improves… New techniques can generate shared prosperity or relentless inequality, depending on how they are used and where new innovative effort is directed.

Rather than accept a broad generalization about technology and prosperity, the authors want to study historical variations and identify the key variables involved. The stories that people tell themselves about technology—including the ones economists tell—can both reflect and affect the historical variations. Writing in the Great Depression, John Maynard Keynes coined the term “technological unemployment.” He could imagine “the means of economising the use of labour outrunning the pace at which we can find new uses for labor.” More recently, robotics and artificial intelligence are raising that possibility again, but the productivity bandwagon remains a popular narrative.  Economic elites who profit from the application of new technologies are especially fond of it.

Variations in labor demand

Acemoglu and Johnson maintain that technological advances may or may not increase the demand for labor, depending on whether they are labor-augmenting or just labor-saving.

A classic example of technology that augmented labor, increased labor demand, and raised wages is the electrified assembly line introduced by Henry Ford. It not only raised the productivity of the existing autoworkers; it also enabled auto manufacturers to employ additional workers productively. (Economists call that variable the “marginal productivity of labor.”) By producing more cars at lower cost, car companies created a mass market for what had been a luxury item. In addition, they created additional jobs in related industries, such as auto repair, highway construction and tourism.

The effects of today’s robotics on automobile manufacturing may be very different. Carmakers can make just as many cars with less human labor, so labor productivity goes up. But demand for additional labor may go down, if factories are already turning out as many cars as their market can absorb. The marginal productivity of labor then falls, and the connection between technology and prosperity is weakened.

That is not to say that automation is always bad news for workers. That depends on the balance of labor-saving and labor-augmentation:

For most of the twentieth century, new technologies sometimes replaced people with machines in existing tasks but also boosted worker effectiveness in some other tasks while also creating many new tasks. This combination led to higher wages, increased employment, and shared prosperity.

The problem then is not just automation but excessive automation, especially if it is not really very productive in the fullest sense of the word. In economics “total factor productivity” refers to the relationship between economic output and all inputs, including capital as well as labor. Replacing workers with machines has costs as well as benefits, since machines cost money too, and displaced humans might have contributed something that machines cannot. The authors use the term “so-so automation” to refer to replacement of workers without much productivity gain. In that case, the classic gains of the earlier automobile boom—lower costs, expanded markets, rising labor demand, and widespread prosperity—do not occur.

Variations in wages

Even if new technologies are labor-enhancing, higher wages do not necessarily follow. They have not followed in societies where workers have been coerced to work without pay, or forbidden to leave their employer in search of better pay. The cotton gin enhanced the productivity of cotton workers in the Old South and expanded the areas where cotton could be profitably cultivated. But “the greater demand for labor, under conditions of coercion, translated not into higher wages but into harsher treatment, so that the last ounce of effort could be squeezed out of the slaves.”

In modern, free-market labor systems, wages are freer to rise along with labor demand. However, “wages are often negotiated rather than being simply determined by impersonal market forces.” A dominant employer may set wages for a multitude of workers, while the workers are too disorganized to bargain from strength. It was only in 1871 in Britain and 1935 in the United States that workers gained the legal right to organize and bargain collectively. Opponents of organized labor have continued to find ways of discouraging labor unions to this day. The share of national income going to labor rather than capital was highest when unions were strongest, in the 1950s.

Variations in power

Acemoglu and Johnson argue that the effects of technology depend on “economic, social, and political choices,” and that “choice in this context is fundamentally about power.”

What societies do with new technologies depends on whose vision of the future prevails. The most powerful segments of society have more say than others, although they can be contested by countervailing forces, especially in democratic societies where masses of workers vote. Although plenty of evidence points to the self-serving behavior of elites, they must at least appear to be promoting the common good for their views to be persuasive.

The technological choices a society makes can serve either to reinforce the power of elites or empower larger numbers of workers. This is especially true of general technologies with many applications. In the twentieth century, the benefits of electricity helped power a more egalitarian, broadly middle-class society. We cannot yet say the same about the digital technologies of the present century. The authors apply their theory, buttressed by historical evidence, to explain why.

Recall the subtitle of the book: “Our Thousand-Year Struggle Over Technology and Prosperity.” Making technology work for all of us has always been a struggle, and one that is related to the struggle for true democracy. Looking at it that way is more realistic and enlightening than seeing only a “productivity bandwagon” rolling smoothly toward mass prosperity.

Continued

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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.

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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.

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Posted by Ed Steffes

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