Posts Tagged ‘globalization’

VanishingMiddleClass2

Both Peter Temin and I are concerned about the vanishing middle-class and the desperate plight of most American workers. We even use similar statistics, such as the growing gap between productivity and workers’ wages and the share of income captured by the top 1 percent.

productivity top1

And, as it turns out, both of us have invoked Arthur Lewis’s “dual economy” model to make sense of that growing gap. However, we present very different interpretations of the Lewis model and how it might help to shed light on what is wrong in the U.S. economy—with, of course, radically different policy implications.

It is ironic that both Temin and I have turned to the Lewis model, which was originally intended to make sense of “dual economies” in the Third World, in which peasant workers trapped by “disguised unemployment” and receiving a “subsistence” wage (equal to the average product of labor) in the “backward,” noncapitalist rural/agricultural sector could be induced via a higher “industrial” wage rate (equal to the marginal product of labor) to move to the “modern,” capitalist urban/manufacturing sector, which would absorb them as long as capital accumulation increased the demand for labor.

That’s clearly not what we’re talking about today, certainly not in the United States and other advanced economies where agriculture employs a tiny fraction of the work force—and where much of agriculture, like the manufacturing and service sectors, is organized along capitalist lines. But Lewis, like Adam Smith before him, did worry about the parasitical role of the landlord class and the way it might serve, via increasing rents, to drag down the rest of the economy—much as today we refer to finance and the above-normal profits captured by oligopolies.

So, our returning to Lewis may not be so far-fetched. But there the similarity ends.

Temin (in a 2015 paper, before his current book was published) divided the economy into two sectors: a high-wage finance, technology, and electronics sector, which includes about thirty percent of the population, and a low-wage sector, which contains the other seventy percent. In his view, the only link between the two sectors is education, which “provides a possible path that the children of low-wage workers can take to move into the FTE sector.”

The reinterpretation of the Lewis model I presented back in 2014 is quite different:

What I have in mind is redefining the subsistence wage as the federally mandated minimum wage, which regulates compensation to workers in the so-called service sector (especially retail and food services). That low wage-rate serves a couple of different functions: it’s a condition of high profitability in the service sector while keeping service-sector prices low, thereby cheapening both the value of labor power (for all workers who rely on the consumption of those goods and services) and making it possible for those at the top of the distribution of income to engage in conspicuous consumption (in the restaurants where they dine as well as in their homes). In turn, the higher average wage-rate of nonsupervisory workers is regulated in part by the minimum wage and in part by the Reserve Army of unemployed and underemployed workers. The threat to currently employed workers is that they might find themselves unemployed, underemployed, or working at a minimum-wage job.

In addition, the profits captured from both groups of workers are distributed to a wide variety of other activities, not just capital accumulation as presumed by Lewis. These include high CEO salaries, stock buybacks, idle cash, and financial-sector profits (with a declining share going to taxes). And, if the remaining portion that does flow into capital accumulation takes the form of labor-saving investments, we can have an economic recovery based on private investment and production with high unemployment, stagnant wages, and rising corporate profits.

For Temin, the goal of economic policy is to reduce the barriers (conditioned and created by an increasingly segregated educational system) so that low-wage workers can adopt to the forces of technological change and globalization, which can eventually “reunify the American economy.”

My view is radically different: the “normal” operation of the contemporary version of the dual economy is precisely what is keeping workers’ wages low and profits high across the U.S. economy. The problem does not stem from the high educational barrier between the two sectors, as Temin would have it, but from the control exercised by the small group that appropriates and distributes the surplus within both sectors.

And the only way to solve that problem is by eliminating the barriers that prevent workers as a class—both black and white, in finance, technology, and electronics as well as retail and food services, regardless of educational level—from participating in the appropriation and distribution of the surplus they create.

wage share

It’s obvious to anyone who looks at the numbers that the wage share of national income is historically low. And it’s been falling for decades now, since 1970.

Before that, during the short Golden Age of U.S. capitalism, the presumption was that the share of national income going to labor was and would remain relatively stable, hovering around 50 percent. But then it started to fall, and now (as of 2015) stands at 43 percent.

That’s a precipitous drop for a supposedly stable share of the total amount produced by workers, especially as productivity rose dramatically during that same period.

The question is, what has caused that decline in the labor share?

The latest story proffered by mainstream economists (such as David Autor and his coauthors) has to do with “superstar” firms:

From manufacturing to retailing, giant companies have managed to gobble up a larger and larger share of the market.

While such concentration has resulted in enormous profits for investors and owners of behemoths like Facebook, Google and Amazon, this type of “winner take most” competition may not be so good for workers as a whole. Over the last 30 years, their share of the total income kitty has been eroding. And the industries where concentration is the greatest is where labor’s share has dropped the most. . .

Think about the retail sector, where mom-and-pop stores once crowded the landscape. Now it is dominated by a handful of giants like Walmart, Target and Costco.

It is true, industry concentration has increased dramatically in recent decades (as I explain here). And the wage share has declined (as illustrated in the chart above).

Here’s the problem: exactly the opposite argument is the one that prevailed in the United States for the earlier period. Economists at the time argued that American workers earned a relatively high share of national income because they worked in concentrated industries, such as cars and steel. Thus, their collectively bargained wages included a portion of the “monopoly rents” captured by the firms within those industries.

Now that the wage share has clearly fallen, and shows no signs of returning to its previous levels, economists have changed their story. In their view, market concentration leads to a lower, not higher, wage share.

Why has there been such an about-face in economists’ story about the causes of the declining wage share?

What all the existing stories share is that they avoid identifying anything that has been done to workers as a class. Whether the story is about technological change, globalization, or now superstar firms, the idea is that there are larger forces that unwittingly have created winners and losers—and the losers, if they want, need to acquire the education and skills to join the winners. But don’t touch the basic elements of the economic system that has created such disparate and divergent outcomes.

As it turns out, the presumed rule of a stable wage share turns out to have been an illusion, an exceptional period of relatively short duration during which workers’ wages did in fact rise along with productivity. That wasn’t the case before, and it hasn’t been true since.

The actual rule, as it turns out, is that the wage share falls, as the rate of exploitation increases. That’s how capitalism works, at least much of the time—through periods of faster and slower technological change, higher or lower levels of globalization, more or less concentrated industries.

Sure, under a particular set of postwar conditions in the United States, for two and a half decades or so, the wage share remained relatively stable (and not without pitched battles between capital and labor, as Richard McIntyre and Michael Hillard have shown). But that ended decades ago, and since then workers have been forced to have the freedom to sell their ability to work under conditions that, even as productivity continued to grow, the wage share itself declined.

Mainstream economists have finally recognized the fact that workers’ share of national income has been failing. But they continue to formulate stories that deflect attention from the real problem, the relative immiseration of workers that has them falling further and further behind.

plumber-cartoon-cropped

Apparently, the latest attempt to redefine the role of economists is to encourage them to be plumbers.

Maybe it’s just my age but, when I read plumbers, I immediately think of the covert Special Investigations Unit in the Nixon White House—the operation that began with attempting to stop the leak of classified information (such as the Pentagon Papers) and then branched into illegal activities while working for the Committee to Re-elect the President (including the Watergate break-in).

I don’t think that’s what MIT economist Esther Duflo (pdf) had in mind when, in her Ely Lecture to the American Economic Association meeting last month, she suggested that economists seriously engage with plumbing, “in the interest of both society and our discipline.”

As economists increasingly help governments design new policies and regulations, they take on an added responsibility to engage with the details of policy making and, in doing so, to adopt the mindset of a plumber. Plumbers try to predict as well as possible what may work in the real world, mindful that tinkering and adjusting will be necessary since our models gives us very little theoretical guidance on what (and how) details will matter.

I’ll admit, I have a lot of respect for plumbers (especially when they’re able to fix the mess I’ve made trying to repair an existing fixture or install a new one). And I do think anyone involved in designing new policies and regulations should learn more about how they are actually implemented.

But economists, especially mainstream economists (of the sort Duflo is speaking for and to), are the last people I’d call in to fix the policy plumbing. Me, I’d pay them a large sum of money to learn about how policy formulation and implementation actually works. And then I’d pay them even more not to get anywhere near the process.

I’d much prefer that others—from the people actually affected by the policies to representatives from other academic disciplines and areas (such as anthropology, labor studies, peace studies, and so on)—be the ones who actually engage with the details of policy-making.

A good example of why I would want mainstream economists to be kept as far as possible away from the process of policy and implementation is a recent piece by Laura Tyson and Susan Lund.*

Their view is that capitalist globalization has had “disruptive effects on millions of advanced-economy workers” (and, we should add, on millions of workers—peasants, wage-laborers, and others—in economies that are not so advanced) and has aggravated income inequality within countries. So far so good.

But then they assert, without evidence, that the main culprit is not how globalization has been carried out, but technological change, which “automates routine manual and cognitive tasks, while increasing demand (and wages) for highly skilled workers.”

And because they take technological change as a given (rather than a strategy on the part of employers to boost profits), they recommend that workers (who, they presume, have no say in the development and implementation of new technologies) are the ones who need to adapt.

advanced economies must help workers acquire the skills needed to fill high-quality jobs in the digital economy. Lifelong learning cannot just be a slogan; it must become a reality. Mid-career retraining must be made available not only to those who have lost their jobs to foreign competition, but also to those facing disruption from the continuing march of automation. Training programs should be able to impart new skills in a matter of months, not years, and they should be complemented by programs that support workers’ incomes during retraining, and that help them relocate for more productive work.

Now, it’s true, Tyson and Lund don’t spend any time on the plumbing of creating and implementing lifelong learning programs. But that’s not the problem. Even if they were good economic plumbers, we’d still end up with a situation in which employers set the agenda and workers are forced to have the freedom to scramble to try to keep up.

That’s the plumbing Tyson and Lund leave out of their analysis. It’s what keeps the extra value flowing from workers to their employers. And, if workers are no longer useful for creating that extra value, they’re simply flushed down the drain.

If and when mainstream economists are willing to talk about those parts of the economic system, I’ll be the first to invite them to join the plumbers’ union.

But only, until they prove they can analyze and fix the problem, as plumber apprentices.

 

*This is not to pick on Tyson and Lund. I could have chosen any one of an almost infinite number of essays on economic policy by mainstream economists I’ve read over the years. Theirs just happens to be the latest I’ve run across.

4507289792_c749d647ca_b

Actually, robots do kill people.

A 21 year old external contractor was installing the robot together with a colleague when he was struck in the chest by the robot and pressed against a metal plate. He later died of his injuries, reports Chris Bryant, the FT’s Frankfurt correspondent.

While we certainly need to be aware of industrial accidents associated with robots, what we really need to be more concerned about is the relationship between the use of robotics and the metaphorical killing of workers via the elimination of their jobs.

Richard Baldwin [ht: ja], president of the Centre for Economic Policy Research and Editor-in-Chief of Vox (VoxEU.org, which he founded in June 2007), appears to agree:

Technological advances could now mean white-collar, office-based workers and professionals are at risk of losing their jobs

But, he argues, those who expect Brexit or the kinds of protectionist policies advocated by President Trump to bring back manufacturing jobs are sadly mistaken.

I think he’s right. Blaming international trade and immigration for the precarious plight of the working-class within advanced nations is wrongheaded.* Moreover, as Baldwin explains elsewhere, “We shouldn’t try and protect jobs; we should protect workers.”

However, the mistake Baldwin and other technological optimists make is to treat industrial robots (and their contemporary extensions, such as telepresence and telerobotics) in a purely instrumental fashion, as both inevitable and technically neutral. Just like the ubiquitous NRA bumper sticker: “Guns Don’t Kill People, People Kill People.”

As Bruno Latour (pdf) has explained, the NRA “cannot maintain that the gun is so neutral an object that is has no part in the act of killing.”

You are different with a gun in hand; the gun is different with you holding it. You are another subject because you hold the gun; the gun is another object because it has entered into a relationship with you. The gun is no longer the gun-in-the-armory or the gun-in-the-drawer or the gun-in-the-pocket, but the gun-in-your-hand, aimed at someone who is screaming. What is true of the subject, of the gunman, is as true of the object, of the gun that is held. A good citizen becomes a criminal, a bad guy becomes a worse guy; a silent gun becomes a fired gun, a new gun becomes a used gun, a sporting gun becomes a weapon.

And much the same is true of robotics. Employers are different when they have access to robots. They are another subject because they can reconfigure production by purchasing and installing robots; and robots are different objects when they enter into a relationship with employers, who stand opposed to their workers.

So, as it turns out, “it is neither people nor guns that kill” people. And, by the same token, it is neither employers nor robots that kill workers and their jobs. Responsibility for the action must be shared between the two—the employers who utilize robotics to increase productivity and raise profits, and the robots that are engineered, produced, and then sold for particular purposes, like transforming jobs and replacing workers.

So, yes, we shouldn’t try and protect jobs. Instead, we should protect workers. But the only way to protect workers is to create institutions for workers to be able to protect themselves. Leaving the European Union and electing Trump won’t do that. They are merely empty promises. Nor, as Baldwin presumes, will leaving robots in the hands of employers and expecting government programs to pick up the pieces.

It is still the case that most people are forced to have the freedom to attempt to sell their ability to work to a small group of employers, who have the option of using robots to replace them—across the globe—if and when they deem it profitable.

What that means is: robots and their employers do kill workers. Because of profits.

 

*And, as the United Nations Conference on Trade and Development (pdf) warns, “the increased use of robots in developed countries risks eroding the traditional labour cost advantage of developing countries.” That’s another reason to be cautious when it comes to facile predictions that the combination of globalization and robotics will be an unqualified advantage to workers in the Global South.

0002f56b_medium

Last year, as I reported the other day, I published over 800 new posts.

I’ve never done this before. However, I decided to look back over the year and choose one post for each month of 2016:

January—Liberal ideology

February—Who are the capitalists?

March—Yea, they’re angry!

April—Life among the liberal econ

May—Letting capitalism off the hook

June—Globalization, inequality, and imperialism

July—Trump and the Prosperity Gospel

August—The Mandibles and dystopian finance fiction

September—What about the white working-class?

October—Nobel economics—or why does capital hire labor?

November—Condition of the working-class in the United States

December—China syndrome

Enjoy!

alec

Alec Monopoly, “Flying Monopoly” (2015)

In the second installment of this series on “class before Trumponomics,” I argued that, in recent decades, while American workers have created enormous wealth, most of the increase in that wealth has been captured by their employers and a tiny group at the top—as workers have been forced to compete with one another for new kinds of jobs, with fewer protections, at lower wages, and with less security than they once expected. And the period of recovery from the Second Great Depression has done nothing to change that fundamental dynamic.

In this post, I want to focus on a more detailed analysis of the other side of the class relationship—capital.

fire

It should come as no surprise that one of the major changes in U.S. capital over the past few decades is the growing importance of financial activities. Since 1980, FIRE (finance, insurance, and real estate) has almost doubled, expanding from roughly 12 percent of the gross output of private industries to over 20 percent.

finance

And the rise in the share of corporate profits from financial activities was even more spectacular—from 10.8 percent in 1984 to a whopping 37.4 percent in 2002—and then falling during the crash, but still at a historically high 26.6 percent in 2015.

By any measure, U.S. capital became increasingly oriented toward finance beginning in the early 1980s—as traditional banks (deposit-gathering commercial banks), non-bank financial entities (especially shadow banking, such as investment banks, hedge funds, insurers and other non-bank financial institutions), and even the financial arm of industrial corporations (such as the General Motors Acceptance Corporation, now Ally Financial) absorbed and then profited by creating new claims on the surplus.

This process of “financialization” was the flip side of the decreasing labor share in the U.S. economy: On one hand, stagnant wages meant both an increasing surplus, which could be recycled via the financial sector, and a growing market for loans, as workers sought to maintain their customary level of consumption via increasing indebtedness. On the other hand, the production of commodities (both goods and services) became less important than capturing a portion of the surplus from around the world, and utilizing it via issuing loans and selling derivatives to receive even more.

international

Not only did finance become increasingly internationalized, so did the U.S. economy as a whole. As a result of employers’ decisions to outsource the production of commodities that had previously been manufactured in the United States and to find external markets for the sale of other commodities (especially services), and with the assistance of the lowering of tariffs and the signing of new trade agreements, the U.S. economy was increasingly opened up from the early-1970s onward. One indicator of this globalization is the increase in the weight of international trade (the sum of exports and imports) in relation to U.S. GDP—more than tripling between 1970 (9.33 percent) to 2014 (29.1 percent).

bank-concentration

The third major change in U.S. capital in recent decades is a rise in the degree of corporate concentration and centralization—to such an extent even the President’s Council of Economic Advisers (pdf) has taken notice. A wave of mergers and acquisitions has made firms larger and has increased the degree of market concentration within a broad range of industries. In finance, for example, the market share of the five largest banks (measured in terms of their assets as a share of total commercial banking assets) more than doubled between 1996 and 2014—rising from 23.2 percent to 47.9 percent.

airlines

The U.S. airline industry also experienced considerable merger and acquisition activity, especially following deregulation in 1978. The figure above (from a report by the U.S. Government Accountability Office [pdf]) provides a timeline of mergers and acquisitions for the four largest surviving domestic airlines—American, Delta, Southwest, and United—based on the number of passengers served. These four airlines accounted for approximately 85 percent of total passenger traffic in the United States in 2013.

profits-interest

Another piece of evidence that concentration and centralization have increased within the U.S. economy is (following Jason Furmanthe growing gap between corporate profits and interest-rates. The fact that corporate profits (as a share of national income, the top line in the chart above) have risen while interest-rates (the nominal constant-maturity 1-year rate estimated by the Federal Reserve, less inflation defined by the Consumer Price Index, the bottom line in the chart above) indicates that the portion of profits created by oligopoly rents has grown in recent decades.*

fire-mfg

Together, the three main tendencies I have highlighted—financialization, internationalization, and corporate rents—indicate a fundamental change in U.S. capital since the 1980s, which has continued during the current recovery. One of the effects of those changes is a decline in the importance of manufacturing, especially in relation to FIRE, as can be seen in the chart above. Manufacturing (as measured by value added as a percentage of GDP) has declined from 22.9 percent (in 1970) to 12 percent (in 2015), while FIRE moved in the opposite direction—from 14.2 percent to 20.3 percent. Quantitatively, the two sectors have traded places, which qualitatively signifies a change in how U.S. capital manages to capture the surplus. While it still appropriates surplus from its own workers (although now more in the production and export of services than in manufacturing), it now captures the surplus, from workers inside and outside the United States, via financial activities. On top of that, the largest firms are capturing additional portions of the surplus from other, smaller corporations via oligopoly rents.

13205

source

What we’ve witnessed then is a fundamental transformation of U.S. capital and thus the U.S. economy, which begins to explain a whole host of recent trends—from the decrease in rates of economic growth (since capital is engaged less in investment than in other activities, such as stock buybacks, hoarding profits in the form of cash, and mergers and acquisitions) to the rise in corporate executive pay in relation to average worker pay (which has ballooned, from 29.9 in 1978 to 275.6 in 2015).

What is clear is that the decisions of U.S. capital as it changed over the course of recent decades created the conditions for the crash of 2007-08 and the unevenness of the subsequent recovery, which culminated in the victory of Donald Trump in November 2016.

 

*Another way to get at these oligopoly rents is to distinguish between the capital share and the profit share. According to Simcha Barkai (pdf), the decline in the labor share over the last 30 years was not offset by an increase in the capital share, which actually declined. But it was accompanied by an increase in the profit share, due to a rise in mark-ups.

10

Mark Tansey, “Coastline Measure” (1987)

The pollsters got it wrong again, just as they did with the Brexit vote and the Colombia peace vote. In each case, they incorrectly predicted one side would win—Hillary Clinton, Remain, and yes—and many of us were taken in by the apparent certainty of the results.

I certainly was. In each case, I told family members, friends, and acquaintances it was quite possible the polls were wrong. But still, as the day approached, I found myself believing the “experts.”

It still seems, when it comes to polling, we have a great deal of difficult with uncertainty:

Berwood Yost of Franklin & Marshall College said he wants to see polling get more comfortable with uncertainty. “The incentives now favor offering a single number that looks similar to other polls instead of really trying to report on the many possible campaign elements that could affect the outcome,” Yost said. “Certainty is rewarded, it seems.”

But election results are not the only area where uncertainty remains a problematic issue. Dani Rodrik thinks mainstream economists would do a better job defending the status quo if they acknowledged their uncertainty about the effects of globalization.

This reluctance to be honest about trade has cost economists their credibility with the public. Worse still, it has fed their opponents’ narrative. Economists’ failure to provide the full picture on trade, with all of the necessary distinctions and caveats, has made it easier to tar trade, often wrongly, with all sorts of ill effects. . .

In short, had economists gone public with the caveats, uncertainties, and skepticism of the seminar room, they might have become better defenders of the world economy.

To be fair, both groups—pollsters and mainstream economists—acknowledge the existence of uncertainty. Pollsters (and especially poll-based modelers, like one of the best, Nate Silver, as I’ve discussed here and here) always say they’re recognizing and capturing uncertainty, for example, in the “error term.”

silver

Even Silver, whose model included a much higher probability of a Donald Trump victory than most others, expressed both defensiveness about and confidence in his forecast:

Despite what you might think, we haven’t been trying to scare anyone with these updates. The goal of a probabilistic model is not to provide deterministic predictions (“Clinton will win Wisconsin”) but instead to provide an assessment of probabilities and risks. In 2012, the risks to to Obama were lower than was commonly acknowledged, because of the low number of undecided voters and his unusually robust polling in swing states. In 2016, just the opposite is true: There are lots of undecideds, and Clinton’s polling leads are somewhat thin in swing states. Nonetheless, Clinton is probably going to win, and she could win by a big margin.

slide_24

As for the mainstream economists, while they may acknowledge exceptions to the rule that “everyone benefits” from free markets and international trade in some of their models and seminar discussions, they acknowledge no uncertainty whatsoever when it comes to celebrating the current economic system in their textbooks and public pronouncements.

So, what’s the alternative? They (and we) need to find better ways of discussing and possibly “modeling” uncertainty. Since the margins of error, different probabilities, and exceptions to the rule are ways of hedging their bets anyway, why not just discuss the range of possible outcomes and all of what is included and excluded, said and unsaid, measurable and unmeasurable, and so forth?

The election pollsters and statisticians may claim the public demands a single projection, prediction, or forecast. By the same token, the mainstream economists are no doubt afraid of letting the barbarian critics through the gates. In both cases, the effect is to narrow the range of relevant factors and the likelihood of outcomes.

One alternative is to open up the models and develop a more robust language to talk about fundamental uncertainty. “We simply don’t know what’s going to happen.” In both cases, that would mean presenting the full range of possible outcomes (including the possibility that there can be still other possibilities, which haven’t been considered) and discussing the biases built into the models themselves (based on the assumptions that have been used to construct them). Instead of the pseudo-rigor associated with deterministic predictions, we’d have a real rigor predicated on uncertainty, including the uncertainty of the modelers themselves.

Admitting that they (and therefore we) simply don’t know would be a start.