Friday, October 11, 2019

What Economists (Including Me) Got Wrong About Globalization [feedly]

Krugman: What Economists (Including Me) Got Wrong About Globalization
https://www.bloomberg.com/amp/opinion/articles/2019-10-10/inequality-globalization-and-the-missteps-of-1990s-economics


This column is adapted from a chapter in "Meeting Globalization's Challenges" (Princeton University Press), a collection of papers by scholars who contributed to a conference at the International Monetary Fund on Oct. 11, 2017. The book will be published on Nov. 4.

Concerns about adverse effects from globalization aren't new. As U.S. income inequality began rising in the 1980s, many commentators were quick to link this new phenomenon to another new phenomenon: the rise of manufactured exports from newly industrializing economies.

Economists took these concerns seriously. Standard models of international trade say that trade can have large effects on income distribution: A famous 1941 paper showed how trading with a labor-abundant economy can reduce wages, even if national income grows.

And so during the 1990s, a number of economists, myself included, tried to figure out how much the changing trade landscape was contributing to rising inequality. They generally concluded that the effect was relatively modest and not the central factor in the widening income gap. So academic interest in the possible adverse effects of trade, while it never went away, waned.

In the past few years, however, worries about globalization have shot back to the top of the agenda, partly due to new research and partly due to the political shocks of Brexit and U.S. President Donald Trump. And as one of the people who helped shape the 1990s consensus — that the contribution of rising trade to rising inequality was real but modest — it seems appropriate for me to ask now what we missed.

The 1990s Consensus

There was confusion and debate during the mid-1990s over how to use data on trade to assess wage impacts. Most studies focused on the volume of trade and the amount of labor and other resources embedded in imports and exports. Some economists objected to this approach, preferring to focus on prices rather than quantities.

What eventually emerged was a "but for" approach: asking how different wages would have been but for the rise of manufactured exports from developing countries — increases that were minimal in 1970 but higher by the mid-1990s. It turned out that imports of manufactured goods from developing countries, while much larger than in the past, were still small relative to the size of advanced economies — around 2% of their gross domestic products. This wasn't enough to cause more than a modest change in relative wages. The effect wasn't trivial, but it wasn't big enough to be a central economic story, either.
Hyperglobalization

These assessments of the impact of trade made around 1995, inevitably relying on data from a couple of years earlier, were probably correct in finding modest effects. In retrospect, however, trade flows in the early 1990s were just the start of something much bigger, or what a 2013 paper by economists Arvind Subramanian and Martin Kessler called hyperglobalization.

Until the 1980s, it was arguable that the growth of world trade since World War II had mainly reflected a dismantling of the trade barriers erected before the war; world trade as a share of world GDP was only slightly higher than it had been in 1913. Over the next two decades, however, both the volume and nature of trade moved into uncharted territory.

This chart shows one indicator of this change: manufactured exports from developing countries, measured as a share of world GDP. What seemed in the early 1990s like a major disturbance in the trade force was just the beginning.

Something Was Happening

What caused this huge surge in what was, in the 1990s, still a fairly novel form of trade? The answer probably includes a combination of technology and policy. Freight containerization was not exactly new, but it took time for businesses to realize how the reduction in transshipping costs made it possible to move labor-intensive parts of the production process overseas. Meanwhile, China made a dramatic shift from central planning to a market economy focused on exports.

Since manufactured exports from developing countries, measured as a share of the world economy, are now triple what they were in the mid-1990s, should we conclude that the effect on income distribution has also tripled? Probably not, for at least two reasons.

First, a significant part of the increase in developing-country exports reflects the rapid growth of trade among the modernizing economies of Asia, Africa and Latin America. That's an important story, but it's not relevant to the impact on advanced-country workers. Even more important, though, the nature of this trade growth — involving goods made by both unskilled and highly skilled workers — means that the value of the labor involved in North-South trade hasn't risen nearly as fast as the volume.

Consider two cases: imports of apparel from Bangladesh and imports of iPhones from China. In the first instance, we are in effect importing the services of less educated workers, putting downward pressure on the demand for such workers in the U.S. In the second case, though, most of the value of the iPhone reflects work done in high-wage, high-education countries like Japan; we are in effect importing skilled as well as unskilled labor, so the impact on income distribution should be much smaller.

Despite these qualifications, it's clear that the impact of developing-country exports grew much more between 1995 and 2010 than the 1990s consensus imagined possible, which may be one reason concerns about globalization made a comeback.

Trade Imbalances

One contrast between the way scholars measure globalization's impact and the way the broader public looks at it — the approach taken by Trump, for example — is the focus on trade imbalances. The public tends to see trade surpluses or deficits as determining winners and losers. But the economic trade models that underlay the 1990s consensus gave no role to trade imbalances at all.

The economists' approach is almost certainly right for the long run, both because countries must pay their way eventually, and because trade imbalances mainly affect the relative shares of traded and nontraded sectors in employment, with no clear effect on the overall demand for labor. Yet rapid changes in trade balances can cause serious problems of adjustment — a broader theme that I'll return to shortly.

Consider, in particular, the comparison between the U.S. non-oil trade balance (which is overwhelmingly manufactured goods) and U.S. manufacturing employment:

The 2000 Import Shock

Until the late 1990s, employment in manufacturing, although steadily falling as a share of total employment, had remained more or less flat in absolute terms. But manufacturing employment fell off a cliff after 2000, and this decline corresponded to a sharp increase in the non-oil deficit.

Does the surge in the trade deficit explain the fall in employment? Yes, a lot of it. A reasonable estimate is that the deficit surge reduced the share of manufacturing in GDP by around 1.5 percentage points, or more than 10%, which means that it explains more than half the roughly 20% decline in manufacturing employment between 1997 and 2005.

This is over a relatively short time period and focuses on absolute employment, not the employment share. Trade deficits explain only a small part of the long-term shift toward a service economy. But soaring imports did impose a shock on some U.S. workers, which may have helped cause the globalization backlash.

Rapid Globalization and Disruption

The pro-globalization consensus of the 1990s, which concluded that trade contributed little to rising inequality, relied on models that asked how the growth of trade had affected the incomes of broad classes of workers, such as those who didn't go to college. It's possible, and probably even correct, to think of these models as accurate in the long run. Consensus economists didn't turn much to analytic methods that focus on workers in particular industries and communities, which would have given a better picture of short-run trends. This was, I now believe, a major mistake — one in which I shared a hand.

It should have been obvious that the politics of globalization were likely to be much more influenced by the experience of individual sectors that gained or lost from shifting trade flows than by big questions of how trade affects the global blue-collar/white-collar wage gap or the broad statistical measure of inequality known as the aggregate Gini coefficient.

This is where the now-famous 2013 analysis of the "China shock" by David Autor, David Dorn and Gordon Hanson comes in. What they mainly did was shift focus from broad questions of global income distribution to the effects of rapid import growth on local labor markets, showing that these effects were large and persistent. This represented a new and important insight.

To make partial excuses for those of us who failed to consider these issues 25 years ago, at the time we had no way to know that either the hyperglobalization that began in the 1990s or the trade-deficit surge a decade later were going to happen. And without the combination of these developments, the China shock would have been much smaller. Still, we missed a crucial part of the story.

A Case for Protectionism?

What else did the 1990s consensus miss? A lot. Developing-country exports of manufactured goods grew far beyond their level at the time that consensus emerged. The combination of this rapid growth and surging trade imbalances meant that globalization produced far more disruption and cost for some workers than the consensus had envisaged.


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Friday, October 4, 2019

Zuckerberg: No One Deserves to Be a Billionaire, But It’s Useful [feedly]

  Zuckerberg: No One Deserves to Be a Billionaire, But It's Useful
https://www.bloomberg.com/news/articles/2019-10-04/zuckerberg-no-one-deserves-to-be-a-billionaire-but-it-s-useful  


moderator


This post is testimony to the great influence Thomas Piketty's analysis of modern capitalism has had, and continues to have, on both the economics profession and politics. Both Sanders and Warren economic programs draw heavily on Piketty and Emmanuel Saez theoretical and policy work on aggravated inequality trends. One of their conclusions, which left wing candidates have embraced, is: "there should be no billionaires". I am always tempted to ask: "Should there also be no poverty?" I am sure both Piketty and Saez would agree. But I am not sure Piketty's equations on profit and wealth predict that exact outcome. They show that capital (weath) accumulation and its political side effects with respect to power, are inexorable, but CAN be offset by taxation.

Both Zuckerberg and Bill Gates have essentially made the same reply to Piketty (Gates did a live interview with him and holds him in high regard). "I agree that income should be taxed progressively. But why wealth? Great concentrations of wealth make vast projects, like climate change, or poverty, possible to address. Even if I am taxed, capital must accumulate to do big things. Why are my decisions worse than what a government agency is making now?"

Piketty makes a (now somewhat famous in econ circles) reply: "If you are right, perhaps instead of taxing or prohibiting "billionaires", we should not tax or constrain them at all?"

Gates: "You have a point." A truly double-edged conversation.

Interesting differences between Marx and Piketty include the former's philosophical and analytical training, and the latter's focus on data. Marx's philosophical materialism tends toward instrumentalism, especially in later years. Instrumentalism maintains that the truth of an idea is determined by its success in the active solution of a problem, and that the value of an idea is determined by its function in human experience. In Marx capital is a social but nonetheless material force. Individual humans make choices but they are constrained by competing economic forces. The economic system, in this sense, requires X investors and Y wage and salary workers. If the system does not provide a Z, you do not get to choose it. Thus, for Marx, Gates', or Zuckerberg's 100 Billion dollars is a force in its own right. Gates or Zuckerberg are as much its agent as owner.

Last thought, this morning: Even if the "billionaire" is banned, capital will still seek to accumulate in other forms, perhaps corporate, or sovereign wealth funds. Even when taxed, the tendency toward accumulation will not be exterminated.


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Facebook Inc. Chief Executive Officer Mark Zuckerberg, the fifth-richest person in the world, was asked by an employee to respond to an assertion by U.S. presidential candidate Bernie Sanders that billionaires shouldn't exist. Zuckerberg conceded that they probably shouldn't.

"No one deserves that much money," Zuckerberg said. "I think if you do something that's good, you get rewarded, but I do think some of the wealth that can be accumulated is unreasonable." 

Zuckerberg, who has a net worth of $69.4 billion, was speaking late Thursday at an internal question-and-answer meeting that he decided to stream live to the public, after audio of similar Q&A meetings earlier this year was leaked. The employee at Thursday's meeting said he was asking Zuckerberg "as the only billionaire with whom I can consult on this matter."

The Facebook co-founder went on to explain that his philanthropic investment arm, the Chan Zuckerberg Initiative, has been making bets on scientific advancements with the goal of eradicating all disease in the next century. The firm's investments might happen more slowly or might never happen through public money, Zuckerberg said, so he is trying to make his billionaire status useful.

"The suggestion that this should all be done publicly, I think, would deprive the market and world from a diversity of different attempts that can be taken," he told employees.

On Tuesday, Sanders unveiled a proposal for a steep tax on billionaires, taking aim at a person's accumulated wealth, not just income.


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Thursday, October 3, 2019

Here Comes the Trump Slump [feedly]

Here Comes the Trump Slump
https://www.nytimes.com/2019/10/03/opinion/trump-economy.html

text oly

When he isn't raving about how the deep state is conspiring against him, Donald Trump loves to boast about the economy, claiming to have achieved unprecedented things. As it happens, none of his claims are true. While both G.D.P. and employment have registered solid growth, the Trump economy simply seems to have continued a long expansion that began under Barack Obama. In fact, someone who looked only at the past 10 years of data would never guess that an election had taken place.

But now it's starting to look as if Trump really will achieve something unique: He may well be the first president of modern times to preside over a slump that can be directly attributed to his own policies, rather than bad luck.

There has always been a deep unfairness about the relationship between economics and politics: Presidents get both credit and blame for events that usually have little to do with their actions. Jimmy Carter didn't cause the stagflation that put Ronald Reagan in the White House; George H.W. Bush didn't cause the economic weakness that elected Bill Clinton; even George W. Bush bears at most tangential responsibility for the 2008 financial crisis.

More recently, the "mini-recession" of 2015-16, a slump in manufacturing that may have tipped the scale to Trump, was caused mainly by a plunge in energy prices rather than any of Barack Obama's policies.


Now the U.S. economy is going through another partial slump. Once again, manufacturing is contracting. Agriculture is also taking a severe hit, as is shipping. Overall output and employment are still growing, but around a fifth of the economy is effectively in recession.

But unlike previous presidents, who were just unlucky to preside over slumps, Trump has done this to himself, largely by choosing to wage a trade war he insisted would be "good, and easy to win."

The link between the trade war and agriculture's woes is obvious: America's farmers are deeply dependent on export markets, China in particular. So they're hurting badly, despite a huge financial bailout that is already more than twice as big as the Obama administration's auto bailout. (Part of the problem may be that the bailout money is flowing disproportionately to the biggest, richest farms.)

Shipping may also seem an obvious victim when tariffs reduce international trade, although it's not just an international issue; domestic trucking is also in recession.

The manufacturing slump is more surprising. After all, America runs a large trade deficit in manufactured goods, so you might expect that tariffs, by forcing buyers to turn to domestic suppliers, would be good for the sector. That's surely what Trump and his advisers thought would happen.



But that's not how it has worked out. Instead, the trade war has clearly hurt U.S. manufacturing. Indeed, it has done considerably more damage than even Trump critics like yours truly expected.

[For an even deeper look at what's on Paul Krugman's mind, sign up for his weekly newsletter.]

The Trumpist trade warriors, it turns out, missed two key points. First, many U.S. manufacturers depend heavily on imported parts and other inputs; the trade war is disrupting their supply chains. Second, Trump's trade policy isn't just protectionist, it's erratic, creating vast uncertainty for businesses both here and abroad. And businesses are responding to that uncertainty by putting plans for investment and job creation on hold.

So the tweeter in chief has bungled his way into a Trump slump, even if it isn't a full-blown recession, at least so far. It's clearly going to hurt him politically, notably because of the contrast between his big talk and not-so-great reality. Also, the pain in manufacturing seems to be falling especially hard on those swing states Trump took by tiny margins in 2016, giving him the Electoral College despite losing the popular vote.

And while many presidents have found themselves confronting politically damaging economic adversity, Trump is, as I said, unique in that he really did this to himself.

Of course, that doesn't mean that he will accept responsibility for his mistakes. For the past few months he has been trying to portray the Federal Reserve as the root of all economic evil, even though current interest rates are well below those his own officials predicted in their triumphalist economic projections.

My guess, however, is that Fed-bashing will prove ineffective as a political strategy, not least because most Americans probably have at best a vague idea of what the Fed is and what it does.

So what will come next? Trump being Trump, it's a good bet that he'll soon be denouncing troubling economic data as fake news; I wouldn't be surprised to see political pressure on the statistical agencies to report better numbers. Hey, if it can happen to the National Weather Service, why not the Bureau of Economic Analysis (which reports, by the way, to Wilbur Ross)?



And somehow or other this will turn out to be another deep-state conspiracy, probably orchestrated by George Soros.

The scary thing is that around 35 percent of Americans will probably believe whatever excuses Trump comes up with. But that won't be enough to save him.

The Times is committed to publishing a diversity of letters to the editor. We'd like to hear what you think about this or any of our articles. Here are some tips. And here's our email: letters@nytimes.com.

Follow The New York Times Opinion section on Facebook, Twitter (@NYTopinion) and Instagram.

Paul Krugman has been an Opinion columnist since 2000 and is also a Distinguished Professor at the City University of New York Graduate Center. He won the 2008 Nobel Memorial Prize in Economic Sciences for his work on international trade and economic geography. @PaulKrugman




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Jared Bernstein: Got work? The highly responsive labor supply of low-income, prime-age workers. [feedly]

Got work? The highly responsive labor supply of low-income, prime-age workers.
http://jaredbernsteinblog.com/got-work-the-highly-responsive-labor-supply-of-low-income-prime-age-workers/


[Note: this is draft of a forthcoming paper for CBPP's Full Employment Project. I posted it here first as I will be referencing its findings at a Brookings inflation conference on Thurs, Oct 3.]

By Jared Bernstein and Keith Bentele[i]

Introduction

The benefits to running a hot labor market continue to be evident both in the data and in anecdotal accounts. In our last paper, we examined the monetary policy rationale for allowing high-pressure labor markets to continue to flourish.[ii] We also focused on the benefits of persistently low unemployment to lower income workers, through both higher real pay and more hours of work. In this short paper, we turn back to this evidence, with a closer focus on the benefits of high-pressure labor markets to the labor supply of lower-paid workers.

The most basic labor market theories generally lack the necessary nuance to shed much light on this question. The textbook 101 model assumes full employment and an equilibrium wage where employers' demands' and undifferentiated workers' supply perfectly match. A wage set too high will lead to more job seekers than jobs; a wage set too low will cause the opposite problem: too few workers willing to fill available slots. In the real world, however, there are of course periods of slack labor markets, along with factors such as racial and gender discrimination. Some particularly disadvantaged workers may face uniquely high barriers to labor market entry. Also, recent research has identified large sectors in our economy, like retail, tech, and health care, where few employers dominate. In such markets, employers can become wage makers, not wage takers, i.e., they can use their dominance to set wages below the theoretical equilibrium.

In this note, we ask a simple, specific question related to this more realistic version of the labor market: do low-wage workers respond to high-pressure labor markets by increasing their labor supply? What evidence is there that tight job markets pull in such workers?

We find highly cyclical responses to both the extensive and intensive margins of labor supply for low-income, prime-age persons, especially for first-quintile African Americans and for women. A simple decomposition finds, for example, that the earnings of low-income Black people doubled in the high-pressure labor market of the 1990s, with gains in their share working (extensive margin) explaining half of the increase. Conversely, under low-pressure conditions, the decline in working shares dominates sharp income losses for these groups of people. We also find the extensive margin to be particularly important for low-income women, and a simple simulation suggests that in the hot labor market of the 1990s, most of the gains in the gender gap were due to women's relative (to men) gains along the extensive margin. We offer policy implications of these findings on both macro and micro levels.

Previous Literature

Arthur Okun is widely credited with pioneering research into the benefits of very low unemployment for marginalized groups. In the context of a "high-pressure economy" he hypothesized that employers are more likely to lower formal hiring standards in order to fill vacancies, and that this would benefit  less-advantaged job seekers in the labor market[iii]. In a 1973 paper Okun found that in such periods, women and teenagers experienced disproportionately large increases in employment. Since this initial confirmation of a rather straightforward hypothesis, many studies have reinforced this finding. The uniquely strong economy in the late-1990s prompted a body of work evaluating the impacts of these conditions. Roberts and Rodgers (2000) examined the impacts of low unemployment on earnings and employment in metro labor markets and found that less educated men, and young African American men in particular, experienced the greatest improvements[iv]. Similarly, Wilson (2015) explored the positive impacts of strong economic growth in the late-1990s on both the employment and earnings of African American people[v]. Katz and Krueger (1999) found that the tight labor market of the late-1990s contributed to a significant increase in the both the incomes of lower-income families and falling poverty rates in those years[vi]. Jargowsky's (2003) research captured a 24% decline in the number of people living in high-poverty neighborhoods, census tracts where 40% or more of residents are in poverty, between 1990 and 2000[vii]. This study found that the strong economy reduced the concentration of poverty for all racial and ethnic groups, but had a particularly pronounced effect on African American communities. The share of poor African American people living in high poverty neighborhoods fell from 30% in 1990 to 19% in 2000. Such impacts have informed William J Wilson's assertion that the "ideal solution" to addressing a root cause of concentrated poverty, inner-city joblessness, "would be economic policies that produce tight labor markets" (Wilson 2008:568)[viii].

The specific findings of greater cyclical variation in wages, employment, and labor market participation for economically vulnerable groups have been widely documented. Hoynes (2000) found this to be the case for the employment and earnings of less educated workers, people of color, and women with lower skill levels. All experienced more variation over the course of the business cycle relative to higher skilled men, a finding that was particularly pronounced in the context of one's probability of being employed full-time year round[ix]. Jefferson (2008) found that trends in the employment-to-population ratio for workers with less education are substantially more volatile compared to those with more educated workers [x]. And more recent research, including that which examines the current strong economy, has only further bolstered these findings. For example, Aaronson et al. (2019:3) state that their research,

"reaffirm[s] the earlier finding of other authors that the labor market outcomes of blacks, Hispanics, and those with less education are more cyclically sensitive than the outcomes of whites and those with more education."[xi]

And consistent with the work of Roberts and Rodgers (2000), they find that cyclical variability in labor market outcomes is particularly pronounced for young African American workers. Further, Aaronson et al. (2019) find suggestive evidence that further strengthening in the context of an already very strong economy is particularly beneficial to some disadvantaged groups.

The flip side of higher cyclical variability is that recessions hit low-wage workers and members of marginalized groups particularly hard. Decreases in earnings and employment during recessions are consistently disproportionately larger for low-wage earners, people of color, and low-income female-headed households[xii]. Kenworthy (2011) has stressed the devastating impact of recessions on hours worked by very low-income households, an issue compounded when followed by a weak recovery[xiii]. While the evidence is admittedly thin at this point, high-pressure labor markets may potentially play a small protective role in regards to this cyclical vulnerability. Aaronson et al. (2019) find that the gains made during high-pressure periods for Black people and women are "somewhat persistent". Similarly, Hotchkiss and Moore (2018) find that high-pressure periods lead to higher employment, wages, and earnings in subsequent downturns for young men and Black people. However, they stress that these specific positive benefits are largely confined to these groups and may be short lived.

Data

For a full description of the data used below, see our earlier paper. We use the same procedures and inclusion criteria to generate the estimates used here with only two important changes. First, previously we used household income from all sources to determine quintile thresholds, here we have used a measure of total household income adjusted for household size (household income/number of household members). Second, our estimates of annual hours worked are based on the average of individual-level data on hours worked (hours per week*weeks per year), as opposed to a quintile-level estimate of annual hours. We found that our inclusion of individuals with $0 earnings in our estimates of quintile level hours and weeks produced an underestimation of annual hours that was not present in the averaged individual-level estimate of annual hours.

Findings

While it is common for labor analysts to look at employment rates, such rates are generally overall averages, often by gender or race. Because our data is broken out by income fifth (and by gender and race), we can look at the share of prime-age people with positive annual work hours, meaning any reported paid work last year, by quintile.[xiv] As Figure 1 shows, consistent with prior research, the series for persons in the lowest fifth is much more cyclical than that for the middle or top fifth.

Figure 1.

In fact, simply using the unemployment rate (logged, with one lag) and the lagged first-quintile series in the above figure, we can derive a dynamic prediction that tracks the series well (See Figure 2).[xv] The share working exceeded the forecast in the latter 1990s, but this was a period when many "pro-work" policy changes affected low-income workers, including work requirements in TANF, a large expansion in the Earned Income Tax Credit, and an increase in the minimum wage. But it was also a high-pressure labor market period. Using the 2018 unemployment rate of 3.9 percent, the model forecasts a jump of about 5 percentage points in 2018.[xvi]

Figure 2.

Figure 3 examines the share of working African American people. Because of the smaller sample size, we plot the bottom 40 percent. These workers appear to be particularly elastic to high-pressure labor markets, with large employment gains in the 1990s and in the current recovery.

Figure 3.

In the appendix, we include similar figures for prime-aged men and women in the first quintile of adjusted household incomes. The cyclical patterns are roughly similar to the total figure above (the simple model tracks the series well), though as earlier research has shown, the women's series tends to trend up while that of men trends down due in part to structural challenges like the loss of production jobs.

Because we have earnings data and annual hours, we can decompose the earnings of low-income people into the share working (the "extensive margin"), annual hours among workers, and hourly wages (see Table 1).[xvii] By decomposing these changes over different time periods, we can observe how this group has fared in both high- and low-pressure labor markets and which factors have the greatest impact on real earnings growth.

Table 1. Real Earnings Contributions in High- and Low-Pressure Labor Markets

The first few panels look at high-pressure labor markets. Between 1993-2000, when the unemployment rate fell from 6.9 to 4 percent, the real, annual earnings for all low-income persons rose just under 50 percent (log points), from about $8,200 to $13,400. Importantly, we include those with zero hours, and thus zero earnings, in these calculations, so as to capture the impact on earnings of their crossing the extensive margin (going from zero to positive hours worked). As the first column shows, the share working increase 23 percent, and since this is an additive decomposition (the first three columns of the row "ln change" sum to the fourth column), this added labor supply explains almost half (23/49) of the earnings gain over this high-pressure period.

The second panel show the more recent period, 2011-2017, when unemployment fell from 8.9 percent to 4.4 percent. Real earnings were up about 30 percent over this period, meaning that on an annualized basis, real earnings grew 2 points faster in the 1990s high-pressure labor market (7 versus 5 percent per year) through 2017. The extensive and intensive margins, entry into employment and increased hours respectively, explain about one-third each, as does the growth in real hourly wages.

The next panel drills down into the experience of first-quintile African Americans in the high-pressure labor market of the 1990s, when Black unemployment fell from 13 percent to 7.6 percent and their real, annual earnings remarkably doubled, for an annual real growth rate of just under 15 percent per year. Fully half of that gain was due to an almost 50 percent increase in the share working, with the other half split between more annual hours by workers and higher real hourly wages.

It is important to turn to low-pressure labor markets to see how this process shifts into reverse. From 2007-11, the jobless rate rose from 4.6 to 8.9 percent, and first quintile real earnings fell almost 30 percent, with half the decline attributable to the fall in the share of workers from 67 to 58 percent. Compare this fall to the absence of change (not shown) for the top quintile over these years. In both 2007 and 2011, their prime-age share at work was 95 percent, a stark reminder of who bears the brunt of recessions.

African American unemployment about doubled, 2007-11, from about 8 to 16 percent. Black people in the first quintile lost almost half of their real earnings in this downturn, with three-fifths of the decline coming from the decline in the share working.

Turning back to the top fifth, the bottom panel of Table 1 shows how affluent, prime-age people are extremely inelastic regarding changes in labor supply. In fact, they're largely topped out in terms of annual hours worked and share working. Their average share working is 95 percent and the standard deviation around that mean over these years is  three-fifths of a percentage point, compared to a standard deviation of 6 points for the first quintile of all prime-age people (10 times that of the top fifth) and 10 points for the African American first quintile. These are profound differences in cyclical variability in employment.

Table 2 presents the same decomposition for first quintile, prime-age people by gender, looking at the high-pressure 1993-2000 period, the Great Recession, and the slow recovery of 2007-11. As shown in the appendix figures on share working by gender, low-income women are more cyclically responsive in these data, at least until around 2000, when both genders appear somewhat more elastic to the business cycle. The findings show that low-income women's extensive margin gains were particularly important in the 1990s, explaining 60 percent of their significant real earnings' gains (45/75). For men, however, that margin contributed little compared to more hours worked and higher real wages.

Table 2. Real Earnings Contributions in High- and Low-Pressure Labor Markets, by Gender

 

Table 3 does a simple simulation to parse out the role of crossing the extensive margin in reducing the gender wage gap in the high-pressure labor market of the 1990s. Note that the gender gap compressed by 23 percentage points in these years, from 39 percent in 1993 to 62 percent in 2000. A simple simulation (see footnote and table note) suggests that almost all of that closure was a function of the increase in women's share working.[xviii]

Table 3. Gender Inequality (Q1) and the Extensive Margin

Note: The 2000 simulated value (in bold) is the product of the 1993 share of women working and their 2000 hours and hourly wage.

In the low-pressure labor market panel, real earnings fell sharply for both genders, and in this case, the extensive margin dominates in both cases.

Conclusion

Our findings and those of other researchers, in tandem with extensive recent anecdotes from the media regarding new opportunities for left-behind workers, show that the labor supply of low-income workers, especially women and Black people, is highly elastic to labor market conditions, while that of high-income workers is much less so. In the high-pressure labor market of the latter 1990s, real annual earnings grew by half for all first quintile workers (including "zeros") and doubled for African American people. In both cases, the increase in the share working explained about half these gains.

The policy implications of these findings invoke both macro and micro policies. At the macro level, as we stressed in our earlier paper, running the labor market hotter-for-longer returns economically significant benefits to those who need them the most. From the perspective of the Federal Reserve's monetary policy, the additional fact that inflation has proven to be quite insensitive to low unemployment seals the deal: as long as inflation remains "well-anchored," for vulnerable workers to get ahead, we can and should pursue full employment.

At the micro level, our findings speak strongly against the notion that receipt of anti-poverty benefits should be conditional on the work requirements that have recently surfaced in various states, for example, through federal waivers to the Medicaid program. Low-income workers have already been highly responsive to job opportunities; the problem is that those opportunities either don't exist in slack labor markets, or they face internal (skill deficits) or external (discrimination) barriers to getting into the job market. Hassling them off of the benefit rolls by making them jump through administration hoops will not lead them to work more, but it will surely diminish their income and their health.

Appendix 

Table A.1

Table A.2

 

 

[i] We thank Jesse Rothstein for comments and Kathleen Bryant for technical assistance. Any mistakes are our own.

[ii]  Jared Bernstein and Keith Bentele, "The Increasing Benefits and Diminished Costs of Running a High-Pressure Labor Market," Center on Budget and Policy Priorities: Full Employment Project, May 15, 2019, https://www.cbpp.org/research/full-employment/the-increasing-benefits-and-diminished-costs-of-running-a-high-pressure.

[iii] Okun, Arthur M. 1973."Upward Mobility in a High-pressure Economy." Brookings Papers on Economic Activity. 1:207-261.

[iv] Cherry, Robert and William M. Rodgers III (eds.) 2000. Prosperity for All? The Economic Boom and African Americans. New York: Russell Sage Foundation.

[v] Wilson, Valerie. 2015. "The Impact of Full Employment on African American Employment and

Wages," Economic Policy Institute.

[vi] Katz, Lawrence, and Alan Krueger. 1999. "The High-Pressure U.S. Labor Market of the 1990s." Brookings Papers on Economic Activity. 1:1-87.

[vii] Paul Jargowsky. 2003.  "Stunning Progress, Hidden Problems: The Dramatic Decline of Concentrated Poverty in the 1990s." The Brookings Institution.

[viii] William Julius Wilson. 2008-09. "The Political and Economic Forces Shaping Concentrated Poverty." Political Science Quarterly. 123(4):555-571.

[ix] Hoynes, Hilary. 2000. "The Employment and Earnings of Less Skilled Workers Over the Business Cycle." in Finding Jobs: Work and Welfare Reform, edited by Rebecca Blank and David Card. New York: Russell Sage Foundation.

[x] Jefferson, Philip N. 2008. "Educational Attainment and the Cyclical Sensitivity of

Employment." Journal of Business and Economic Statistics 26(4):526-35.3

[xi] Aaronson, Stephanie R., Mary C. Daly, William Wascher &  David W. Wilcox. 2019. "Okun Revisited: Who Benefits Most From a Strong Economy?" Brookings Papers on Economic Activity. BPEA Conference Drafts.

[xii] Aaronson, Stephanie R., Mary C. Daly, William Wascher &  David W. Wilcox. 2019. "Okun Revisited: Who Benefits Most From a Strong Economy?" Brookings Papers on Economic Activity. BPEA Conference Drafts.

Bentele, Keith G. 2012. "Evaluating the Performance of the U.S. Social Safety Net in the Great Recession." Center for Social Policy Publications. Paper 62.

Cajner, Tomaz, Tyler Radler, David Ratner, and Ivan Vidangos. 2017. "Racial Gaps in Labor Market Outcomes in the Last Four Decades and over the Business Cycle." Working Paper 2017-071. Finance and Economics Discussion Series. Washington, D.C.: Federal Reserve Board.

Zavodny, Madeline, and Tao Zha. 2000. "Monetary Policy and Racial Unemployment Rates." Federal Reserve Bank of Atlanta Economic Review 85(4):1–59.

[xiii] Kenworthy, Lane. 2011. Progress for the Poor. New York: Oxford University Press.

[xiv] Note that this is a somewhat different metric than the oft-cited prime-age employment rate from BLS. The measure asks if people are working in the reference week of the month; this one asks if people had any positive work hours over the course of the prior year. The latter tends to have a higher level, but the trends are roughly similar.

[xv] "Dynamic" in this context means the lagged dependent variable is predicted (versus plugging in the actual value) for each observation in the predicted series.

[xvi] We plan to shortly update this analysis with the recently released 2018 data.

[xvii] Annual earnings for all prime-age persons in the quintile (assigning zeros to non-workers) is the product of the
share working*annual hours*hourly wage. Taking log changes facilitates the decomposition.

[xviii] We make this calculation by simulating women's 2000 earnings using their actual hours and wage but using their 1993 share working (45%). The difference between this simulated gender gap and the actual gender gap can thus be assigned to their large increase in share working.


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My new book: Social Democratic Capitalism [feedly]

My new book: Social Democratic Capitalism
https://lanekenworthy.net/2019/10/02/my-new-book-social-democratic-capitalism/

Lane Kenworthy's new book: an economic defense of Social Democratic capitalism, which is nearly identical to Bernie Sanders Democratic Socialism, or Elizabeth Warren's progressive capitalism. Kenworthy's arguments, like recent posts by Brad DeLong, frankly sound more sober, astute, and data driven than some advocates (James Galbraith, e.g.)

__________________________

It's available today. The Oxford University Press and Amazon pages have the table of contents, blurbs, and more. You can read the first chapter online. Here is the opening:

For nations, as for individuals, it's good to be rich. Affluent countries are more likely to be democratic, more likely to have government programs that cushion life's bumps and boost the capabilities and well-being of the less fortunate, and more likely to prioritize personal liberty. Their citizens tend to be more secure, better educated, healthier, freer, and happier.

The world's twenty or so rich democratic countries aren't all alike, and they've changed a good bit over the past century. Their experiences give us helpful clues about what institutions and policies best promote human flourishing. To this point in history, the most successful societies have been those that feature capitalism, a democratic political system, good elementary and secondary (K–12) schooling, a big welfare state, employment-conducive public services, and moderate regulation of product and labor markets. I call this set of policies and institutions "social democratic capitalism."

Social democratic capitalism improves living standards for the least well-off, enhances economic security, and very likely boosts equality of opportunity. It does so without sacrificing the many other things we want in a good society, from liberty to economic growth and much more. Its chief practitioners have been the Nordic nations: Denmark, Finland, Norway, and Sweden. Contrary to what some presume, there is no good reason to think social democratic capitalism will work well only in these countries. Its success almost certainly is transferable to other affluent nations. Indeed, all of those nations already are partial adopters of social democratic capitalism.

The United States, the largest of the world's rich democracies, is one of those partial adopters. If the United States were to expand some of its existing public social programs and add some additional ones, many ordinary Americans would have better lives. Despite formidable political obstacles, there is good reason to think America will move in this direction in coming decades.

Those are my conclusions. This book provides the evidence and the reasoning.




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The Dispersion of High- and Low-Productivity Firms Within an Industry [feedly]

Productivity, and its measurement limitations, pose one of the most complex problems for socialist economics. Our primary measurement indexes are PRICES.  Socialism attempts to expand the domain of non-commodity values, as technology and relative abundance (i.e. unit cheapness) expands. Things that do not have prices -- there is a  universe of VALUES that are not commercial -- typically do NOT get measured. Plus, as Tim Taylor's post illustrates, the actual INPUTS to the price/cost productivity that we DO measure, are far more complex than the unit labor costs that show up in corporate accounting.

The Dispersion of High- and Low-Productivity Firms Within an Industry
http://conversableeconomist.blogspot.com/2019/10/the-dispersion-of-high-and-low.html

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If you think about an economy as fairly stable and static, you would expect that any two companies within an industry would be fairly close in terms of productivity. After all, if Company A and Company B are selling similar products, and A has much higher productivity than B, it should drive B out of business. Thus, one might expect that at the end of this process, the competitors we observe within an industry in the real world should be fairly close in productivity level.

However, this expectation is dramatically wrong. Within an industry, it is a standard pattern to find a wide dispersion of productivity across firms in the industry. Academic researchers have been familiar with this pattern for at least 15 years. But now (pulse rate accelerates) there is systematic time series data across industries from 1997-2015!  "The Dispersion Statistics on Productivity (DiSP) is a joint experimental data product from the U.S. Bureau of Labor Statistics and the U.S. Census Bureau. The DiSP provide statistics on within-industry dispersion in productivity."

For example, here's a figure from Cheryl Grim of the US Census Bureau. The bar graphs show that if you take a firm in the 75th percentile of the shoe or the cement industry and compare it with a firm in the 25th percentile of the shoe or cement industry, the firm in the 75th percentile will be about 150% as productive. In the computer industry, a firm in the 75th percentile is 400% more productive than a firm in the 25th percentile.



The existence of such differences in productivity across industry have been known for some time.   Cindy Cunningham, Lucia Foster, Cheryl Grimm John Haltiwanger, Sabrina Wulff Pabilonia, Jay Stewart, and Zoltan Wolf explain in "Dispersion in Dispersion: Measuring Establishment-Level Differences in Productivity" (Center for Economic Studies Working Paper CES 18-25R, September 2019).

They point out that research by Chad Syverson back in 2004, looking at data from manufacturing industries in 1977, found that firms in the 90th percentile of a certain industry were about four times as productive as firms in the 10th percentile. In the more recent data: "Illustrating the properties of the new data product, we find large within-industry dispersion in labor productivity: establishments at the 75th percentile are about 2.4 times as productive as those at the 25th percentile on average. 

Why do such differences exist? The reasons are obvious enough, as Grim explains?
Producers within industries differ in many ways. They produce different products of varying quality and have different customers and markets. They use different technology and business practices to combine different amounts of materials and equipment to produce their products. Some businesses are also larger and/or older than other businesses. Their ability to adjust their scale and mix of operations may vary due to these differences. Experimenting with new products and processes can also contribute to productivity differences. Businesses that have successfully adopted new technologies are likely to be more "productive" (as measured by these differences in revenue per hour) compared to businesses that have not yet adopted such technologies. All of these factors can contribute to enormous variations in this measure of business performance.
The fact that firms in the same industry be so different in productivity levels, and that these differences don't seem to fade away, has a number of interesting implications.

First, the pattern suggests that productivity growth doesn't always mean cutting-edge gains; indeed there is enormous potential for economic growth if the firms now lagging in productivity can be brought up to speed, perhaps by merging with higher productivity firms. In addition, one way that productivity growth happens for the economy as a whole is when high-productivity firms put low-productivity firms out of business.

Second, the persistence of these gaps suggests that some firms are protected from competition. For example, cement is not very transportable, and so competition in the cement industry is often limited to local firms. The potential reason why productivity differences may persist in other firms is worth considering.

Third, there seems to be some evidence that productivity diffusion is widening, as "superstar" firms in various industries pull further ahead. Indeed, this may be an important factor contributing to growth of inequality of wages, because workers and managers at high-productivity firms are typically much better-paid than those at low-productivity firms. edly newsfeed