unemployment – J. W. Mason

“Inflation is bad. But mass unemployment would have been worse.”

(Lauren Melodia and I had an op-ed in the Nov. 21 Washington Post, challenging the idea that today’s inflation means that the stimulus measures of the past year and half were too large. I’m posting it here as well.)

As we think about rising prices today, it’s important not to lose sight of where we were not so long ago. In the spring of 2020, much of the economy abruptly shut down. Schools and child-care centers closed. Air travel fell below 100,000 people a day, compared with 2.5 million daily passengers in a normal year. No one was staying in hotels or going to the gym. About 1.4 million small businesses shut their doors in the second quarter of the year.

More than 20 million Americans lost their jobs in the early days of the pandemic, and there was a very real possibility that many would face hunger, eviction and poverty. Many economists predicted a deep downturn comparable to the Great Recession that followed the financial crisis of 2007-08, if not the Great Depression of the 1930s.

Even at the start of this year, as Congress was debating the American Rescue Plan, it was far from clear that we were out of danger. In January, there were 10 million fewer jobs than a year earlier. Covid-related deaths were running at 30,000 per week — the highest rate at any point in the pandemic. No one knew how fast vaccines could be rolled out. There was still a real risk that the economy could tip into depression.

Thanks to stimulus measures, including the $2.2 trillion Cares Act, signed by President Donald Trump in March 2020, and the $1.9 trillion American Rescue Plan, signed by President Biden in March 2021, that didn’t happen. People who lost their jobs in restaurants, airports, hotels and elsewhere continued to pay their rent and put food on the table.

For much of 2020 and 2021, all the uncertainty — and the risks associated with vacationing, dining out and so on — meant households held back on spending, and savings piled up. Now, with the economy reopening and the worst of the pandemic (let’s hope) behind us, people are rushing to make use of those savings. Unfortunately, businesses can’t adjust production as fast as people can spend money, resulting in the inflation we’re seeing now: Prices rose 0.9 percent from September to October 2021 and are up 6.2 percent since October 2020.

It would be nice if there were a way to avoid economic catastrophe during the year-plus of pandemic restrictions while also avoiding rising prices today. But in the real world, there probably wasn’t. The pandemic imposed costs on the economy that had to be paid one way or another.

Think of it this way. When a restaurant shuts down for public health reasons, two things happen: Its services are not available for purchase, and the people who work there lose their incomes. If the government does nothing, aggregate demand and supply will remain in rough balance, but the displaced workers will be unable to pay their bills. Alternatively, the government can step in to maintain the incomes of the displaced workers. In this case, the spending that consumers might have done in restaurants will spill over into the rest of the economy — if not right away, then eventually. In a sense, the rising costs we’re seeing today are a result of economic production that didn’t happen last year.

In economics textbooks, the level of demand that brings the economy to full employment will also cause stable inflation — an assumption labeled “the divine coincidence.” But here on Earth, things don’t always work out so neatly. The level of spending required to replace incomes lost in the pandemic, combined with the disruptions to production and trade, meant there was no way to get an adequate recovery without some increase in inflation, especially given the bumps on the road to controlling the coronavirus. As the spread of the delta variant and some Americans’ resistance to getting a vaccine have held back spending on services, demand has spilled over into goods. And as it turns out, our global supply chains are unable to handle a rapid rise in demand for goods — especially because many manufacturers had expected a deep downturn and planned accordingly.

Today’s inflation has surprised many people, including us. We had been more worried about sustained high unemployment. One of us even gave a talk a year ago called “The Coronavirus Recession Is Just Beginning.” We were wrong about that. But then, so was almost everyone. In the summer of 2020, the Congressional Budget Office was predicting that the unemployment rate in late 2021 would be 8 percent; in fact, it has fallen to 4.6 percent. Many private forecasters were similarly gloomy. Under the circumstances, policymakers were absolutely right to prioritize payments to families.

The economist Larry Summers has been making the case since February that the government’s stimulus programs were larger than required and ran the risk of “inflationary pressures of a kind we have not seen in a generation.” Fiscal conservatives are claiming that Summers has been vindicated because inflation is higher than most supporters of the most recent relief package expected. But the economic data doesn’t match the scenario he described.

Summers predicted that the cumulative stimulus impact would be larger than the country’s output gap — the difference between actual and potential gross domestic product. Today, despite the stimulus, both real and nominal GDP remain significantly below the pre-pandemic trend. So unless you think the economy was operating above potential before the pandemic, there’s no reason to think it is above potential now. To the extent that domestic conditions are contributing to inflation, it’s not because spending has surpassed the economy’s capacity but because there has been a rapid shift in demand from services to goods.

In any case, most of the inflation we’re seeing is due not to domestic conditions but to the worldwide spike in food, energy and shipping costs. Perhaps we could have had inflation of 5 percent instead of 6 percent if the stimulus had been smaller. The cost of that trade-off would have been material hardship for millions of families and the risk of tipping the economy into a downturn. And that, fundamentally, is why today’s inflation is not a sign that the stimulus was too large: It has to be weighed against the risks on the other side.

After 2007, the United States experienced many years of high unemployment and depressed growth, thanks in large part to a stimulus that most now agree was too small. Policymakers belatedly learned that lesson, and as a result, the United States is making a rapid recovery from the most severe economic disruption in modern history. Yes, inflation is a real problem that needs to be addressed. In a recent Roosevelt Institute brief, we suggested that rather than raise interest rates, the best way to control inflation is to address supply constraints in the sectors where prices are climbing. But as bad as inflation is, mass unemployment is much worse. Given the alternatives, policymakers made the right choice.

“Earnings Shocks and Stabilization During COVID-19”

The other day, I put up a post arguing, on the basis of my analysis of the income data in the Current Population Survey, that the economic disruptions from the pandemic had not led to any reduction in real income for the lowest-income families. This is the opposite of the Great Recession, and presumably earlier recessions, where the biggest income losses were at the bottom. The difference, I suggested, was the much stronger fiscal response this time compared with previous downturns.

My numbers were rough — tho I think informative — estimates based on a data set that is mainly intended for other purposes. Today I want to call attention to an important paper that reaches similar conclusions on the basis of far better data.

The paper is “Earnings Shocks and Stabilization During COVID-19” by Jeff Larrimore, Jacob Mortenson and David Splinter.¹ If you’re following these debates, it’s a must-read.

The question they ask is slightly different from the one I did. Rather than look at the average change in income at each point in the distribution, they ask what fraction of workers experienced large declines in their incomes. Specifically they ask, for each point at the distribution of earnings in a given year, what fraction of workers had earnings at least 10 percent lower a year later? They include people whose earnings were zero in the second year (which means the results are not distorted by compositional effects), and do the exercise both with and without unemployment insurance and — for the most recent period — stimulus payments. They use individual tax records from the IRS, which means their sample is much larger and their data much more accurate than the usual survey-based sources.

What they find, first of all, is that earnings are quite volatile — more than 25 percent of workers experience a fall in earnings of 10 percent or more in a typical year, with a similar share experiencing a 10 percent or more increase. Looking at earnings alone, the fraction of workers experiencing large falls in income rose to about 30 percent in both 2009 and 2020; the fraction experiencing large increases fell somewhat in 2009, but not in 2019. See their Figure 1 below.

Turning to distribution, if we look at earnings alone, large falls were more concentrated at the bottom in 2020 than in 2009. This is shown in their Figure 2. (Note that while the percentiles are based on earnings plus UI benefits, the vertical axis shows the share with large falls in earnings alone.) This pattern is consistent with the concentration of pandemic-related job losses in low-wage sectors.

But when you add unemployment insurance in, the picture reverses. Now, across almost the whole lower half of the distribution, large falls in earnings were actually less common in 2020 than in 2019. And when you add in stimulus payments, it’s even more dramatic. Households in the bottom 20 percent of the distribution were barely half as likely to experience a larger fall in income in the crisis year of 2020 as in they were in the normal year of 2019.

The key results are summarized in their Table 1, below. It’s true that the proportion of low-wage households that experienced large falls in earnings during 2020 was greater than the proportion of high-wage households. But that’s true in every year — low incomes are just much more volatile than high ones. What’s different is how much the gap closed. Even counting the stimulus payments, households in the top fifth of earnings were somewhat more likely to experience a large fall in earnings in 2020 than in 2019. But in the bottom fifth, the share experiencing large falls in income fell from 43 percent to 27 percent. Nothing like this happened in 2009 — then, the frequency of large falls in income rose by the same amount (about 6 points) across the distribution.

One thing this exercise confirms is that the more favorable experience low-income households in the pandemic downturn was entirely due to much stronger income-support programs. Earnings themselves fell even more disproportionately at the bottom than in the last recession. In the absence of the CARES Act, income inequality would have widened sharply rather than narrowed.

The one significant limitation of this study is that tax data is only released well after the end of the year it covers. So at this point, it can only tell us what happened in 2020, not in 2021. It’s hard to guess if this pattern will continue in 2021. (It might make a difference whether the child tax credit payments are counted.) But whether or not it does, doesn’t affect the results for 2020.

While the US experienced the most rapid fall in economic activity in history, low-wage workers experienced much less instability in their incomes than in a “good” year. This seems like a very important fact to me, one that should be getting much more attention than it is.

It didn’t have to turnout that way. In most economic crises, it very much doesn’t. People who are saying that the economy is over stimulated are implicitly saying that protecting low-wage workers from the crisis was a mistake. When the restaurant workers should have been left to fend for themselves. That way, they wouldn’t have any savings now and wouldn’t be buying so much stuff. When production is severely curtailed, it’s impossible to maintain people’s incomes without creating excess demand somewhere else. But that’s a topic for another post.

The point I want to make — and this is me speaking here, not the authors of the paper — is that the protection that working people enjoyed from big falls in income in 2020 should be the new benchmark for social insurance. Because the other thing that comes out clearly from these numbers is the utter inadequacy of the pre-pandemic safety net. In 2019, only 9 percent of workers with large falls in earnings received UI benefits, and among those who did, the typical benefit was less than a third of their previous earnings. You can see the result of this in the table — for 2009 and 2019, the fraction of each group experiencing large falls in earnings hardly changes when UI is included. Before 2020, there was essentially no insurance against large falls in earnings.

To be sure, the tax data doesn’t tell us how many of those with big falls in earnings lost their jobs and how many voluntarily quit. But the fact that someone leaves their job voluntarily doesn’t mean they shouldn’t be protected from the loss of income. Social Security is, in a sense, a form of (much more robust) unemployment insurance for a major category of voluntary quits. The paid family and medical leave that, it seems, will not be in this year’s reconciliation bill but that Democrats still hope to pass, is another.

Back in the spring, people like Jason Furman were arguing that if we had a strong recovery in the labor market then we would no longer need the $400/week pandemic unemployment assistance. But this implicitly assumes that we didn’t need something like PUA already in 2019.

I’d like to hear Jason, or anyone, make a positive argument that before the pandemic, US workers enjoyed the right level of protection against job loss. In a good year in the US economy, 40 percent of low-wage workers experience a fall in earnings of 10 percent or more. Is that the right number? Is that getting us the socially optimal number of evictions and kids going to bed hungry? Is that what policy should be trying to get us back to? I’d like to hear why.

Video: The Macro Case for the Green New Deal

(Earlier this week, I gave a virtual presentation at an event organized by the Roosevelt Institute and the Green New Deal Network. Virtual events are inferior to live ones in many, many ways. But one way they are better, is that they are necessarily on video, and can be shared. Anyway, here is 25 minutes on why the economic situation calls for even more spending than the (surprisingly ambitious) proposals from the Biden administration, and also on why full employment shouldn’t be seen as an alternative to social justice and equity goals but as the best way of advancing them.)

Good News on the Economy, Bad News on Economic Policy

(Cross-posted from the Roosevelt Institute blog. I am hoping to start doing these kinds of posts on new economic data somewhat regularly.)

On Friday, the the Bureau of Labor Statistics released the unemployment figures for May. As expected, the reported unemployment rate was very low—3.6 percent, the same as last month. Combined with the steady growth in employment over the past few years, this level of unemployment—not seen since the 1960s—suggests an exceptionally strong labor market by historical standards. On one level this really is good news for the economy. But at the same time it is very bad news for economic policy: The fact that employment this low is possible, shows that we have fallen even farther short of full employment in earlier years than we thought.

Some skeptics, of course, will cast doubts on how meaningful the BLS numbers are. The headline unemployment rate, they will argue, understates true slack in the labor market; many of the jobs being created are low-wage and insecure; workers’ overall position is still weak and precarious by historical standards.

This is all true. But it is also true that the unemployment numbers are not an isolated outlier. Virtually every other measure also suggests a labor market that is relatively favorable to workers, at least by the standards of the past 20 years.

The broader unemployment measures published by the BLS, while higher than the headline rate, have come down more or less in lockstep with it. (The new release shows that the BLS’s broadest measure of unemployment, U-6, continued to decline in May, thanks to a steep fall in the number of people working part-time because they can’t find full-time work.) The labor force participation rate, after declining for a number of years, has now started to trend back upward, suggesting that people who might have given up on finding a job a few years ago are once again finding it worthwhile to look for one. The fraction of workers voluntarily quitting their jobs, at 2.3 percent, is now higher than it ever got during the previous business cycle. The quit rate is a good measure of labor market tightness—one of former Fed chair Janet Yellen’s preferred measures—because it shows you how people evaluate their own job prospects; people are much more likely to quit their current job if they expect to get a better one. Reported job openings, a longstanding measure of labor market conditions, are at their highest level on record, with employers reporting that nearly 5 percent of positions are unfilled. Wage growth, which was nowhere to be seen well into the official recovery, has finally begun to pick up, with wage growth noticeably faster since 2016 than in the first six years of the expansion. In the nonfinancial business sector—where the shares of labor and capital are most easily measured—the share of value added going to labor has finally begun to tick up, from a steady 57 percent from 2011 to 2014 up to 59 percent by 2017. Though still far short of the 65 percent of value added claimed by labor at the height of the late-1990s boom, the recent increase does suggest an environment in which bargaining power has at last begun to shift in favor of workers.

For progressives, it can be a challenge to talk about the strengthening labor market. Our first instinct is often to call attention to the ways in which workers’ position is still worse than it was a generation ago, and to all the ways that the labor market is still rigged in favor of employers. This instinct is not wrong, but it is only one side of the picture. At the same time, we need to call attention to the real gains to working people from a high-pressure economy—one where aggregate demand is running ahead of available labor.

A high-pressure economy is especially important for those at the back of the hiring queue. People sometimes say that full employment is fine, but that it doesn’t help people of color, younger people, or those without college degrees. This thinking, however, is backwards. It is educated white men with plenty of experience whose job prospects depend least on overall labor market conditions; their employment prospects are good whether overall unemployment rates are high or low. It is those at the back of the hiring queue—Black Americans, those who have received less education, people with criminal records, and others discriminated against by potential employers—who depend much more on a strong labor market. The Atlanta Fed’s useful wage tracker shows this clearly: Wage growth for lower-wage, non-white, and less-educated workers lagged behind that of college-educated white workers during the high-unemployment years following the recession. Since 2016, however, that pattern has reversed, with the biggest wage gains for nonwhite workers and those at the bottom of the wage distribution. This pattern has been documented in careful empirical work by Josh Bivens and Ben Zipperer of the Economic Policy Institute, who show that, historically, tight labor markets have disproportionately benefited Black workers and raised wages most at the bottom.

Does this mean we should be satisfied with the state of macroeconomic policy—if not in every detail, at least with its broad direction?

No, it means just the opposite. Labor markets do seem to be doing well today. But that only shows that macroeconomic performance over the past decade was even worse than we thought.

This is true in a precise sense. Macroeconomic policy always aims at keeping the economy near some target. Whether we define the target as potential output or full employment, the goal of policy is to keep the actual level of activity as close to it as possible. But we can’t see the target directly. We know how high gross domestic product (GDP) growth is or how low unemployment is, but we don’t know how high or how low they could be. Everyone agrees that the US fell short of full employment for much of the past decade, but we don’t know how far short. Every month that the US records an unemployment rate below 4 percent suggests that these low unemployment rates are indeed sustainable. Which means that they should be the benchmark for full employment. Which also means that the economy fell that much further short of full employment in the years after the 2008-2009 recession—and, indeed, in the years before it.

For example: In 2014, the headline unemployment rate averaged 6.2 percent. At that time, the benchmark for full employment (technically, the non-accelerating inflation rate of unemployment, or NAIRU) used by the federal government was 4.8 percent, suggesting a 1.4 point shortfall, equivalent to 2.2 million excess people out of work. But let’s suppose that today’s unemployment rate of 3.6 percent is sustainable—which it certainly seems to be, given that it is, in fact, being sustained. Then the unemployment rate in 2014 wasn’t 1.4 points too high but 2.6 points too high, which is nearly twice as big of a gap as policymakers thought at the time. Again, this implies that the failure of demand management after the Great Recession was even worse than we thought.

And not just after it. For most of the previous expansion, unemployment was above 5 percent, and the labor share was falling. At the time, this was considered full employment – indeed, the self-congratulation over the so-called Great Moderation and “amazing success” of economic policy reached a crescendo in this period. But if a perofrmance like today’s was possible then — and why shouldn’t it have been? — then what policymakers were actually presiding over was an extended stagnation. As Minnesota Fed chair Narayan Kocherlakota – one of the the few people at the economic-policy high table who seems to have learned something from the past decade – points out, the US “output gap has been negative for almost the entirety of the current millenium.”

These mistakes have consequences. For years now, we have been repeatedly told that the US is at or above full employment—claims that have been repeatedly proved wrong as the labor market continues to strengthen. Only three years ago, respectable opinion dismissed the idea that, with sufficient stimulus, the unemployment could fall below 4 percent as absurd. As a result, we spent years talking about how to rein in demand and bring down the deficit, when in retrospect it is clear that we should have been talking about big new public spending programs to boost demand.

This, then, is a lesson we can draw from today’s strong unemployment numbers. Strong economic growth does improve the bargaining position of workers relative to employers, just as it has in the past. The fact that the genuine gains for working people over the past couple years have only begun to roll back the losses of the past 20 doesn’t mean that strong demand is not an important goal for policy. It means that we need much more of it, sustained for much longer. More fundamentally, strong labor markets today are no grounds for complacency about the state of macroeconomic policy. Again, the fact that today’s labor market outcomes are better than people thought possible a few years ago shows that the earlier outcomes were even worse than we thought. The lesson we should take is not that today’s good numbers are somehow fake; they are real, or at least they reflect a real shift from the position of a few years ago. Rather, the lesson we should take is that we need to set our sights higher. If today’s strong labor markets are sustainable—and there’s no reason to think that they are not—then we should not accept a macroeconomic policy consensus that has been willing to settle for so much less for so long.

Macroeconomic Lessons from the Past Decade

Below the fold is a draft of a chapter I’m contributing to an edited volume on aggregate demand and employment. My chapter is supposed to cover macroeconomic policy and employment in the US, with other chapters covering other countries and regions.

The chapter is mostly based on material I’ve pulished elsewhere, mainly my Roosevelt papers “What Recovery?” and “A New Direction for the Federal Reserve.” My goal was something that summarized the arguments there for an audience of (presumably) heterodox macroeconomists, and that could also be used in the classroom.

There is still time to revise this, so comments/criticisms are very welcome.

Continue reading Macroeconomic Lessons from the Past Decade

Can We Blame Low Labor Participation on Past High Unemployment?

Fifth post in a series. Posts one, two, three and four.

We know that US GDP fell sharply in 2008-2009. We know that none of that decline has been made up by faster growth since the recession: GDP today is about 14 percent below the pre-2008 trend, a gap that shows no sign of closing. We also know that one-third of that shortfall is accounted for by slower productivity growth, and the remaining two-thirds by slower employment growth.

To put numbers on it: Over the past decade, US employment rose by a total of 6 percent, or about 0.5 percent per year. This is about half the rate of employment growth over the last ten years before the recession, and less a quarter the average rate for the postwar period as a whole. 2000-2010 was the first decade since the Depression in which US employment actually fell. Since the unemployment rate today is very close to that of ten years ago, this whole slowdown is accounted for by a decline in laborforce participation.

Employment growth, unlike productivity growth, was already slowing prior to the recession, and pre-recession forecasts predicted a further slowdown comparable to what actually occurred. This is consistent with a widely-held view that the slowdown in employment is the result of demographic and other structural factors, not of the recession or demand weakness in general. In the next couple posts, I want to take a critical look at this claim. How confident should we be that employment would be the same today in a counterfactual world where the 2008-2009 didn’t happen? How responsive might employment be to stronger demand going forward? And more broadly, how much do changes in laborforce participation seem to be explained by more or less exogenous factors like demographics, and how much by demand and labor-market conditions?

The rest of this post is about an approach to this question that did not produce the results I was hoping for. So I probably won’t include this material in whatever paper comes out of these posts. But as we feel our way into reality it’s important to note down the dead ends as well as the routes that seem promising. And even though this exercise didn’t help much in answering the big questions posed in the previous paragraph, it’s still interesting in its own right.

Can the fall in laborforce participation be explained as a direct, predictable effect of the rise in unemployment during the recession? It seems like maybe it can. The starting point is the observation that unemployed workers are much more likely to drop out of the laborforce than people with jobs are. You can see this clearly in the BLS tables on employment transitions. As the figure below shows, about 3 percent of employed people exit the laborforce each month, a fraction that has been remarkably stable since the data begins in 1990. Meanwhile, about 20 percent of unemployed people drop out of the laborforce each month.

On the face of it, this 17-point difference suggests an important role for the unemployment rate in changes in labor force participation. All else equal, each year-point of additional unemployment should reduce the labor-force participation rate by two points. (0.17 x 12 = 2.) So you would think that much of the recent fall in laborforce participation could be explained simply by the rise in unemployment during the recession.

When I thought of this it seemed very logical. It would be easy to do a counterfactual exercise, I thought, showing how laborforce participation would have evolved simply based on the historical transition rates between employment, unemployment and out of the laborforce, and the actual evolution of employment and unemployment. If you could show that something like the actual fall in laborforce participation was a predictable result of the rise in unemployment during the recession, that would support the idea that demand rather than “structural” factors are at work. And even if it wasn’t that strong positive evidence, it would suggest skepticism about similar counterfactual exercises using historical participation rates by age and so on.

I mean, it makes sense, right? Unemployed people are much more likely to leave the workforce than employed people, so a rise in unemployment should naturally lead to a decline in laborforce participation. But as the figure below shows, the numbers don’t work.

What I did was start with the populations of employe, unemployed and not-in-the-laborforce people at the end of the recession in December 2009. Then I created a counterfactual scenario for the remaining period using the actual transition rates between employment and unemployment but the pre-recession average rates for transitions between not in the workforce and unemployment and employment. In other words, just knowing the average rates that people move between employment, unemployment and out of the workforce, and the actual shifts between employment and unemployment, what path would you have predicted for laborforce participation over 2010-2016?

The heavy gray line shows the historical fraction of the population aged 16 and over who are not in the laborforce. The black line shows the results of the counterfactual exercise. Not very close.

There turn out to be two reasons why the counterfactual exercise gives such a poor fit. Both are interesting and neither was obvious before doing the exercise. The first reason is that there are surprisingly large flows from out of the labor force back into it. Per the BLS, about 7 percent of people who report being out of the labor force in a given month are either employed or unemployed (i.e. actively seeking work) the following month. This implies that the typical duration of being out of the workforce is less than a year — though of course this is a mix of people who leave the workforce for just a month or two and people who leave for good. For present purposes, the important thing is that exogenous changes to the employment-population ratio decline quickly, with a half-life of only about a year. So while the historical data suggests that a rise in unemployment like we saw in 2008-2009 should have been associated with a large rise in the share of the population not in the laborforce, it also suggests that this effect should have been transitory — a couple years after unemployment rates returned to normal, participation rates should have as well. This is not what we’ve seen.

The large gross movements in and out of the laborforce mean that sustained lower participation rates can’t be straightforwardly understood as the “echo” of high unemployment in the past. But they do also tend to undermine the structural story — if the typical stint outside the laborforce lasts less than a year it can hardly be due to something immutable.

The second reason why the counterfactual doesn’t fit the data was even more surprising, at least to me. I constructed my series using the historical average transition rates into and out of the workforce. But transition rates during the recession and early recovery departed from the historical average in an important way: unemployed workers were significantly less likely to exit the workforce. This turns out to be the normal pattern, at least over the previous two business cycles — if you look back to that first figure, you can see dips in the transition rate from unemployed to out of the workforce in the early 1990s and early 2000s downturns as well. The relationship is clearer in the next figure, a scatter of the unemployment rate and the share of unemployed workers leaving the workforce each month.

As you can see, there is a strong negative relationship — when unemployment was around 4 percent in 1999-2000 and again in 2006-2007, about a quarter of the unemployed exited the laborforce each month. But at the peak of the past recession when unemployment reached 10 percent, only 18 percent of the unemployed left the laborforce each month. That might not seem like a huge difference, but it’s enough to produce quite different dynamics. It’s also a bit surprising, since you would think that people would be more likely to give up searching for work when unemployment is high than when when it is low. The obvious explanation would be that the people who are out of work when the unemployment rate is low are not simply a smaller set of the same people who are out of work when the rate is high, but are different in some way. The same factors that keep them at the back of the hiring queue may make also be likely to push them out of the laborforce altogether. Extended unemployment insurance might also play a role.

It would be possible to explore this further using CPS data, which is the source for the BLS tables I’m working with. No doubt there are papers out there describing the different characteristics of the unemployed in periods of high versus low unemployment. (Not being a labor economist, I don’t know this literature.) But I am going to leave it here.

Summary: The fact that unemployed people are much more likely to leave the laborforce than employed people are, suggests that some part of the fall in laborforce particiaption since 2008 might be explained by the lingering effects of high unemployment in the recession and early recovery. But this story turns out not tow work, for two reasons. First, the rapid turnover of the not in the laborforce population means that this direct effect of high unemployment on participation is fairly shortlived. Second, the rate at which unemployed people exit the laborforce turns out to be lower when unemployment is high. Together, these two factors produce the results shown in the second figure — the fall in participation you would predict based simply on high unemployment is steeper but shorter-lived than what actually occurred. The first factor — the large flows in and out of the laborforce — while it vitiates the simple story I proposed here, is consistent with a broader focus on demand rather than demographics as an explanation for slow employment growth. If people are frequently moving in and out of the laborforce, it’s likely that their decisions are influenced by their employment prospects, and it means they’re not determined by fixed characteristics like age. The second factor — that unemployed people were less likely to give up looking for jobs during 2009-2011, as in previous periods of high unemployment — is, to me, more surprising, and harder to fit into a demand-side story.

Unemployment and Productivity Growth

I write here frequently about “the money view” — the idea that we need to see economic relationships as a system of money flows and money commitments, that is not reducible to the “real” production and exchange of goods and services. Seeing the money-game as a self-contained system is the first step; the next step is to ask how this system interacts with the concrete activities of production.

One way to look at this interface is through the concept of potential output, and its relationship to current expenditure, or demand. In the textbook view, there is no connection between the long-run evolution of potential output with demand. This is a natural view if you think that economic quantities have an independent material existence. First we have scarce resources, then the choice about which end to devote them to. Knut Wicksell suggests somewhere an evocative metaphor for this view of economic growth: It’s as if we had a cellar full off wine in barrels, which will improve with age. The problem of economic growth is then equivalent to choosing the optimal tradeoff between having better wine, and drinking it sooner than later. But whatever choice we make, all the wine is already there. Ramsey and Solow growth models, with their “golden rule” growth rate, are descriptions of this kind of problem. Aggregate demand doesn’t come into it.

From our point of view, on the other hand, production is a creative, social activity. Economic growth is not a matter of allowing an exiting material process to continue operating through time, but of learning how to work together in new ways. The fundamental problem is coordination, not allocation. From this point of view, the technical conditions of production are endogenous to the organization of production, and the money payments that structure it. So it’s natural to think that aggregate expenditure could be an important factor determining the pace at which productive activity can be reorganized.

Now, whether demand actually does matter in the longer run is hotly debated point in heterodox economics. You can find very smart Post Keynesians like Steve Fazzari arguing that it does, and equally smart Marxists like Dumenil and Levy arguing that it does not. (Amitava Dutt has a good summary; Mark Setterfield has a good recent discussion of the formal issues of incorporating demand into Kaldorian growth models.) But within our framework, at least it is possible to ask the question.

Which brings me to this recent article in the Real World Economic Review. I don’t recommend the piece — it is not written in a way to inspire confidence. But it does make an interesting claim, that over the long run there is an inverse relationship between unemployment and labor productivity growth in the US, with average labor productivity growth equal to 8 minus the unemployment rate. This is consistent with the idea that demand conditions influence productivity growth, most obviously because pressures to economize on labor will be greater when labor is scarce.

A strong empirical regularity like this would be interesting, if it was real. But is it?

Here is one obvious test (a bit more sensible to me than the approach in the RWER article). The figure below shows the average US unemployment rate and real growth rate of hourly labor productivity for rolling ten-year windows.

It’s not exactly “the rule of 8” — the slope of the regression line is just a big greater than -0.5, rather than -1. But it is still a striking relationship. Ten-year periods with high growth of productivity invariably also have low unemployment rates; periods of high average unemployment are invariably also periods of slow productivity growth.

Of course these are overlapping periods, so this tells us much less than it would if they were independent observations. But the association of above-average productivity growth with below-average unemployment is indeed a historical fact, at least for the postwar US. (As it turns out, this relationship is not present in most other advanced countries — see below.) So what could it mean?

1. It might mean nothing. We really only have four periods here — two high-productivity-growth, low-unemployment periods, one in the 1950s-1960s and one in the 1990s; and two low-productivity-growth, high-unemployment periods, one in the 1970s-1980s and one in the past decade or so. It’s quite possible these two phenomena have separate causes that just happened to shake out this way. It’s also possible that a common factor is responsible for both — a new technology-induced investment boom is the obvious candidate.

2. It might be that high productivity growth leads to lower unemployment. The story here I guess would be the Fed responding to a positive supply shock. I don’t find this very plausible.

3. It might be that low unemployment, or strong demand in general, fosters faster productivity growth. This is the most interesting for our purposes. I can think of several versions of this story. First is the increasing-returns story that originally motivated Verdoorn’s law. High demand allows firms to produce further out on declining cost curves. Second, low unemployment could encourage firms to adopt more labor-saving production techniques. Third, low unemployment might associated with more rapid movement of labor from lower-productivity to higher-productivity activities. (In other words, the relationship might be due to lower visible unemployment being associated with lower disguised unemployment.) Or fourth, low unemployment might be associated with a relaxing of the constraints that normally limit productivity-boosting investment — demand itself, and also financing. In any of these stories, the figure above shows a causal relationship running from the x-axis to the y-axis.

One scatterplot of course hardly proves anything. I’m really just posing the question. Still, this one figure is enough to establish one thing: A positive relationship between unemployment and labor productivity has not been the dominant influence on either variable in the postwar US. In particular, this is strong evidence against the idea the idea of technological unemployment, beloved by everyone from Jeremy Rifkin to Lawrence Summers. (At least as far as this period is concerned — the future could be different.) To tell a story in which paid labor is progressively displaced by machines, you must have a positive relationship between labor productivity and unemployment. But historically, high unemployment has been associated with slower growth in labor productivity, not faster. So we can say with confidence that whatever has driven changes in unemployment over the past 75 years, it has not been changes in the pace at which human labor is replaced by technology.

The negative relationship between unemployment and productivity growth, whatever it means, turns out to be almost unique to the US. Of the dozen or so other countries I looked at, the only one with a similar pattern is Japan, and even there the relationship is weaker. I honestly don’t know what to make of this. But if you’re interested, the other scatterplots are below the fold.

Note: Labor productivity is based on real GDP per hour, from the BLS International Labor Comparisons project; unemployment is the harmonized unemployment rate for all persons from the OECD Main Economic Indicators database. I used these because they are (supposed to be) defined consistently across countries and were available on FRED. Because the international data covers shorter periods than the US data does, I used 8-year windows instead of 10-year windows.