Can We Blame Low Labor Participation on Past High Unemployment?

Fifth post in a series. Posts onetwothree 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?

transitions2The 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.