potential – J. W. Mason

What Recovery: Reading Notes

My Roosevelt Institute paper on potential output came out last week. (Summary here.) The paper has gotten some more press since Neil Irwin’s Times piece, including Ryan Cooper in The Week and Felix Salmon in Slate. My favorite headline is from Boing Boing: American Wages Are So Low, the Robots Don’t Want Your Jobs.

In the paper I tried to give a fairly comprehensive overview of the evidence and arguments that the US economy is not in any meaningful sense at potential output or full employment. But of course it was just one small piece of a larger conversation. Here are a few things I’ve found interesting recently on the same set of issues. .

Perhaps the most important new academic contribution to this debate is this paper by Olivier Coibion, Yuriy Gorodnichenko, and Mauricio Ulate, on estimates of potential output, which came out too late for me to mention in the Roosevelt report. Their paper rigorously demonstrates that, despite their production-function veneer, the construction of potential output estimates ensures that any persistent change in growth rates will appear as a change in potential. It follows that there is “little value added in estimates of potential GDP relative to simple measures of statistical trends.” (Matthew Klein puts it more bluntly in an Alphaville post discussing the paper: “‘Potential’ output forecasts are actually worthless.”) The paper proposes an alternative measure of potential output, which they suggest can distinguish between transitory demand shocks and permanent shifts in the economy’s productive capacity. This alternative measure gives a very similar estimate for the output gap as simply looking at the pre-2008 forecasts or extrapolating from the pre-2008 trend. “Our estimates imply that U.S. output remains almost 10 percentage points below potential output, leaving ample room for policymakers to close the gap through demand-side policies if they so chose to.” Personally, I ‘m a little less convinced by their positive conclusions than by their negative ones. But this paper should definitely put to the rest the idea (as in last year’s notorious CEA-chair letter) that it is obviously wrong — absurd and unserious — that a sufficient stimulus could deliver several years of 4 percent real growth, until GDP returned to its pre-recession trend. It may or may not be true, but it isn’t crazy.

Many of the arguments in my paper were also made in this valuable EPI report by Josh Bivens, reviving the old idea of a “high pressure economy”. Like me, Bivens argues that slow productivity growth is largely attributable to low investment, which in turn is due to weak demand and slow wage growth, which blunts the incentive for business to invest in labor-saving technology. One important point that Bivens makes that I didn’t, is that much past variation in productivity growth has been transitory; forecasts of future productivity growth based on the past couple of years have consistently performed worse than forecasts based on longer previous periods. So historical evidence gives us no reason see the most recent productivity slowdown as permanent. My one quibble is that he only discusses faster productivity growth and higher inflation as possible outcomes of a demand-driven acceleration in wages. This ignores the third possible effect, redistribution from from profits to wages — in fact a rise in the labor share is impossible without a period of “overfull” employment.

Minneapolis Fed president Neel Kashkari wrote a long post last fall on “diagnosing and treating the slow recovery.” Perhaps the most interesting thing here is that he poses the question at all. There’s a widespread view that once you correct for demographics, the exceptional performance of the late 1990s, etc., there’s nothing particularly slow about this recovery — no problem to diagnose or treat.

Another more recent post by Kashkari focuses on the dangers of forcing the Fed to mechanically follow a Taylor rule for setting interest rates. By his estimate, this would have led to an additional 2.5 million unemployed people this year. It’s a good illustration of the dangers of taking the headline measures of economic performance too literally. I also like its frank acknowledgement that the Fed — like all real world forecasters — rejects rational expectations in the models it uses for policymaking.

Kashkari’s predecessor Narayan Kocherlakota — who seems to agree more with the arguments in my paper — has a couple short but useful posts on his personal blog. The first, from a year ago, is probably the best short summary of the economic debate here that I’ve seen. Perhaps the key analytic point is that following a period of depressed investment, the economy may reach full employment given the existing capital stock while it is still well short of potential. So a period of rapid wage growth would not necessarily mean that the limits of expansionary policy have ben reached, even if those wage gains were fully passed through to higher prices. His emphasis:

Because fiscal policy has been too tight, we have too little public capital. … At the same time, physical investment has been too low… Conditional on these state variables, we might well be close to full employment. … But, even though we’re close to full employment, there’s a lot of room for super-normal growth. Both capital and TFP are well below their [long run level]. The full-employment growth rate is going to be well above its long-run level for several years. We can’t conclude the economy is overheating just because it is growing quickly.

His second post focuses on the straightforward but often overlooked point that policy should take into account not just our best estimates but our uncertainty about them, and the relative risks of erring on each side. And if there is even a modest chance that more expansionary policy could permanently raise productivity, then the risks are much greater on the over-contractionary side. [1] In particular, if we are talking about fiscal stimulus, it’s not clear that there are any costs at all. “Crowding out” is normally understood to involve a rise in interest rates and a shift from private investment to public spending. In the current setting, there’s a strong case that higher interest rates at full employment would be a good thing (at least as long as we still rely on as the main tool of countercyclical policy). And it’s not obvious, to say the least, that the marginal dollar of private investment is more socially useful than many plausible forms of public spending. [2] Kashkari has a post making a similar argument in defense of his minority vote not to raise rates at the most recent FOMC meeting. (Incidentally, FOMC members blogging about their decisions is a trend to be encouraged.)

In a post from March which I missed at the time, Ryan Avent tries to square the circle of job-destroying automation and slow productivity growth. One half of the argument seems clearly right to me: Abundant labor and low wages discourage investment in productivity-raising technologies. As Avent notes, early British and even more American industrialization owe a lot to scarce labor and high wages. The second half of the argument is that labor is abundant today precisely because so much has been displaced by technology. His claim is that “robots taking the jobs” is consistent with low measured productivity growth if the people whose jobs are taken end up in a part of the economy with a much lower output per worker. I’m not sure if this works; this seems like the rare case in economics where an eloquent story would benefit from being re-presented with math.

Along somewhat similar lines, Simon Wren-Lewis points out that unemployment may fall because workers “price themselves into jobs” by accepting lower-wage (and presumably lower-productivity) jobs. But this doesn’t mean that the aggregate demand problem has been solved — instead, we’ve simply replaced open unemployment with what Joan Robinson called “disguised unemployment,” as some of people’s capacity for work continues to go to waste even while they are formally employed. “But there is a danger that central bankers would look at unemployment, … and conclude that we no longer have inadequate aggregate demand…. If demand deficiency is still a problem, this would be a huge and very costly mistake.”

Karl Smith at the Niskanen Center links this debate to the older one over the neutrality of money. Central bank interventions — and aggregate demand in general — are understood to be changes in the flow of money spending in the economy. But a lon-standing tradition in economic theory says that money should be neutral in the long run. As we are look at longer periods, changes in output and employment should depend more and more on real resources and technological capacities, and less and less on spending decisions — in the limit not at all. If you want to know why GDP fell in one quarter but rose in the next (this is something I always tell my undergraduates) you need to ask who chose to reduce their spending in the first period and who chose to increase it in the first. But if you want to know why we are materially richer than our grandparents, it would be silly to say it’s because we choose to spend more money. This is the reason why I’m a bit impatient with people who respond to the fact that, relative to the pre-2008 trend, output today has not recovered from the bottom of the recession, by saying “the trend doesn’t matter, deviations in output are always persistent.” This might be true but it’s a radical claim. It means you either take the real business cycle view that there’s no such thing as aggregate demand, even recessions are due to declines in the economy’s productive potential; or you must accept that in some substantial sense we really are richer than our grandparents because we spend more money. You can’t assert that GDP is not trend-stationary to argue against an output gap today unless you’re ready to accept these larger implications.

The invaluable Tom Walker has a fascinating post going back to even older debates, among 19th century anti-union and pro-union pamphleters, about whether there was a fixed quantity of labor to be performed and whether, in that case, machines were replacing human workers. The back and forth (more forth than back: there seem to be a lot more anti-labor voices in the archives) is fun to read, but what’s the payoff for todays’ debates?

The contemporary relevance of this excursion into the archives is that economic policy and economic thought walks on two legs. Conservative economists hypocritically but strategically embrace both the crowding out arguments for austerity and the projected lump-of-labor fallacy claims against pensions and shorter working time. They are for a “fixed amount” assumption when it suits their objectives and against it when it doesn’t. There is ideological method to their methodological madness. That consistency resolves itself into the “self-evidence” that nothing can be done.

That’s exactly right. When we ask why labor’s share has fallen so much over the past generation, we’re told it’s because of supply and demand — an increased supply of labor from China and elsewhere, and a decreased demand thanks to technology. But if it someone says that it might be a good idea then to limit the supply of labor (by lowering the retirement age, let’s say) and to discourage capital-intensive production, the response is “are you crazy? that will only make everyone poorer, including workers.” Somehow distribution is endogenous when it’s a question of shifts in favor of capital, but becomes exogenously fixed when it’s a question of reversing them.

A number of heterdox writers have identified the claim that productivity growth depends on demand as Verdoorn’s law (or the Kaldor-Verdoorn Law). For example, the Post Keynesian blogger Ramanan mentions it here and here. I admit I’m a bit dissatisfied with this “law”. It’s regularly asserted by heterodox people but you’ll scour our literature in vain looking for either a systematic account of how it is supposed to operate or quantitative evidence of how and how much (or whether) it does.

Adam Ozimek argues that the recent rise in employment should be seen as an argument for continued expansionary policy, not a shift away from it. After all, a few years ago many policymakers believed such a rise was impossible, since the decline in employment was supposed to be almost entirely structural.

Finally, Reihan Salam wants to enlist me for the socialist flank of a genuinely populist Trumpism. This is the flipside of criticism I’ve sometimes gotten for making this argument — doesn’t it just provide intellectual ammunition for the Bannon wing of the administration and its calls for vast infrastructure spending, which is also supposed to boost demand and generate much faster growth? Personally I think you need to make the arguments for what you think is true regardless of their political valence. But I might worry about this more if I believed there was even a slight chance that Trump might try to deliver for his working-class supporters.

[1] Kocherlakota talks about total factor productivity. I prefer to focus on labor productivity because it is based on directly observable quantities, whereas TFP depends on estimates not only of the capital stock but of various unobservable parameters. The logic of the argument is the same either way.

[2] I made similar arguments here.

EDIT: My comments on the heterodox literature on the Kaldor-Verdoorn Law were too harsh. I do feel this set of ideas is underdeveloped, but there is more there than my original post implied. I will try to do a proper post on this work at some point.

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.

Employment, Productivity and the Business Cycle

Fourth post in a series. Posts one, two and three.

Empirically-oriented macroeconomists have recognized since the early 20th century that output, employment and productivity move together over the business cycle. The fact that productivity falls during recessions means that employment varies less over the cycle than output does. This behavior is quite stable over time, giving rise to Okun’s law. In the US, Okun’s law says that the unemployment rate will rise by one point in each 2.5 point shortfall of GDP growth over trend — a ratio that doesn’t seem to have declined much since Arthur Okun first described it in the mid-1960s. [1]

It’s not obvious that potential should show this procyclical behavior. As I noted in the previous post, a naive prediction from a production function framework would be that a negative demand shock should reduce employment more than output, since business can lay off workers immediately but can’t reduce their capital stock right away. In other words, productivity should rise in recessions, since the labor of each still-employed worker is being combined with more capital.

There are various explanations for why labor productivity behaves procyclically instead. The most common focus on the transition costs of changing employment. Since hiring and firing is costly for businesses, they don’t adjust their laborforce to every change in demand. So when sales fall in recessions, they will keep extra workers on payroll — paying them now is cheaper than hiring them back later. Similarly, when sales rise businesses will initially try to get more work out of their existing employees. This shows up as rising labor productivity, and as the repeated phenomenon of “jobless recoveries.”

Understood in these terms, the positive relationship between output, employment and productivity should be a strictly short-term phenomenon. If a change in demand (or in other constraints on output) is sustained, we’d expect labor to fully adjust to the new level of production sooner or later. So over horizons of more than a year or two, we’d expect output and employment to change in proportion. If there are other limits on production (such as non-produced inputs like land) we’d expect output and labor productivity to move inversely, with faster productivity growth associated with slower employment growth or vice versa. (This is the logic of “robots taking the jobs.”) A short-term positive, medium term negative, long-term flat or negative relationship between employment growth and productivity growth is one of the main predictions that comes out of a production function. But it doesn’t require one. You can get there lots of other ways too.

And in fact, it is what we see.

The figure shows the simple correlation of employment growth and productivity growth over various periods, from one quarter out to 50 quarters. (This is based on postwar US data.) As you can see, over periods of a year or less, the correlation is (weakly) positive. Six-month periods in which employment growth was unusually weak are somewhat more likely to have seen weak productivity growth as well. This is the cyclical effect presumably due to transition costs — employers don’t always hire or fire in response to short-run changes in demand, allowing productivity to vary instead. But if sales remain high or low for an extended period, employers will eventually bring their laborforce into line, eliminating this relationship. And over longer periods, autonomous variation in productivity and labor supply are more important. Both of these tend to produce a negative relationship between employment and productivity. And that’s exactly what we see — a ten-year period in which productivity grew unusually quickly is likely to be one in which employment grew slowly. (Admittedly postwar US data doesn’t give you that many ten-year periods to look at.)

Another way of doing this is to plot an “Okun coefficient” for each horizon. Here we are looking at the relationship between changes in employment and output. Okun’s law is usually expressed in terms of the relatiojship between unemployment and output, but here we will look at it in terms of employment instead. We write

(1) %ΔE = a (g – c)

where %ΔE is the percentage change in employment, g is the percentage growth in GDP, c is a constant (the long-run average rate of productivity growth) and a is the Okun coefficient. The value of a says how much additional growth in employment we’d expect from a one percentage-point increase in GDP growth over the given period. When the equation is estimated in terms of unemployment and the period is one, year, a is generally on the order of 0.4 or so, meaning that to reduce unemployment by one point over a year normally requires GDP growth around 2.5 points above trend. We’d expect the coefficient for employment to be greater, but over short periods at least it should still be less than one.

Here is what we see if the estimate the equation for changes in output and employment for various periods, again ranging from one quarter up to ten years. (Again, postwar US data. The circles are the point estimates of the coefficients; the dotted lines are two standard errors above and below, corresponding to a standard 95% confidence interval.)

What’s this show? If we estimate Equation (1) looking at changes over one quarter, we find that one percentage point of additional GDP growth is associated with just half a point of additional employment growth. But if we estimate the same equation looking at changes over two years, we find that one point of additional GDP growth is associated with 0.75 points of additional employment growth.

The fact that the coefficient is smallest for the shorter periods is, again, consistent witht he conventional understanding of Okun’s law. Because hiring and firing is costly, employers don’t fully adjust staffing unless a change in sales is sustained for a while. If you were thinking in terms of a production function, the peak around 2 years represents a “medium-term” position where labor has adjusted to a change in demand but the capital stock has not.

While it’s not really relevant for current purposes, it’s interesting that at every horizon the coefficient is significantly below zero. What this tells us is that there is no actual time interval corresponding to the “long run” of the model– a period long enough for labor and the capital stock to be fully adjusted but short enough that technology is fixed. Over this hypothetical long run, the coefficient would be one. One way to think about the fact that the estimated coefficients are always smaller, is that any period long enough for labor to adjust, is already long enough to see noticeable autonomous changes in productivity. [2]

But what we’re interested in right now is not this normal pattern. We’re interested in how dramatically the post-2008 period has departed from it. The past eight years have seen close to the slowest employment growth of the postwar period and close to the slowest productivity growth. It is normal for employment and productivity to move together for a couple quarters or a year, but very unusual for this joint movement to be sustained over nearly a decade. In the postwar US, at least, periods of slow employment growth are much more often periods of rapid productivity growth, and conversely. Here’s a regression similar to the Okun one, but this time relating productivity growth to employment growth, and using only data through 2008.

prod on emp While the significance lines can’t be taken literally given that these are overlapping periods, the figure makes clear that between 1947 and 2008, there were very few sustained periods in which both employment and productivity growth made large departures from trend in the same direction.

Put it another way: The past decade has seen exceptionally slow growth in employment — about 5 percent over the full period. If you looked at the US postwar data, you would predict with a fair degree of confidence that a period of such slow employment growth would see above-average productivity growth. But in fact, the past decade has also seen very low productivity growth. The relation between the two variables has been much closer to what we would predict by extrapolating their relationships over periods of a year. In that sense, the current slowdown resembles an extended recession more than it does previous periods of slower growth.

As I suggested in an earlier post, I think this is a bigger analytic problem than it might seem at first glance.

In the conventional story, productivity is supposed to be driven by technology, so a slowdown in productivity growth reflects a decline in innovation and so on. Employment is driven by demographics, so slower employment growth reflects aging and small families. Both of these developments are negative shifts in aggregate supply. So they should be inflationary — if the economy’s productive potential declines then the same growth in demand will instead lead to higher prices. To maintain stable prices in the face of these two negative supply shocks, a central bank would have to raise interest rates in order to reduce aggregate spending to the new, lower level of potential output. Is this what we have seen? No, of course not. We have seen declining inflation even as interest rates are at historically low levels. So even if you explain slower productivity growth by technology and explain slower employment growth by demographics, you still need to postulate some large additional negative shift in demand. This is DeLong and Summers’ “elementary signal identification point.”

Given that we are postulating a large, sustained fall in demand in any case, it would be more parsimonious if the demand shortfall also explained the slowdown in employment and productivity growth. I think there are good reasons to believe this is the case. Those will be the subject of the remaining posts in this series.

In the meantime, let’s pull together the historical evidence on output, employment and productivity growth in one last figure. Here, the horizontal axis is the ten-year percentage change in employment, while the vertical axis is the ten-year percentage change in productivity. The years are final year of the comparison. (In order to include the most recent data, we are comparing first quarters to first quarters.) The color of the text shows average inflation over the ten year period, with yellow highest and blue lowest. The diagonal line corresponds to the average real growth rate of GDP over the full period.

What we’re looking at here is the percentage change in productivity, employment and prices over every ten-year period from 1947-1957 through 2006-2016. So for instance, growth between 1990 and 2000 is represented by the point labeled “2000.” During this decade, total employment rose by about 20 percent while productivity rose by a total of 15 percent, implying an annual real growth of 3.3 percent, very close to the long-run average.

One natural way to think about this is that yellow points below and to the right of the line suggest negative supply shocks: If the productive capacity of the economy declines for some reason, output growth will slow, and prices will rise as private actors — abetted by a slow-to-react central bank — attempt to increase spending at the usual rate. Similarly, blue points above the line suggest positive supply shocks. Yellow points above the line suggest positive demand shocks — an increase in spending can increase output growth above trend, at least for a while, but will pull up prices as well. And blue points below the line suggest negative demand shocks. This, again, is Delong and Summers’ “elementary signal identification point.”

We immediately see what an outlier the recent period is. Both employment and productivity growth over the past ten years have been drastically slower than over the preceding decade — about 5 percent each, down from about 20 percent. 2000-2010 and 2001-2011 were the only ten-year periods in postwar US history when total employment actually declined. The abruptness of the deceleration on both dimensions is a challenge for views that slower growth is the result of deep structural forces. And the combination of the slowdown in output growth with falling prices — especially given ultra-low interest rats — strongly suggests that we’ve seen a negative shift in desired spending (demand) rather than in the economy’s productive capacities (supply).

Another way of looking at this is as three different regimes. In the middle is what we might call “the main sequence” — here there is steady growth in demand, met by varying mixes of employment and productivity growth. On the upper right is what gets called a “high-pressure economy,” in which low unemployment and strong demand draw more people into employment and facilitates the reallocation of labor and other resources toward more productive activity, but put upward pressure on prices. On the lower left is stagnation, where weak demand discourages participation in the labor force and reduces productivity growth by holding back investment, new business formation and by leaving a larger number of those with jobs underemployed, and persistent slack leads to downward pressure on prices (though so far not outright deflation). In other words, macroeconomically speaking the past decade has been a sort of anti-1960s.

[1] There are actually two versions of Okun’s law, one relating the change in the unemployment rate to GDP growth and one relating the level of unemployment to the deviation of GDP from potential. The two forms will be equivalent if potential grows at a constant rate.

[2] The assumption that variables can be partitioned into “fast” and “slow” ones, so that we can calculate equilibrium values of the former with the latter treated as exogenous, is a very widespread feature of economic modeling, heterodox as much as mainstream. I think it needs to be looked at more critically. One alternative is dynamic models where we focus on the system’s evolution over time rather than equilibrium conditions. This is, I suppose, the kind of “theory” implied by VAR-type forecasting models, but it’s rare to see it developed explicitly. There are people who talk about a system dynamics approach, which seems promising, but I don’t know much about them.

CBO Forecasts: What’s Under the Hood?

In this post I want to say something about the methodology behind the CBO’s potential output forecasts. Here’s the tl;dr:

Officially, the CBO forecasts are based on a production function, which requires use of a number of unobservable parameters and questionable assumptions. But with one important exception, use of the the production function has no effect on the final estimate of potential output. The results are always very close to what you would get by simply extrapolating the trend of labor productivity.

The post is based on various CBO documents on their forecasting methodology, mainly this one, this one and this one, and on the relevant sections of the most recent Budget and Economic Outlook. It’s also much too long, mainly negative critique, and basically unnecessary to the larger argument I’m developing. Much of the post is devoted to the neoclassical production function (a serious demerit); since I’m far from an expert on it, there’s a nontrivial chance of embarrassing mistakes. You can keep reading or not.

Continue reading CBO Forecasts: What’s Under the Hood?

Trend, Forecast and Actual: Decomposing the Differences

Second post in a series. Post one is here.

The previous post argued that if we want to know how much of the slowdown in US growth is a result of the Great Recession, a reasonable starting point is to look at revisions to estimates of potential GDP since the recession. As it turns out, while CBO forecasts prior to the recession did predict slower growth than the long-run trend, the predicted slowdown was only about a quarter what we’ve actually seen. That suggests that most of the output shortfall relative to trend is due to the collapse in demand following the financial crisis, rather than to slower growth in the economy’s productive capacity.

The next natural step is to separate slower growth into various components and see how they behave individually. There are various ways to do this, but perhaps the most straightforward is the identity:

output = productivity * employment = productivity * laborforce * (1 – unemployment)

The big advantage of this is that we are working with fairly directly observable aggregates. Another advantage, important for present purposes, is that the CBO gives the relevant components for its estimates of potential output. Productivity here means labor productivity — output per worker. As applied to potential, unemployment means the non-accelerating inflation rate of unemployment, or NAIRU — the unemployment rate supposed to be consistent with stable inflation, which is targeted by the central bank.

So, here are the CBO’s forecasts of the three components over the past 10 years. The format is the same as the figure for output in the previous post: The horizontal axis is the year being forecasted, and the different lines represent forecasts made in various years — the blue-green ones before the start of the recession, the orange-red ones after it. (The forecasts are published in January, so the 2009 one is the first to incorporate data from the recession.) The heavy black lines show the actual historical behavior of the variable.

In the following graph, the forceast lines are for the NAIRU, the black line is for the actual unemployment rate.

We see some interesting things here. With respect to productivity, there are modest downward adjustments in 2007 and 2008 but the big adjustment come later, especially in 2009 and 2014. And the later adjustments are not just to the level of productivity but to the trend. Not only is there no convergence between actual productivity and pre-recession forecasts, the gap has continued to get wider over time. For laborforce, by contrast, the biggest adjustments come before the recession, especially in 2003, when the trend is revised downward. The post-recession revisions are smaller. The actual trajectory of the laborforce does show a definite reversion toward the immediate pre-recession forecasts. Finally, the estimated NAIRU was adjusted upward during the recession and back down since then with no systematic movement one way or the other. So the fairly stable gap between post-recession output and the pre-recession trend is a bit misleading. It combines two opposite developments, a widening productivity gap and a narrowing laborforce gap.

These results are summarized in the following table. The first column shows the difference between actual 2016 output and what you would predict by projecting forward the 1990-2006 trend. [1] The second column shows the deviation from trend that was already predicted in the CBO’s 2006 forecasts for 2016. The third column shows the revisions made since 2006.

	Actual vs Trend	Predicted vs Trend	Post-Recession Revision
Output	-14.1	-4.2	-10.4
Productivity	-5.4	5.1	-8.7
Laborforce	-9.2	-8.9	-1.8
Unemployment	-0.3	-0.4	0.1

What do we see here? Again, if we look at the shortfall of GDP relative to the pre-2006 trend, about 30 percent was predicted by the CBO. But the picture is quite different for employment and productivity taken separately. The deceleration in laborforce growth (which is about one-third slower population growth, two-thirds declining laborforce participation) was almost entirely predicted by the CBO. But in 2006 the CBO was also predicting above-trend productivity growth, which would have largely offset slower growth of the laborforce. The downward revisions over the past decade have mainly been to productivity — 9 percent, versus only a 2 percent downward revision to potential laborforce. Unemployment does not play an important role in either case — both actual unemployment and the estimated NAIRU are very close to their 2006 values. (This is different from Europe, where higher NAIRUs explain a large part of the change in potential output.)

Now this is a bit of a puzzle. I mentioned in the previous post a couple articles on hysteresis; I also very much like this piece by Laurence Ball. But all of them discuss hysteresis primarily in terms of the laborforce — the long-term unemployed giving up on job search and so on. That doesn’t mesh well with the fact that the downward revisions in potential output reflect mainly slower productivity growth rather than slower laborforce growth.

One natural way to interpret this is that (as Claudia Sahm suggests on twitter) the downward revisions in potential output since 2007 simply reflect a correction to earlier overestimates to productivity growth, which perhaps gave too much weight to a one-time acceleration in the 1990s. I ‘ll return in a later post to why I don’t accept this. For now, let’s just say that we take seriously the Summers-Ball view that downward revisions to potential output since the recession are a measure of hysteresis. Then we have to broaden our understanding of what hysteresis means. We can’t think of it as mainly a labor-market phenomenon.

In the next post, I’ll discuss a couple remaining points on the CBO forecasts. Then, a post arguing that the simultaneous deceleration of employment, productivity and prices looks more like an extended business-cycle downturn than a decline in the economy’s productive capacity. Then we’ll look at demographics and laborforce participation. And then back to the question of productivity, which I’d like to link to Joan Robinson’s concept of disguised unemployment.

[1] I use the years 1990 and 2006 because those are two years where actual output is very close to the CBO estimate of potential.

What Do Changing Estimates of Potential Output Tell Us?

I want to revisit the question we were debating last spring, about the space for additional expansionary policy in the US. How far is the economy from potential, in whatever relevant sense? This post will be the first in a series, and there will be a paper sometime in the fall.

One way to approach the question is to ask another one: How much of the shortfall in output relative to the pre-2008 trend is the result of the recession, as opposed to “structural” factors that would have led to slower growth in any case? The two questions are somewhat independent: Even if demographic factors, let’s say, were tending to reduce laborforce growth, there’s no reason in principle that couldn’t be overcome by stronger demand. On the other hand, even if we reject the idea that the recession itself resulted from a decline in productive capacity, it’s possible that a persistent demand shortfall could over time damage capacity in a way that can’t subsequently be repaired by restoring demand. Still, an output shortfall that is due to the collapse in spending in 2008-2009 is more likely to be reversed by increased spending, than one that is due to other causes.

Laurence Ball, DeLong and Summers, and Fatas and Summers, among others, try to answer the question of how much the decline in output is due to the recession, by comparing pre-recession estimates of potential output with more recent ones. A change in potential output attributable to changes in current output is often referred to as “hysteresis.” Changing forecasts are a reasonable measure of hysteresis: If predictable that structural factors like the changing age mix of the population were going to lead to slower growth, then it should in fact have been predicted; so systematic deviations from the forecasts must reflect something else. Now, if you are committed to the view that demand effects are strictly short-run, then a persistent deviation from trend necessarily reflects supply-side developments of some kind. But as long as we have no strong priors either way, the evolution of estimated potential over time should be informative about how much of the output shortfall is the result of the recession and how much is due to other causes.

The three papers do different versions of this exercise and all find that (1) the bulk of the slowdown in growth since 2008 is due to the recession, or at least was not predicted prior to it; and (2) there is no tendency for output to return to potential, rather, changes in current output are fully passed through to later estimates of potential. Here’s a simple version. The figure shows the CBO’s 10-year forecasts of potential GDP from 2002 through this year, along with historical GDP. (All are in 2009 dollars.)

The horizontal axis shows the year the estimate is for. The different lines show estimates made in different years. So the purple line at the top is the ten-year forecast of potential output published in January 2002, while the pink line at the bottom is the ten-year forecast published in January of this year. What do we see?

First, there has been a systematic reduction in estimates of potential. While there are some upward adjustment in the early years, more recently all the adjustments have been downward. The estimates of 2015, for example, first made in 2005, has been reduced every year since then. Same goes for 2016 and all future years. These are not random errors. And they are not small: the estimate of 2016 potential GDP made by the CBO in 2016 was more than 10 percent greater than the estimate this year.

Second, there is no tendency for output to return to earlier estimates of potential. While the official output gap has gotten much smaller since 2009, this is entirely a result of the downward adjustment of potential; there has been no closing of the gap between output and potential estimated in 2009 or earlier years.

On the other hand, these revisions can’t be all due to the recession, since the CBO significantly reduced its forecasts of potential output growth over 2005-2007. The largest revision comes in 2009, after the first year of recession. (Again, these are January forecasts.) But there had already been significant downward adjustments at that point. (Especially, as we’ll see in the net post, in predicted laborforce growth.) Still, most of the deviation from trend reflects post-recession adjustments in potential.

It breaks down like this. Current GDP is 12 percent below what you would have predicted based on long-run growth rates up to 2008. The CBO puts the current output gap at around 2 percent. This reflects the fact that the CBO currently considers full employment to be 4.8 percent unemployment, slightly below the current level. The remainder of the 12-point gap represents a slowdown in potential output growth. How much of that was predicted in 2005? Less than none – at that time, the CBO’s forecast for 2015 output was 1.5 percent above the long run trend. By January 2008 — the last pre-recession forecast — the CBO had revised its 2015 forecast down by about 4 percent, to 3 percent below trend. In 2009, after the first year of the recession, it revised it down another 3 points, to 6 percent below trend. And over the past seven years it’s been revised down seven more times for a total of 5 points, to reach the current estimate of potential of around 10 percent below trend. So about a quarter of the 12 point gap between current GDP and its long-run trend was predicted before the recession.

Now the fact that the slowdown was not predicted before the recession, doesn’t prove that it is due to the recession. It does, I think, allow us to reject things like “aging of the baby boomers” as the main explanation for the shortfall: Something that easily predictable, would have been predicted. (And as we’ll see in a later post, demographic changes cannot in fact explain the slowdown in output growth— the effect of aging on labor force participation, while real, is too small to explain the actual decline, and it’s offset by a comparable but less-discussed shift in the other direction — the declining share of households with young children.) It is, however, possible that some new development (a “shock” in the jargon, but I don’t like this term) just happened to reduce the economy’s productive capacity at the same time it was recovering from the recession.

In their 2012 article, DeLong and Summers argue that the absence of wage and price growth is strong evidence against this latter explanation:

It is possible that these revisions reflect not … hysteresis but merely the recognition that previous forecasts of potential output were too high. However, an elementary signal extraction point rebuts this interpretation. … one should not reduce one’s estimate of potential output if lower-than-previously-expected levels of production are associated with lower-than-previously-expected levels of inflation. … Typically, the bad news that leads to a marking down of potential output is not news that output is lower than, but rather news that output and inflation together are above, their anticipated co-movement line. Such news is not in evidence.

Over the past four years inflation has only fallen further, so the point presumably still holds.

So if we take the unpredicted decline in potential as a measure of the effects of the recession, we’re left with something like this: Of the gap between actual US GDP and its pre-2008 trend, 75 percent is due to the continuing effects of the recession, 25 percent to other factors. That seems like a reasonable place to start.

Links for March 25

Some links, on short-termism, trade, the Fed and other things.

Senators Tammy Baldwin and Jeff Merkley have introduced a bill to limit activist investors’ ability to push for higher payouts. The bill, which is cosponsored by Bernie Sanders and Elizabeth Warren, would strengthen the 13D disclosure requirements for hedge funds and others acquiring large positions in a corporation. This is obviously just one piece of a larger agenda, but it’s good to see the “short-termism’ conversation leading to concrete proposals.

I’m pleased to be listed as one of the supporters of the bill, but I think the strongest endorsement is this furious reaction from a couple of hedge fund dudes. It’s funny how they take it for granted that shareholder democracy is on the same plane as democracy democracy, but my favorite bit is, “Shareholders do not cause bad management, just as voters do not cause bad politicians.” This sounds to me like an admission that shareholders are functionless parasites — if they aren’t responsible for the quality of management, what are we paying them all those dividends for?

I wrote a twitter essay on why the US shouldn’t seek a more favorable trade balance.

Jordan Weissman thinks I was “a bit ungenerous” to Trump.

My Roosevelt Institute colleague Carola Blinder testified recently on reform of the Fed, making the critical point that we need to take monetary policy seriously as a political question. “Contrary to conventional thinking, the rules of central banking are not neutral: Both monetary policy and financial supervision have profound effects on income and wealth inequality … [and] are the product of political contestation and compromise.” Relatedly, Mark Thoma suggests that the Fed “cares more about the interests of the rich and powerful than it does the working class”; his solution, as far as I can tell, is to hope that it doesn’t.

Matt Bruenig has a useful post on employment by age group in the US v the Nordic countries. As he shows, the fraction of people 25-60 working there is much higher than the fraction here (though workers here put in more hours). This has obvious relevance for the arguments of the No We Can’t caucus that there’s no room for more stimulus, because demographics.

A reminder: “Ricardian equivalence” (debt and tax finance of government spending have identical effects on private behavior) was explicitly denied by David Ricardo, and the “Fisher effect” (persistent changes in inflation lead to equal movements of nominal interest rates, leaving real rates unchanged) was explicitly denied by Irving Fisher. One nice thing about this piece is it looks at how textbooks describe the relationship between the idea and its namesake. Interesting, Mankiw gets Fisher right, while Delong and Olney get him wrong: They falsely attribute to him the orthodox view that nominal interest rates track inflation one for one, when in fact he argued that even persistent changes in inflation are mostly not passed on to nominal rates.

Here is a fascinating review of some recent books on the Cold War conflicts in Angola. One thing the review brings out was how critical the support of Cuba was to South Africa’s defeat there, and how critical that defeat in turn was to the end of apartheid. We tend to take it for granted that history had to turn out as it did, but it’s worth asking if, in the absence of Castro’s commitment to Angola, white rule in South Africa might have ended much later, or not at all.

Plausibility, Continued

Real output per worker, 1921-1939:

The Depression didn’t just see a fall in employment, it saw a fall in the output of those still employed, reversing much of the productivity gains of the 1920s. (This surprised Keynes, among others, who still believed in the declining marginal product of labor, which predicted the opposite.) Recovery in the late 1930s, conversely, didn’t just mean higher employment, it involved a sharp acceleration in labor productivity. There’s a widespread idea that output per worker necessarily reflects supply-side factors — technology, skills, etc. But if demand had such direct effects on labor productivity in the Great Depression, why not in the Lesser Depression too? But for some reason, people who scoff at the idea of the “Great Forgetting” of the 1930s have no trouble believing that the drastic slowdown in productivity growth of recent years has nothing to do with the economic crisis it immediately followed.

EDIT: I should add: While the decline in production during the Depression was, of course, primarily a matter of reduced employment, the decline in productivity was not trivial. If output per employee had continued to rise in the first half of the 1930s at the same rate as in 1920s, the total fall in output would have been on the order of 25 percent rather than 33 percent.

Note also that the only other comparable (in fact larger) fall in GDP per worker came in the immediate postwar demobilization period 1945-1947. I’ve never understood the current convention that says we should ignore the depression and wartime experience when thinking about macroeconomic relationships. Previous generations thought just the opposite — that we can learn the most about how the system operates from these kinds of extreme events, that “the prime test of Keynesian theory must be the Great Depression.” Isn’t it logical, if you want to understand how shifts in aggregate demand affect economic outcomes, that you would look first at the biggest such shifts, where the effects should be clearest? The impact of these two big demand shifts on output per worker, seem like good reason to expect such effects in general.

And it’s not hard to explain why. In real economies, there are great disparities in the value of the labor performed by similar people, and immense excess capacity in the form of low-productivity jobs accepted for lack of anything better. Increased demand mobilizes that capacity. When the munitions factories are running full tilt, no one works shining shoes.

Plausibility

This shows the initial deviation of real per-capita GDP from its long run trend, and the average growth rate over the following ten years, for 1925 through 2005. The long run trend is based on the 1925-2005 average growth rate of real per-capita GDP of 2.3%. The points in the upper left are the ten-year periods beginning in 1931 through 1941.

UPDATE: A number of people have objected to this exercise on the grounds that the Depression and World War II period is not relevant for our current situation. I don’t agree with this. But even without them, the picture is not so different. While the postwar period up til now has never seen a persistent deviation from trend as we are experiencing now, or as rapid growth as the Friedman paper projects, the relationship between the two is clearly present. And a decade of growth far above the postwar norm turns out to be just what you would predict on the basis of that relationship. Here’s the same graph as above, but this time using only 1947-2005.

As you can see, the relationship is a fairly strong one. The Friedman growth number does lie a bit above the regression line. But it’s still true that the current exceptionally low level of GDP relative to trend would, on historical evidence, lead us to expect that growth over the next ten years will be around 3.8 percent — well above anything previously seen in the postwar period and close to double the long-term average.

Note that the seven points well below the line in the middle are 1999-2005, whose 10-year growth windows include the Great Recession. Without them, Friedman’s number would be much closer to the line. What do we make of that? Should the exceptionally poor performance of this period make us more pessimistic about medium-term growth prospects (it’s sign of supply-side exhaustion) or more optimistic (it’s a sign of a demand gap that can be filled)? This is not an easy question to answer. But just counting up previous growth rates won’t help answer it.

Can Sanders Do It?

My old professor Jerry Friedman wrote a piece several weeks ago, arguing that a combination of increased public spending and income redistribution (higher minimum wages and other employment regulation favorable to labor) proposed by the Sanders campaign could substantially boost growth and employment during his presidency. As readers of this blog know, this piece has gotten a lot of attention in the past couple of days. Most notably, it inspired a letter from four former CEA chairs strongly rejecting the claim that Sanders proposals could “have huge beneficial impacts on growth rates, income and employment that exceed even the most grandiose predictions by Republicans about the impact of their tax cut proposals.” A number of prominent liberal economists have endorsed the CEA letter or expressed similar doubts.

I want to try to clarify the stakes in this debate. There are three questions, each logically prior to the other.

1. Is it reasonable to think that better macroeconomic policy could deliver substantially higher output and employment?
2. Are the kinds of things proposed by Sanders capable in principle of getting us there?
3. Are the specific numbers in Sanders’ proposals the right ones for such a really-full employment plan?

The second question doesn’t matter until we’ve answered yes to the first one. And the third doesn’t matter until we’ve answered yes to the first two.

The first question is not only logically prior, it also seems to be what the public debate is actually about . The CEA letter, and almost all the other criticism of the Friedman paper I have seen, focuses on whether the outcomes described are plausible at all, not the specific ways they are derived from the Sanders proposals. Almost all the pushback I have seen has been to the effect that 5 percent real GDP growth and 275,000 new jobs per month are not possible results of any conceivable macro policies.

As I’m sure Jerry Friedman would agree, there are plenty of ways his estimates could be improved. But it’s pointless, even disingenuous, to debate the specific numbers before agreeing on the larger questions. I want to focus on the first question here, both because it is the premise of the others and because it is where the debate is currently located.

So: Is it plausible that there could be 5 percent-plus real GDP growth and 300,000 new jobs per month over the eight years of a Sanders presidency? I think it is — or at least, I don’t think there is a good economic argument that it’s not.

I want to make five related points here. First, conventional wisdom in economics is that an exceptionally deep recession should be followed by a period of exceptionally strong growth. Second, the growth in output and employment implied by the paper are more or less what is required to return to the pre-recession trend. Third, discussions of macroeconomic policy in other contexts imply the possibility of growth qualitatively similar to what Jerry describes. Fourth, it is not necessarily the case that the employment Jerry projects would exceed full employment in any meaningful sense. Fifth, if you don’t believe a growth performance at this level is possible, that implies a sharp slowdown in potential output, for which you need a credible story. The last point is probably the most important.
1. It’s not controversial to say that a historically deep recession ought to be followed by a period of historically strong growth. Every macroeconomics textbook teaches that changes in GDP can be split into two components: short-run variation driven by aggregate demand and by monetary and financial factors, and a long-run trend driven by population growth and technological change. While all sorts of things that constrain or inhibit spending can cause temporary dips in production, over time it should converge back to the fundamentals-determined trend. Unless they involve the destruction of real resources — and they don’t — recessions should not have lasting effects. A direct corollary of this textbook view is that the deeper the recession, the stronger should be growth in the following period — otherwise, there’s no way to get back to trend. The people who are saying that Jerry’s growth numbers are impossible on their face are implicitly saying that that we should expect all output losses in recessions to be permanent. This is not orthodox economic theory, at all. Orthodoxy says that the exceptionally deep recession should be followed by a period of exceptionally strong growth — and if it hasn’t been, that suggests some ongoing demand problem which policy can reasonably be expected to solve.
2. Friedman’s growth estimates are just what you need to get output and employment back to trend. This point is well made by Matthew Klein. As Klein puts it, this “supposedly ‘extreme’ and ‘unsupportable’ forecast implies American output will return to its previous trend just as Sanders would be finishing up his second term, in the third quarter of 2024.”

As Klein and others point out, the level of GDP projected by Jerry for the end of Sanders’ second term is right in line with what the CBO and other establishment forecasters were saying just a few years ago. I just now was looking at the CBO’s forecasts as of January 2013; they were projecting 4-4.5 percent real GDP growth over 2016-2017. This is, of course, exceptionally high by historical standards — Paul Krugman says that Jeb Bush was “rightly mocked” by progressives for suggesting he could deliver growth at that level. But the CBO was making the same prediction and it’s no mystery why — a period of growth well above historical levels is the logical condition of a return of output to trend. By the way, I should emphasize that Friedman’s growth estimates were not derived this way. It’s just a lucky coincidence — if it holds up — that the measures proposed by the Sanders campaign happen to be the right magnitude to close the output gap over eight years.

Similarly, Friedman’s employment numbers (around 277,000 new jobs per month) are indeed way above what we have seen recently. But if you want to get the employment-population ratio back to its 2006 levels by 2024, you need even more than that — about 300,000 new jobs per month, by my calculations. Many respectable economists — including at least one of the CEA signers — have written that the employment ratio is a better indicator of labor-market conditions than the unemployment rate, and expressed concern about its decline. A few years ago, Brad DeLong had no doubt that more expansionary policy could raise the employment population ratio back to 60.8 percent, if not to the pre-recession level of 63 percent: “we could still put 5.5 million more people to work with appropriate demand-management policies.” To do that by 2024 would imply monthly job growth around 220,000 — less than what Friedman claims for the Sanders proposals, but ~~about double what~~ ~~we are seeing now~~ more than double what the CBO is currently projecting for 2017-2024. It’s just arithmetic: you can’t raise the employment-population ratio without a sustained period of job growth substantially higher than what we are seeing now. So it makes no sense to talk about that as a goal if you think that faster job growth is not a feasible outcome for policy.

It is true, of course, that the aging of the population implies a long-term fall in the employment ratio, all else equal. But let’s put this in perspective. DeLong, for example, suggests that 0.13 points per year is probably an overestimate of the decline due to demographics. David Rosnick, applying the 2006 employment ratios of various age groups to the population projected for 2026, finds a larger decline due to demographics, on the order of 0.25 points per year. But even that leaves most of the fall in employment unexplained by demographics. By any standard, there is a lot of room to do better. But we have to agree that this is something that, in principle, demand side policy can do.

rosnick-2014-12-23-fig4 — *from David Rosnick*

3. In other contexts, it’s taken for granted that more expansionary policy could deliver substantially higher growth. Anyone who says that the zero lower bound is a constraint on monetary policy, or who suggests that the “natural rate of interest” is negative, is saying that output could be substantially higher given more expansionary monetary policy. Presumably, this is true for other forms of expansionary policy as well. (In terms of the model beloved by undergraduate textbooks and New York Times columnists: If the preferred point in ISLM space is to the right of the current one, we should be able to get there by shifting the IS curve just as well as by shifting the LM curve.) Obviously, the transition to that higher level of GDP would involve a period of much higher growth. It would be interesting to ask how fast output would have grown if we’d been able to remove the ZLB constraint in, say, 2010; I suspect the numbers might not look that different from Friedman’s.

Similarly, most participants in this debate agree that the ARRA stimulus of 2009 was effective, with multipliers above 2.0 for at least some categories of spending. Many also think that it should have been bigger. If increased government spending could boost output in 2008, then why couldn’t it today? And if the right answer to “how big?” then was “enough to close the output gap,” why isn’t that the right answer today? Yes, it would be a big number. (Again, it’s a lucky coincidence — if correct — that it happens to be close to what Sanders is proposing.) But so what? If “a trillion has a lot of zeroes” wasn’t a good argument against an adequate stimulus in 2009, then it isn’t one today.

Or again: If we think that austerity explains a big part of poor growth in European countries, we have to at least consider the the same might be true here. It would be very good luck, to say the least, if years of feuding between the administration and Republican congresses had somehow delivered exactly the right fiscal balance. In general, this discussion has been muddied by the fact that the pragmatic choice to delegate demand management to central banks, has been turned into an axiom in economic theory. From where I’m sitting, the statement “it would be helpful if the central bank set a lower interest rate” is equivalent, for most macroeconomic purposes, with the statement “it would be helpful if the level of public spending were higher.”

4. Friedman’s projections are unreasonable only if you think the US is already at full employment. The unstated but central premise of the critics is that we are at or near full employment, so there is no space for further demand policy. Friedman’s paper says that by the end of a second Sanders term, unemployment would be at 3.8%. Krugman replies: “It’s possible that we can get unemployment down under 4 percent, but that’s way below any estimates I’ve seen of the level of unemployment consistent with moderate inflation.” Now here we have an interesting question. Whether we are at full employment today depends, first, on how much you think the fall in the employment-population ratio reflects weak demand as opposed to structural or demographic factors — or in other words, to what extent faster job growth would draw nonworkers into the labor market, as opposed to pushing down the unemployment rate. But it also depends on what you think full employment means.

If you believe that any demand-induced acceleration of nominal wage growth will be passed to higher prices, or if you think that price stability should be the sole concern of macro policy, then there will be a hard floor on unemployment, which may not be much lower than where we are today. But if you think some appreciable fraction of faster nominal wage growth would go to an increase in the wage share (or faster productivity growth) rather than to inflation, and if you think some acceleration in inflation is acceptable (or even desirable), then “full employment” becomes a broad region rather than a sharp line. (I wrote a bit about these issues here.) In this case there will even be an argument — made by plenty of mainstream people, including some of the ones criticizing Friedman now — that a period of “overfull” employment would be desirable to bring the wage share back up from its current historically low levels. To believe that a 3.8% unemployment rate is ruled out by price stability considerations is to claim that faster wage growth cannot raise the wage share, which I don’t think is well supported either theoretically or empirically. (Or that raising the wage share is not desirable.) Also worth recalling: In the debates around the NAIRU in the 1990s, the general conclusion was that the idea of a hard floor to unemployment below which inflation will rise uncontrollably, is not in fact a useful guide for policy.

5. The argument against Friedman’s piece comes down to the claim that the economy is already close to potential. If this is the case then, yes, claims that increased public spending can achieve large gains in output are delusional. I think this is a useful debate to have, but I’m not sure how the CEA chairs would make the case. First, again, many of those criticizing Friedman’s numbers have supported the idea of more expansionary policy in other contexts. Second and more fundamentally, the persistent fall in the employment population ratio and the deviation of output from pre-recession trend seem very hard to explain in “supply” terms. Yes, there are demographic changes, but again, even if you hold the age distribution of the population constant, the employment ratio is still 3 points lower than at the start of the recession. That’s a deficit of 10 million jobs. Closing that gap requires an extended period of above average growth, qualitatively similar to what Friedman describes. If you believe that’s impossible, you have to explain why.

Logically, there are a couple possible answers. Either you argue that the earlier estimates of potential GDP were exaggerated, and we were at overfull employment prior to the recession. If you take this route, you have to be ready to make the case that the country needed substantially slower growth and higher unemployment in the 2000s, despite the noticeable lack of wage growth or rising inflation. Or, you can claim that something happened in 2008-2009 that permanently reduced potential output. So then, what is the negative technological shock that hit the economy in 2008-2009? Is Casey Mulligan right that American businesses have been crippled by the red tape of Obamacare? I don’t think either of those are good options for liberals. Another possibility is to talk about hysteresis and so on — the persistent effects on the laborforce and productivity growth from periods of weak demand. Here you will be on firmer ground — there is plenty of evidence that deep recession inflict lasting harm on workers and businesses. But this kind of reasoning makes Friedman’s numbers more plausible, not less. Because if weak demand can drag potential output down, strong demand can presumably pull it up.

The bottom line is this. Ten years ago, the CBO expected GDP to be $20.5 trillion (correcting for inflation) as of the end of 2015. Today, it is $18.1, trillion, or about 12 percent lower. Similarly, the employment-population ratio fell by 5 points during the recession (from 63.4 to 58.4 percent) and has risen by only one point during the past six years of recovery. Either these facts — unprecedented in the postwar period — reflect a shortfall of effective demand, or they don’t. If they do reflect a lack of demand, then there is no reason the expanded pubic spending and downward redistribution that Sanders proposes cannot close the gap, with a period of high growth while output and employment return to trend. (The fact that such high growth hasn’t been seen in the postwar period is neither here nor there, since there also has been no comparable deviation from trend.) Alternatively, you may think that the shortfall relative to previous growth rates reflects a decline in potential output. But then you need to offer some explanation of why the growth of the economy’s productive capacity slowed so abruptly, and you need to apply this belief consistently. I think it’s more reasonable to believe that the gaps in output and employment reflect a demand shortfall. In which case, the Sanders plan could in principle have the kind of results Friedman describes.

UPDATE: There was a significant error in section 2, which I’ve corrected.