Tag: aggregate demand

The Persistence of Demand

Here’s the very short version of this very long post:

Hysteresis means that a change in GDP today has effects on GDP many years in the future. In principle, this could be because it affects either future aggregate demand or potential output. These two cases aren’t distinguished clearly in the literature, but they have very different implications. The fact that the Great Recession was followed by a period of low inflation, slow wage growth and low interest rates, rather than the opposite, suggests that the persistent-demand form of hysteresis is more important than potential-output hysteresis. The experience of the Great Recession is consistent with perhaps 20 percent of a shock to demand in this period carrying over to demand in future periods. This value in turn lets us estimate how much additional spending would be needed to permanently return GDP to the pre-2007 trend: 50-60 percent of GDP, or $10-12 trillion, spread out over a number of years.

 

Supply Hysteresis and Demand Hysteresis

The last few years have seen renewed interest in hysteresis – the idea that shifts in demand can have persistent effects on GDP, well beyond the period of the “shock” itself. But it seems to me that the discussion of hysteresis doesn’t distinguish clearly between two quite different forms it could take.

On the one hand, demand could have persistent effects on output because demand influences supply – this seems to be what people usually have in mind. But on the other hand, demand itself might be persistent. In time-series terms, in this second story aggregate spending behaves like a random walk with drift. If we just look at the behavior of GDP, the two stories are equivalent. But in other ways they are quite different.

Let’s say we have a period in which total spending in the economy is sharply reduced for whatever reason. Following this, output is lower than we think it otherwise would have been. Is this because (a) the economy’s productive potential was permanently reduced by the period of reduced spending? Or is it (b) because the level of spending in the economy was permanently reduced? I will call the first case supply hysteresis and the second demand hysteresis.

On the left, supply hysteresis. On the right, demand hysteresis.

It might seem like a semantic distinction, but it’s not. The critical thing to remember is that what matters for much of macroeconomic policy is not the absolute level of output but the output gap — the difference between actual and potential output. If current output is above potential, then we expect to see rising inflation. (Depending on how “potential” is understood, this is more or less definitional.) We also expect to see rising wages and asset prices, shrinking inventories, longer delivery times, and other signs of an economy pushing against supply constraints. If current output is below potential, we expect the opposite — lower inflation or deflation, slower wage growth, markets in general that favor buyers over sellers. So while lower aggregate supply and lower aggregate demand may both translate into lower GDP, in other respects their effects are quite different. As you can see in my scribbles above, the two forms of hysteresis imply opposite output gaps in the period following a deep recession. 

Imagine a hypothetical case where there is large fall in public spending for a few years, after which spending returns to its old level. For purposes of this thought experiment, assume there is no change in monetary policy – we’re at the ZLB the whole time, if you like. In the period after the depressed spending ends, will we have (1) lower unemployment and higher inflation than before, as the new income created during the period of high public spending leads to permanently higher demand. Or will we have (2) higher unemployment and lower inflation than if the spending had not occurred, because the period of high spending permanently raised labor force participation and productivity, while demand returns to its old level?

Supply hysteresis implies (1), that a temporary negative demand shock will lead to persistently higher inflation and lower unemployment (because the labor force will be smaller). Demand hysteresis implies (2), that a temporary negative demand shock will lead to permanently lower inflation and higher unemployment. Since the two forms of hysteresis make diametrically opposite predictions in this case, seems important to be clear which one we are imagining. Of course in the real world, could see a combination of both, but they are still logically distinct. 

Most people reading this have probably seen a versions of the picture below. On the eve of the pandemic, real per-capita GDP was about 15 percent below where you’d expect it to be based on the pre-2007 trend. (Or based on pre-2007 forecasts, which largely followed the trend.) Let’s say we agree that the deviation is in some large part due to the financial crisis: Are we imagining that output has persistently fallen short of potential, or that potential has fallen below trend? Or again, it might be a combination of both.

In the first case, we would expect monetary policy to be generally looser in the period after a negative demand shock, in the second case tighter. In the first case we’d expect lower inflation in period after shock, in the second case higher.

It seems to me that most of the literature on hysteresis does not really distinguish these cases. This recent IMF paper by Antonio Fatas and coauthors, for example, defines hysteresis as a persistent effect of demand shocks on GDP. This could be either of the two cases. In the text of the paper,  they generally assume hysteresis means an effect of demand on supply, and not a persistence of demand itself, but they don’t explicitly spell this out or make an argument for why the latter is not important.

It is clear that the original use of the term hysteresis was understood strictly as what I am calling supply hysteresis. (So perhaps it would be better to reserve the word for that, and make ups new name for the other thing.) If you read the early literature on hysteresis, like these widely-cited Laurence Ball papers, the focus was on the European experience of the 1980s and 1990s; hysteresis is described as a change in the NAIRU, not as an effect on employment itself. The mechanism is supposed to be a specific labor-market phenomenon: the long term unemployed are no longer really available for work, even if they are counted in the statistics. In other words, sustained unemployment effectively shrinks the labor force, which means that in the absence of policy actions to reduce demand, the period following a deep recession will see faster wage growth and higher inflation than we would have expected.

(This specific form of supply hysteresis implies a persistent rise in unemployment following a downturn, just as demand hysteresis does. The other distinctions above still apply, and other forms of supply hysteresis would not have this implication.) 

Set aside for now whether supply-hysteresis was a reasonable description of Europe in the 1980s and 1990s. Certainly it was a welcome alternative to the then-dominant view that Europe needed high unemployment because of over-protective labor market institutions. But whether or not thinking of hysteresis in terms of the NAIRU made sense in that context, it does not make sense for either Europe or the US (or Japan) in the past decade. Everything we’ve seen has been consistent with a negative output gap — with actual output below potential — with a depressed level of demand, not of supply. Wage growth has been unexpectedly weak, not strong; inflation has been below target; and central banks have been making extra efforts to boost spending rather than to rein it in.

Assuming we think that all this is at least partly the result of the 2007-2009 financial crisis — and thinking that is pretty much the price of entry to this conversation — that suggests we should be thinking primarily about demand-hysteresis rather than supply-hysteresis. We should be asking not, or not only, how much and how durably the Great Recession reduced the country’s productive potential, but how how durably it reduced the flow of money through the economy. 

It’s weird, once you think about it, how unexplored this possibility is in the literature. It seems to be taken for granted that if demand shocks have a lasting effect on GDP, that must be because they affect aggregate supply. I suspect one reason for this is the assumption — which profoundly shapes modern macroeconomics — that the level of spending in the economy is directly under the control of the central bank. As Peter Dorman observes, it’s a very odd feature of modern macroeconomic modeling that the central bank is inside the model — the reaction of the monetary authorities to, say, rising inflation is treated as a basic fact about the economy, like the degree to which investment responds to changes in the interest rate, rather than as a policy choice. In an intermediate macroeconomics textbook like Carlin and Soskice (a good one as far as they go), students are taught to think about the path of unemployment and inflation as coming out of a “central bank preference function,” which is taken as a fundamental parameter of the economy. Obviously there is no place for demand hysteresis in this framework. To the extent that we think of the actual path of spending in the economy as being chosen by the central bank as part of some kind of optimizing process, past spending in itself will have no effect on current spending. 

Be that as it may, it seems hard to deny that in real economies, the level of spending today is strongly influenced by the level of spending in the recent past. This is the whole reason we see booms and depressions as discrete events rather than just random fluctuations, and why they’re described with metaphors of positive-feedback process like “stall speed” or “pump-priming.”1

How Persistent Is Demand?

Let’s say demand is at least somewhat persistent. That brings us to the next question: How persistent? If we were to get extra spending of 1 percent of GDP in one year, how much higher would we now expect demand to be several years later?

We can formalize this question if we write a simple model like:

Zt = Z*t + Xt

Z*t = (1+g) Z*t-1 + a(Zt-1 – Z*t-1)

Here Z is total spending or demand, Z* is the trend, what we might think of as normal or expected demand, g is the normal growth rate, and X is the influence of transitory influences outside of normal growth.

With a = 0, then, we have the familiar story where demand is a trend plus random fluctuations. If we see periods of above- and below-trend demand, that’s because the X influences are themselves extended over time. If a boom year is followed by another boom year, in this story, that’s because whatever forces generated it in the first year are still operating, not because the initial boom itself was persistent. 

Alternatively, with a = 1, demand shocks are permanent. Anything that increases spending this year, should be expected to lead to just as much additional spending next year, the year after that, and so on.

Or, of course, a can have any intermediate value. 

Think back to 2015, in the debate over the first Sanders’ campaign’s spending plans that was an important starting point for current discussions of hysteresis. The basic mistake Jerry Friedman was accused of making was assuming that changes in demand were persistent — that is, if the multiplier was, say 1.5, that an increase in spending of $500 billion would raise output by $750 billion not only in that year and but in all subsequent years. As his critics correctly pointed out, that is not how conventional multipliers work. In terms of my equations above, he was setting a=1, while the conventional models have a=0. 

He didn’t spell this out, and I didn’t think of it that way at the time. I don’t think anyone did. But once you do, it seems to me that while Friedman was wrong in terms of the standard multiplier, he was not wrong about the economy — or at least, no more wrong than the critics. It seems to me that both sides were using unrealistically extreme values. Demand shocks aren’t entirely permanent, but they also aren’t entirely transitory.  A realistic model should have 0 < a < 1.

Demand Persistence and Fiscal Policy

There’s no point in refighting those old battles now. But the same question is very relevant for the future. Most obviously, if demand shocks are persistent to some significant degree, it becomes much more plausible that the economy has been well below potential for the past decade-plus. Which means there is correspondingly greater space for faster growth before we encounter supply constraints in the form of rising inflation. 

Both forms of hysteresis should make us less worried about inflation. If we are mainly dealing with supply hysteresis, then rapid growth might well lead to inflation, but it would be a transitory phenomenon as supply catches up to the new higher level of demand.  On the other hand, to the extent we are dealing with demand hysteresis, it will take much more growth before we even have to worry about inflation.

Of course, both forms of hysteresis may exist. In which case, both reason for worrying less about inflation would be valid. But we still need to be clear which we are talking about at any given moment.

A slightly trickier point is that the degree of demand persistence is critical for assessing how much spending it will take to get back to the pre-2007 trend. 

If the failure to return to the pre-2007 is the lasting effect of the negative demand shock of the Great Recession, it follows that  sufficient spending should be able to reverse the damage and return GDP to its earlier trend. The obvious next question is, how much? The answer really depends on your preferred value for a. In the extreme (but traditional) case of a=0, each year we need enough spending to fill the entire gap, every year, forever. Given a gap of around 12 percent, if we assume a multiplier of 1.5 or so, that implies additional public spending of $1.6 trillion. In the opposite extreme case, where a=1, we just need enough total spending to fill the gap, spread out over however many years. In general, if we want to get close a permanent (as opposed to transitory) output gap of W, we need W/(a μ) total spending, where μ is the conventional multiplier.2

If you project forward the pre-2007 trend in real per-capita GDP to the end of 2019, you are going to get a number that is about 15% higher than the actual figure, implying an output gap on the order of $3.5 trillion. In the absence of demand persistence, that’s the gap that would need to be filled each year. But with persistent demand, a period of elevated public spending would gradually pull private spending up to the old trend, after which it would remain there without further stimulus.

What Does the Great Recession Tell Us about Demand Persistence?

At this point, it might seem that we need to turn to time-series econometrics and try to estimate a value for a, using whatever methods we prefer for such things. And I think that would be a great exercise! 

But it seems to me we can actually put some fairly tight limits on a without any econometrics, simple by looking back to the Great Recession. Keep in mind, once we pick an output gap for a starting year, then given the actual path of GDP, each possible value of a implies a corresponding sequence of shocks Xt. (“Shock” here just means anything that causes a deviation of demand from its trend, that is not influenced by demand in the previous period.) In other words, whatever belief we may hold about the persistence of demand, that implies a corresponding belief about the size and duration of the initial fall in demand during the recession. And since we know a fair amount about the causes of the recession, some of these sequences are going to be more plausible than others.

The following figures are an attempt to do this. I start by assuming that the output gap was zero in the fourth quarter of 2004. We can debate this, of course,, but there’s nothing heterodox about this assumption — the CBO says the same thing. Then I assume that in the absence of exogenous disturbances, real GDP per capita would have subsequently grown at 1.4 percent per year. This is the growth rate during the expansion between the Great Recession and the pandemic; it’s a bit slower than the pre-recession trend.3 I then take the gap between this trend and actual GDP in each subsequent quarter and divide it into the part predictable from the previous quarter’s gap, given an assumed value for a, and the part that represents a new disturbance in that period. So each possible value of a, implies a corresponding series of disturbances. Those are what are shown in the figures.

If you’re not used to this kind of reasoning, this is probably a bit confusing. So let me put it a different way. The points in the graphs above show where real GDP would have been relative to the long-term trend if there had been no Great Recession. For example, if you think a = 0, then GDP in 2015 would have been just the same in the absence of the recession, so the values there are just the actual deviation from trend. So you can think of the different figures here as showing the exogenous shocks that would be required under different assumptions about persistence, to explain the actual deviation from trend. They are answering this question: Given your beliefs about how persistent demand is, what must you think GDP would have been in subsequent years in a world where the Great Recession did not take place? (Or maybe better, where the fall in demand form the housing bubble was fully offset by stimulus.)

The first graph, with persistence = 0, is easiest to understand. If there is no carryover of demand shocks from one period to the next, then there must be some factor reducing demand in each later period by the full extent of the gap from trend. If we move on to, say, the persistence=0.1 figure, that is saying that, if you think 10 percent of a demand shock is normally carried over into future periods, that means that there was something happening in 2012 that would have depressed demand by 2 percent relative to the earlier trend, even if there had been no Great Recession. 

Because people are used to overcomplicated economics models, I want to stress again. What I am showing you here is what you definitionally believe, if you think that in the absence of the Great Recession, growth in the 2010s would have been at about the same rate it was, just from a higher base, and you think that whatever fraction of a change in spending in one year is carried over to the next year. There are no additional assumptions. I’m just showing what the logical corollary of those beliefs would be for the pattern of demand shocks,

Another important feature of these figures is how large the initial fall in demand is. Logically, if you think demand is very persistent, you must also think the initial shock was smaller. If most of the fall in spending in the first half of 2008, say, was carried over to the second half of 2008, then it takes little additional fall in spending in that period to match the observed path of GDP. Conversely, if you think that very little of a change in demand in one period carries over to the next one then the autonomous fall in demand in 2009 must have been larger.

The question now is, given what we know about the forces impacting demand a decade ago, which of these figures is most plausible? If there had been sufficient stimulus to completely eliminate the fall in demand in 2007-2009, how strong would the headwinds have been a few years late? 

Based on what we know about the Great Recession, I think demand persistence in the 0.15 – 0.25 range most plausible. This suggests that a reasonable baseline guess for total spending required to return to the pre-2007 would be around 50 percent of GDP, spread out over a number of years. With an output gap of 15 percent of GDP, a multiplier of 1.5, and demand persistence of 0.2, we have 15 / (1.5 * 0.2) = 50 percent of GDP. This is, obviously, a very rough guess, but if you put me on the spot and asked how much spending over ten years it would take to get GDP permanently back to the pre-2007 trend, $10-12 trillion would be my best guess.

How do we arrive at persistence in the 0.15 – 0.25 range?

On the lower end, we can ask: What are the factors that would have pushed down demand in the mid 2010s, even in the absence of the Great Recession Remember, if we use demand persistence of 0.1, that implies there were factors operating in 2014 that would have reduced demand by 2 percent of GDP, even if the recession had not taken place. What would those be?

I don’t think it makes sense to say housing — housing prices had basically recovered by then. State and local spending is a better candidate — it remained quite depressed and I think it’s hard to see this as a direct effect of the recession. Relative to trend, state and local investment was down about 1 percent of GDP in 2014, while the federal stimulus was basically over. On the other hand, unless we think that monetary policy is totally ineffective, we have to include the stimulative effect of a zero policy rate and QE in our demand shocks. This makes me think that by 2014, the gap between actual GDP and the earlier trend was probably almost all overhang from the recession. And this implies a persistence of at least 0.15. (If you look back at the figures, you’ll see that with persistence=0.15, the implied shock reaches zero in 2014.)

Meanwhile, on the high end, a persistence of 0.5 would mean that the demand shock maxed out at a bit over 3 percent of GDP, and was essentially over by the second half of 2009. This seems implausibly small and implausibly brief. Residential investment fell from 6.5 percent of GDP in 2004 to less than 2.5 percent by 2010. And that is leaving aside housing wealth-driven consumption. Meanwhile, the ARRA stimulus didn’t really come online until the second half of 2009. I don’t believe monetary policy is totally ineffective, but I do think it operates slowly, especially on loosening side. So I find it hard to believe that the autonomous fall in demand in early 2009 was much less than 5 percent of GDP. That implies a demand persistence of no more than 0.25.

Within the 0.15 to 0.25 range, probably the most important variable is your judgement of the effectiveness of monetary policy and the ARRA stimulus. If you think that one or both was very effective, you might think that by mid-2010, they were fully offsetting the fall in demand from the housing bust. This would be consistent with  persistence around 0.25. Conversely, if you’re doubtful about the effectiveness of monetary policy and the ARRA (too little direct spending), you should prefer a value of 0.2 or 0.15. 

In any case, it seems to me that the implied shocks with persistence in the 0.15 – 0.25 range look much more plausible than for values outside that range. I don’t believe that the underlying forces that reduced demand in the Great Recession had ceased to operate by the second half of 2009. I also don’t think that they were autonomously reducing demand by as much as 2 points still in early 2014. 

You will have your own priors, of course. My fundamental point is that your priors on this stuff have wider implications. I have not seen anyone spell out the question of the persistence of demand in the way I have done here. But the idea is implicit in the way we talk about business cycles. Logically, a demand shortfall in any given period can be described as a mix of forces pulling down spending in that period, and the the ongoing effect of weak demand in earlier periods. And whatever opinion you have about the proportions of each, this can be quantified. What I am doing in this post, in other words, is not proposing a new theory, but trying to make explicit a theory that’s already present in these debates, but not normally spelled out.

Why Is Demand Persistent?

The history of real economies should be enough to convince us that demand can be persistent. Deep downturns — not only in the US after 2007, but in much of Europe, in Japan after 1990, and of course the Great Depression — show clearly that if the level of spending in an economy falls sharply for whatever reason, it is likely to remain low years later, even after the precipitating factor is removed. But why should economies behave this way?

I can think of a couple of reasons.

First, there’s the pure coordination story. Businesses pay wages to workers in order to carry out production. Production is carried out for sale. Sales are generated by spending. And spending depends on incomes, most of which are generated from production. This is the familiar reasoning of the multiplier, where it is used to show how an autonomous change in spending can lead to a larger (or smaller) change in output. The way the multiplier is taught, there is one unique level of output for each level of autonomous demand. But if we formalized the same intuition differently, we could imagine a system with multiple equilibria. Each would have a different level of income, expenditure and production, but in each one people would be making the “right” expenditure choices given their income. 

We can make this more concrete in two ways. First, balance sheets. One reason that there is a link from current income to current expenditure is that most economic units are financially constrained to some degree. Even if you knew your lifetime income with great precision, you wouldn’t be able to make your spending decisions on that basis because, in general, you can’t spend the money you will receive in the distant future today.

Now obviously there is some capacity to shift spending around in time, both through credit and through spending down liquid assets. The degree to which this is possible depends on the state of the balance sheet. To the extent a period of depressed demand leaves households and businesses with weaker balance sheets and tighter financial constraints, it will result in lower spending for an extended period. A version of this idea was put forward by Richard Koo as a “balance sheet recession,” in a rather boldly titled book. 

Finally there is expectations. There is not, after all, a true lifetime income out there for you to know. All you can do is extrapolate from the past, and from the experiences of other people like you. Businesses similarly must make decisions about how much investment to carry out based on extrapolation from the past – on what other basis could they do it?

A short period of unusually high or low demand may not move expectations much, but a sustained one almost certainly will. A business that has seen demand fall short of what they were counting on is going to make more conservative forecasts for the future. Again, how could they not? With the balance sheet channel, one could plausibly agree that demand shocks will be persistent but not permanent. But with expectations, once they have been adjusted, the resulting behavior will in general make them self-confirming, so there is no reason spending should ever return to its old path. 

This, to me, is the critical point. Mainstream economists and policy makers worry a great deal about inflation expectations, and whether they are becoming “unanchored.” But expectations of inflation are not the only ones that can slip their moorings. Households and businesses make decisions based on expectations of future income and sales, and if those expectations turn out to be wrong, they will be adjusted accordingly. And, as with inflation, the outcomes of which people form expectations themselves largely depend on expectations.

This was a point emphasized by Keynes: 

It is an essential characteristic of the boom that investments which will in fact yield, say, 2 per cent in conditions of full employment are made in the expectation of a yield of, say, 6 per cent, and are valued accordingly.

When the disillusion comes, this expectation is replaced by a contrary ‘error of pessimism’, with the result that the investments, which would in fact yield 2 per cent in conditions of full employment, are expected to yield less than nothing; and the resulting collapse of new investment then leads to a state of unemployment in which the investments, which would have yielded 2 per cent in conditions of full employment, in fact yield less than nothing. We reach a condition where there is a shortage of houses, but where nevertheless no one can afford to live in the houses that there are.

He continues the thought in terms that are very relevant today:

Thus the remedy for the boom is not a higher rate of interest but a lower rate of interest! For that may enable the so-called boom to last. The right remedy for the trade cycle is not to be found in abolishing booms and thus keeping us permanently in a semi-slump; but in abolishing slumps and thus keeping us permanently in a quasi-boom.

 

Video: The Macro Case for the Green New Deal

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

Good News on the Economy, Bad News on Economic Policy

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Could Trump Have a Point about Rate Hikes?

(Cross-posted from The Next New Deal at The Roosevelt Institute.)

At its December meeting, the Federal Reserve raised its benchmark interest rate a quarter point. The move, while widely expected, represented a clear rebuke to President Trump, who has repeatedly urged the Fed to keep rates low. He took to Twitter after the move to attack Fed head Jerome Powell as a golfer who has no touch (“he can’t putt”)—strong words in the president’s social circle.

Trump’s critics on the left may be tempted to cheer the Fed’s decision as a welcome triumph of the separation of powers. But opposing him on the grounds that the labor market is already great may end up weakening the case for a progressive agenda. We need to consider the possibility that, in this one case, the president is right.

By raising rates, the Fed is signaling that it thinks that the economy is now operating at potential, or full employment. Conventional economic theory says that when the economy is below potential, more spending will bring unemployed and underemployed people to work, and more fully utilize structures and equipment, but once potential is reached, additional spending will just lead to higher prices. So when output is below potential, anything that raises spending—whether it is tax cuts, increased federal spending, a more favorable trade balance, or lower interest rates—is macroeconomically useful. But once the economy is at potential, and there are no more unemployed people or underused buildings and machines, the same policies will lead only to more inflation.

By this standard, the case for the most recent rate increase was plausible, though not a slam dunk. By the official measures produced by the Bureau of Economic Analysis (BEA), 2018 was the first year since 2007 that GDP reached potential, and at 3.7 percent, the headline unemployment rate is quite low by historical standards. So textbook logic suggests that if demand growth does not slow, inflation is likely to rise.

The past decade, however, has given us reason to doubt the textbook models. As I argued in the Roosevelt report What Recovery?, it is far from clear that the BEA’s measure does a good job capturing the productive potential of the economy. Similarly, the headline unemployment rate may no longer be a good measure of the economically relevant category of people available for work; many people move directly between being out of the laborforce and being employed. The behavior of inflation has defied any mechanical linkage with GDP growth, wages, or unemployment. And even if one accepts that output is nearing potential, a higher interest rate may not be necessary to slow it. (This is related to the idea of r*, the “neutral” rate of interest, which neither raises nor lowers demand—something that many people, including Powell himself, have suggested we don’t actually know.) Given these uncertainties, many people—across the political spectrum—have argued that it’s foolish for the central bank to try to make policy based on guesses of where inflation is heading. Instead, they should wait to raise rates until it is clear that inflation is above target.

More broadly, the question of whether the economy is at full employment implies a judgement on whether this is the best we can do, economically. Are the millions of people who have dropped out of the laborforce over the past decade really unable or unwilling to engage in paid work? Is the decline of American manufacturing the inevitable result of a lack of competitiveness? Are the millions of people working at low-wage, dead-end jobs incapable of doing anything more rewarding? The decision to raise rates implicitly assumes that the answers are yes. People who think that the economy could work better for ordinary people should hesitate to agree.

We live in a country filled with energetic, talented, creative people, many of whom are forced to spend their days doing tedious busywork. Personally, I find it offensive to claim that a job at McDonald’s or in a nail salon or Amazon warehouse is the fullest use of anyone’s potential. When John Maynard Keynes said “we will build our New Jerusalem out of the labour which in our former vain folly we were keeping unused and unhappy in enforced idleness,” he didn’t only mean literal idleness, but wasted labor more broadly. In a society in which aggregate expenditure was constantly pushing against supply constraints, millions of people today who spend their working hours in menial, unproductive activities would instead be developing their capacities as engineers, artists, electricians, doctors, and scientists.

Progressives concerned about the distribution of income should also pause before cheering an interest rate hike. The textbook model assumes that wage changes are passed more or less one for one to prices (that’s why the Fed pays so much attention to unemployment). But we know that this is not true. Slow wage growth may simply mean a lower share of income going to workers, rather than lower inflation, and high wages may lead to an increase in labor share rather than to higher inflation. Indeed, as a matter of math, the labor share of income cannot rise unless wages rise faster than the sum of productivity growth and inflation. For most of the past decade—and much of the decade before—wages have risen more slowly than this. As a result, labor compensation has fallen to 58 percent of value added in the corporate sector (where it is most reliably measured), down from 60 percent a decade ago and 66 percent in 2000. The only way that this shift from labor to capital can be reversed is if we see an extended period of “excessive” wage growth. This recent hike suggests that the Fed will not tolerate that.

The alternative is to deliberately foster what is sometimes called a “high-pressure” economy. Allowing the unemployment rate to remain low enough for sustained rapid wage growth won’t just help restore the ground that workers have lost over the past decade. It could also boost laborforce participation, as discouraged workers return to the labor market. And it could boost productivity, as scarce workers and strong demand encourage businesses to undertake labor-saving investment. An increasing number of economists think that these kinds of effects, called hysteresis, mean that weak demand conditions can reduce the economy’s productive potential—and strong demand can increase it.

We are already seeing some signs of this. The fall in the laborforce participation over the past decade was, according to most studies, was much larger than can be explained by aging and other demographic factors. Now, as the labor market gets stronger, people who dropped out of the laborforce are reentering it. Some businesses in low-unemployment areas are now paying for English lessons so they can hire non-English speaking immigrants, who are normally among the last to be employed. After years of stagnation, wages are beginning to rise fast enough to produce a modest rise in the hare of output going to workers—the predictable result of a strong labor market. A recent study by the Federal Reserve Bank of Atlanta confirmed that a high-pressure economy, with unemployment well below normal levels, can boost earnings and strengthen attachment to the laborforce. The effects are long-lasting and strongest for those at the back of the hiring queue, such as Black Americans and those with less-formal education. Labor productivity has yet to pick up, but business investment is now quite strong, so it is likely that productivity may soon start rising as well. None of these gains will be realized if the Fed acts too quickly to rein in a boom.

Critics of the president who argue that the economy is already at full employment risk replaying the 2016 election, where the Democrats were perceived—fairly or not—as defenders of the status quo, while Trump spoke to and for those left behind by the recovery. And they risk throwing away one of the best arguments for a progressive program in 2021 and beyond. The next Democratic president will enter office with an ambitious agenda. Whether the top priority is Medicare for All, a Green New Deal, universal childcare, or free higher education, realizing this agenda will require a substantial increase in government spending. Making the case for this will be much easier if there is broad agreement that the economy still suffers from a demand shortfall that public spending can fill.

 

EDIT: The one thing I did not mention here and should have is that the principle of central bank indpedence is also not something that anyone on the left should be defending. Like the various countermajoritarian features of the US political system, it will be wielded more aggressively against any kind of progressive program. And as Mike Konczal and I have argued, both financial crises and extended periods of weak demand have forced central banks to broaden their mandate, making it much harder to mark off “monetary policy” proper from economic policy in general.

Macroeconomic Lessons from the Past Decade

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

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

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

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Continue reading Macroeconomic Lessons from the Past Decade

“Economic Growth, Income Distribution, and Climate Change”

In response to my earlier post on climate change and aggregate demand, Lance Taylor sends along his recent article “Economic Growth, Income Distribution, and Climate Change,” coauthored with Duncan Foley and Armon Rezai.

The article, which was published in Ecological Economics, lays out a structuralist growth model with various additions to represent the effects of climate change and possible responses to it. The bulk of the article works through the formal properties of the model; the last section shows the results of some simulations based on plausible values of the various parmaters. 4 I hadn’t seen the article before, but its conclusions are broadly parallel to my arguments in the previous two posts. It tells a story in which public spending on decarbonization not only avoids the costs and dangers of climate change itself, but leads to higher private output, income and employment – crowding in rather than crowding out.

Before you click through, a warning: There’s a lot of math there. We’ve got a short run where output and investment are determined via demand and distribution, a long run where the the investment rate from the short run dynamics is combined with exogenous population growth and endogenous productivity growth to yield a growth path, and an additional climate sector that interacts with the economic variables in various ways. How much the properties of a model like this change your views about the substantive question of climate change and economic growth, will depend on how you feel about exercises like this in general. How much should the fact that that one can write down a model where climate change mitigation more than pays for itself through higher output, change our beliefs about whether this is really the case?

For some people (like me) the specifics of the model may be less important that the fact that one of the world’s most important heterodox macroeconomists thinks the conclusion is plausible. At the least, we can say that there is a logically coherent story where climate change mitigation does not crowd out other spending, and that this represents an important segment of heterodox economics and not just an idiosyncratic personal view.

If you’re interested, the central conclusions of the calibrated model are shown below. The dotted red line shows the business-as-usual scenario with no public spending on climate change, while the other two lines show scenarios with more or less aggressive public programs to reduce and/or offset carbon emissions.

Here’s the paper’s summary of the outcomes along the business-as-usual trajectory:

Rapid growth generates high net emissions which translate into rising global mean temperature… As climate damages increase, the profit rate falls. Investment levels are insufficient to maintain aggregate demand and unemployment results. After this boom-bust cycle, output is back to its current level after 200 years but … employment relative to population falls from 40% to 15%. … Those lucky enough to find employment are paid almost three times the current wage rate, but the others have to rely on subsistence income or public transfers. Only in the very long run, as labor productivity falls in response to rampant unemployment, can employment levels recover. 

In the other scenarios, with a peak of 3-6% of world GDP spent on mitigation, we see continued exponential output growth in line with historical trends. The paper doesn’t make a direct comparison between the mitigation cases and a world where there was no climate change problem to begin with. But the structure of the model at least allows for the possibility that output ends up higher in the former case.

The assumptions behind these results are: that the economy is demand constrained, so that public spending on climate mitigation boosts output and employment in the short run; that investment depends on demand conditions as well as distributional conflict, allowing the short-run dynamics to influence the long-run growth path; that productivity growth is endogenous, rising with output and with employment; and that climate change affects the growth rate and not just the level of output, via lower profits and faster depreciation of existing capital.5

This is all very interesting. But again, we might ask how much we learn from this sort of simulation. Certainly it shouldn’t be taken as a prediction! To me there is one clear lesson at least: A simple cost benefit framework is inadequate for thinking about the economic problem of climate change. Spending on decarbonization is not simply a cost. If we want to think seriously about its economic effects, we have to think about demand, investment, distribution and induced technological change. Whether you find this particular formalization convincing, these are the questions to ask.

Guns and Ice Cream

I’ve gotten some pushback on the line from my decarbonization piece that “wartime mobilization did not crowd out civilian production.” More than one person has told me they agree with the broader argument but don’t find that claim believable. Will Boisvert writes in comments:

Huh? The American war economy was an *austerity* economy. There was no civilian auto production or housing construction for the duration. There were severe housing shortages, and riots over housing shortages. Strikes were virtually banned. Millions of soldiers lived in barracks, tents or foxholes, on rations. So yeah, there were drastic trade-offs between guns and butter (which was rationed for civilians).

It’s true that there were no new cars produced during the war, and very little new housing.6 But this doesn’t tell us what happened to civilian output in general. For most of the war, wartime planning involved centralized allocation of a handful of key resources — steel, aluminum, rubber — that were the most important constraints on military production. This obviously ruled out making cars, but most civilian production wasn’t directly affected by wartime controls. 7 If we want to look at what happened to civilian production overall, we have to look at aggregate measures.

The most comprehensive discussions of this I’ve seen are in various pieces by Hugh Rockoff.8 Here’s the BEA data on real (inflation-adjusted) civilian and military production, as he presents it:

Civilian and military production in constant dollars. Source: H. Rockoff, ‘The United States: from ploughshares into swords’ in M. Harrison, ed, The Economics of World War II

As you can see, civilian and military production rose together in 1941, but civilian production fell in 1942, once the US was officially at war. So there does seem to be some crowding out. But looking at the big picture, I think my claim is defensible. From 1939 to its peak in 1944, annual military production increased by 80 percent of prewar GDP. The fall in real civilian production over this period was less than 4 percent of prewar GDP. So essentially none of the increase in military output came at the expense of civilian output; it was all additional to it. And civilian production began rising again before the end of the war; by 1945 it was well above 1939 levels.

Production is not the same as living standards. As it happens, civilian investment fell steeply during the war — in 1943-44, it was only about one third its prewar level. If we look at civilian consumption rather than output, we see a steady rise during the war. By the official numbers, real per-capita civilian consumption was 5 percent higher in 1944 – the peak of war production — than it had been in 1940. Rockoff believes that, although the BLS did try to correct for the distortions created by rationing and price controls, the official numbers still understate the inflation facing civilians. But even his preferred estimate shows a modest increase in per-capita civilian consumption over this period.

We can avoid the problems of aggregation if we look at physical quantities of particular goods. For example, shoes were rationed, but civilians nonetheless bought about 5 percent more shoes annually in 1942-1944 than they had in 1941. Civilian meat consumption increased by about 10 percent, from 142 pounds of meat per person in 1940 to 154 pounds per person in 1944. As it happens, butter seems to be one of the few categories of food where consumption declined during the war. Here’s Rockoff’s discussion:

Consumption of edible fats, particularly butter, was down somewhat during the war. Thus in a strict sense the United States did not have guns and butter. The reasons are not clear, but the long-term decline in butter consumption probably played a role. Ice cream consumption, which had been rising for a long time, continued to rise. Thus, the United States did have guns and ice cream. The decline in edible fat consumption was a major concern, and the meat rationing system was designed to provide each family with an adequate fat ration. The concern about fats aside, [civilian] food production held up well.

As this passage suggests, rationing in itself should not be seen as a sign of increased scarcity. It is, rather, an alternative to the price mechanism for the allocation of scarce goods. In the wartime setting, it was introduced where demand would exceed supply at current prices, and where higher prices were considered undesirable. In this sense, rationing is the flipside of price controls. Rationing can also be used to deliver a more equitable distribution than prices would — especially important where we are talking about a necessity like food or shoes.

The fundamental reason why rationing was necessary in the wartime US was not that civilian production had fallen, but because civilian incomes were rising so rapidly. Civilian consumption might have been 5 percent higher in 1944 than in 1940; but aggregate civilian wages and salaries were 170 percent higher. Prices rose somewhat during the war years; but without price controls and rationing inflation would undoubtedly have been much higher. Rockoff’s comment on meat probably applies to a wide range of civilian goods: “Wartime shortages … were the result of large increases in demand combined with price controls, rather than decreases in supply.”

Another issue, which Rockoff touches on only in passing, is the great compression of incomes during the war. Per Piketty and co., the income share of the top 10 percent dropped from 45 percent in 1940 to 33 percent in 1945. If civilian consumption rose modestly in the aggregate, it must have risen by more for the non-wealthy majority. So I think it’s pretty clear that in the US, civilian living standards generally rose during the war, despite the vast expansion of military production.

You might argue that even if civilian consumption rose, it’s still wrong to say there was no crowding out, since it could have risen even more without the war. Of course one can’t know what would have happened; even speculation depends on what the counterfactual scenario is. But certainly it didn’t look this way at the time. Real per capita income in the US increased by less than 2 percent in total over the decade 1929-1939.  So the growth of civilian consumption during the war was actually faster than in the previous decade. There was a reason for the popular perception that “we’ve never had it so good.”

It is true that there was already some pickup in growth in 1940, before the US entered the war (but rearmament was already under way). But there was no reason to think that faster growth was fated to happen regardless of military production. If you read stuff written at the time, it’s clear that most people believed the 1930s represented, at least to some degree, a new normal; and no one believed that the huge increase in production of the war years would have happened on its own.

Will also writes:

War production itself was profoundly irrational. Expensive capital goods were produced, thousands of tanks and warplanes and warships, whose service lives spanned just a few hours. Factories and production lines were built knowing that in a year or two there would be no market at all for their products.

I agree that military production itself is profoundly irrational. Abolishing the military is a program I fully support. But I don’t think the last sentence follows. Much wartime capital investment could be, and was, rapidly turned to civilian purposes afterwards. One obvious piece of evidence for this is the huge increase in civilian output in 1946; there’s no way that production could increase by one third in a single year except by redirecting plant and equipment built for the military.

And of course much wartime investment was in basic industries for which reconversion wasn’t even necessary. The last chapter of Mark Wilson’s Destructive Creation makes a strong case that postwar privatization of factories built during the war was very valuable for postwar businesses, and that acquiring them was a top priority for business leaders in the reconversion period. 9 By one estimate, in the late 1940s around a quarter of private manufacturing capital consisted of plant and equipment built by the government during the war and subsequently transferred to private business. In 1947, for example, about half the nation’s aluminum came from plants built by the government during the war for aircraft production. All synthetic rubber — about half total rubber production — came from plants built for the military. And so on. While not all wartime investment was useful after the war, it’s clear that a great deal was.

I think people are attracted to the idea of wartime austerity because we’ve all been steeped in the idea of scarcity – that economic problems consist of the allocation of scarce means among alternative ends, in Lionel Robbins’ famous phrase. Aggregate demand is, in that sense, a profoundly subversive idea – it suggests that’s what’s really scarce isn’t our means but our wants. Most people are doing far less than they could be, given the basic constraints of the material world, to meet real human needs. And markets are a weak and unreliable tool for redirecting our energies to something better. World War II is the biggest experiment to date on the limits of boosting output through a combination of increased market demand and central planning. And it suggests that, altho supply constraints are real — wartime controls on rubber and steel were there for a reason – in general we are much, much farther from those constraints than we normally think.

 

 

 

Decarbonization: A Keynesian View

The International Economy has asked me to take part in a couple of their recent roundtables on economic policy. My first contribution, on productivity growth, is here (scroll down). My second one, on green investment, is below. But first, I want to explain a little more what I was trying to do with it.

I am not trying to minimize that challenge of dealing with the climate change. But I do want to reject one common way of thinking about those challenges — as a “cost”, as some quantity of other needs that will have to go unmet. I reject it because output isn’t fixed — a serious effort to deal with climate change will presumably lead to a boom with much higher levels of employment and investment. And more broadly I reject it because it’s profoundly wrong to think of the complex activities of production as being equivalent to a certain quantity of “stuff”.

There’s a Marxist version of this, which I also reject — that the reproduction of capitalism requires an ever-increasing flow of material inputs and outputs, which rules out any kind of environmental sustainability. I think this mistakenly equates the situation facing the individual capitalist — the need to maximize money sales relative to money outlays — with the logic of the system as a whole. There is no necessary link between endless accumulation of money and any particular transformation of the material world. To me the real reason capitalism makes it so hard to address climate change isn’t any objective need to dump carbon into the atmosphere. It’s the obstacles that private property and the pursuit of profit — and their supporting ideologies — create for any kind of conscious reorganization of productive activity.

The question was, who will be the winners and losers from the transition away from carbon? Here’s what I wrote:

The response to climate change is often conceived as a form of austerity—how much consumption must we give up today to avoid the costs of an uninhabitable planet tomorrow? This way of thinking is natural for economists, brought up to think in terms of the allocation of scarce means among competing ends. By some means or other—prices, permits, or plans—part of our fixed stock of resources must, in this view, be used to prevent (or cope with) climate change, reducing the resources available to meet other needs.

The economics of climate change look quite different from a Keynesian perspective, in which demand constraints are pervasive and the fundamental economic problem is not scarcity but coordination. In this view, the real resources for decarbonization will not have to be with- drawn from other uses. They can come from an expansion of society’s productive capabilities, thanks to the demand created by clean-energy investment itself. Addressing climate change need not imply a lower standard of living—if it boosts employment and steps up the pace of technological change, it may well lead to a higher one.

People rightly compare the scale of the transition to clean technologies to the mobilization for World War II. Often forgotten, though, is that in countries spared the direct destruction of the fighting, like the United States, wartime mobilization did not crowd out civilian production. Instead, it led to a remarkable acceleration of employment and productivity growth. Production of a liberty ship required 1,200 man hours in 1941, only 500 by 1944. These rapid productivity gains, spurred by the high-pressure economy of the war, meant there was no overall tradeoff between more guns and more butter.

At the same time, the degree to which all wartime economies—even the United States—were centrally planned, reinforces a lesson that economic historians such as Alexander Gerschenkron and Alice Amsden have drawn from the experience of late industrializers: however effective decentralized markets may be at allocating resources at the margin, there is a limit to the speed and scale on which they can operate. The larger and faster the redirection of production, the more it requires conscious direction—though not necessarily by the state.

In a world where output is fundamentally limited by demand, action to deal with climate change doesn’t require sacrifice. Do we really live in such a world? Think back a few years, when macroeconomic discussions were all about secular stagnation and savings gluts. The headlines may have faded, but the conditions that prompted them have not. There’s good reason to think that the main limit to capital spending still is not scarce savings, but limited outlets for profitable investment, and that the key obstacle to faster growth is not technology or “structural” constraints, but the willingness of people to spend money. Bringing clean energy to scale will call forth new spending, both public and private, in abundance.

Of course, not everyone will benefit from the clean energy boom. The problem of stranded assets is real— any effective response to climate change will mean that much of the world’s coal and oil never comes out of the ground. But it’s not clear how far this problem extends beyond the fossil fuel sector. For manufacturers, even in the most carbon-intensive industries, only a small part of their value as enterprises comes from the capital equipment they own. More important is their role in coordinating production—a role that conventional economic models, myopically focused on coordination through markets, have largely ignored. organizing complex production processes, and maintaining trust and cooperation among the various participants in them, are difficult problems, solved not by markets but by the firm as an ongoing social organism. This coordination function will retain its value even as production itself is transformed.

UPDATE: Followup post on the World War II experience here.

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.