macroeconomics – Page 4

Rogoff on the Zero Lower Bound

I was at the ASSAs in Chicago this past weekend. [1] One of the most interesting panels I went to was this one, on Advances in Open Economy Macroeconomics. Among other big names, Ken Rogoff was there, as the discussant for a rather strange paper by Pierre-Olivier Gourinchas and Helene Rey.

The Gourinchas and Rey paper, like much of mainstream macro these days, made a big deal of how different everything is at the zero lower bound. Rogoff wasn’t having it. Here’s a rough transcript of what he said:

The obsession with the zero lower bound is encouraging all kinds of wacko ideas. People are saying that at the ZLB, productivity increases are bad (Eggertsson/Krugman/Summers), protectionism is good (Eichngreen), price flexibility is bad, and so on.

But there is an emerging literature that says economists are taking the zero lower bound too literally. In fact, getting negative rates is not that hard. So before you take seriously these, let’s say, very creative ideas, it would be simpler to think about getting rid of the zero bound.

There are lots of ways to do it. I talk about some in my book, but people already understood this back in the 1930s. There was Robert Eisler’s proposal to have banks accept cash deposits at a discount, for instance, which would have effectively created negative rates. If Keynes had read Eisler, he might have gone in a different direction. [2] It’s a very old idea — Kublai Khan did something similar. There will be pushback from the financial sector, of course, who think negative rates will be costly for them, but fundamentally it is not hard to do.

These rather striking comments crystallized something in my mind. What is the big deal about the ZLB? For mainstream macroeconomists, including Gourinchas and Rey in this paper, the reason the ZLB matters is that it prevents the central bank form setting an interest rate low enough to keep output at potential. [3] It’s precisely this that makes inapplicable the conventional analysis of a nonmonetary problem of allocating scarce resources between alternative ends, and requires thinking about other entry points. If the central bank can’t solve the problem of aggregate demand then you have to take it seriously, with all the wacko and/or creative stuff that follows.

In the dominant paradigm, this is a specific technical problem of getting interest rates below zero. Solve that, and we are back in the comfortable Walrasian world. But for those of us on the heterodox side, it is never the case that the central bank can reliably keep output at potential — maybe because market interest rates don’t respond to the policy rate, or because output doesn’t respond to interest rates, or because the central bank is pursuing other objectives, or because there is no well-defined level of “potential” to begin with. (Or, in reality, all four.) So what people like Gourinchas and Rey, or Paul Krugman, present as a special, temporary state of the economy, we see as the general case.

One way of looking at this is that the ZLB is a device to allow economists like Krugman and Gourinchas and Rey — who whatever their scholarly training, are aware of the concrete reality around them — to make Keynesian arguments without forfeiting their academic respectability. You can understand why someone like Rogoff sees that as cheating. We’ve spent decades teaching that the fundamental constraint on the economy is the real endowment of resources and technology; that saving boosts growth; that trade is always win-win; that money and finance matter only in the short run (and the short run is tolerably short). The practical problem of negative policy rates doesn’t let you forget all of that.

Which, if you turn it around, perhaps reflects well on the ZLB crowd. Maybe they want to forget all that? Maybe, you could say, they take the zero lower bound seriously because they don’t take it literally. That is, they treat it as a hard constraint precisely because they are aware that it is only a stand-in for a deeper reality.

[1] The big annual economics conference. It stands for Allied Social Sciences Association — the disciplinary imperialism is right there in the name.

[2] This was an odd thing for Rogoff to say, since of course while Keynes didn’t discuss Eisler as far as I know, he talks at length about the similar proposals for depreciating cash of Silvio Gesell and Major Douglas. Notoriously he says these “brave cranks and heretics” have more to offer than Marx.

[3] Gourinchas and Rey are reality-based enough to say “the policy rate,” not “the interest rate.”

EDIT: Added the seriously-but-not-literally phrasing as suggested by Steve Roth on Twitter.

Demand and Productivity

I’m picking up, after some months, the project I was working on over the summer on potential output. Obviously the political context is different now. But the questions of what potential output actually means, how tightly it binds, and how close the economy is to it at any given moment, are not going away. Previous entries: one, two, three, four, and five.

You’ve probably heard the story about Ed Rensi, the former McDonald’s CEO who claimed the company’s move to replace cashier’s with self-serve kiosks was a response to minimum wage increases.

“I told you so,” he writes. “In 2013, when the Fight for $15 was still in its growth stage, I and others warned that union demands for a much higher minimum wage would force businesses with small profit margins to replace full-service employees with costly investments in self-service alternatives.”

Is this for real? Maybe not: The shift toward kiosks has been happening for a while, so it’s not just a response to the recent minimum wage hikes; and it may not end up reducing labor costs anyway.

But let’s say the move is as as Rensi claims. Then we should call it what it is: an increase in labor productivity. With fewer workers McDonald’s will produce just as many hamburgers; in other words, production per worker will be higher. [1]

As I’ve suggested, this sort of thing is a real problem for a certain strand of minimum wage advocacy. Advocates like to point to productivity gains in response to higher wages as an argument in their favor. (The gains are usually imagined in terms of loyalty, motivation, lower turnover, etc. rather than machines, but functionally it’s the same.) But productivity gains can only reduce the job losses from a minimum wage increase if those losses are large; they are not consistent with a story in which employment stays the same. [2]

But at the macro level, this dynamic has different implications. If the McDonald’s case is typical — if higher labor costs regularly lead to higher productivity — then we need to rethink our idea of supply constraints. There is more space for expansionary policy than we usually think.

Let’s start at the beginning. Suppose there is some policy change, or some random event, that boosts desired spending in the economy. It could be more government spending, it could be lower interest rates, it could be a rise in exports. What happens then?

In the conventional story, higher spending normally leads to greater production of goods and services, which in turn requires higher employment. This leaves fewer people unemployed. Lower unemployment increases the bargaining power of workers, forcing employers to bid up nominal wages. [3] These higher wages are passed on to prices, leading to higher inflation. When inflation reaches whatever level is considered price stability, then we say the economy is at full employment, or at potential output. (In this story the two are equivalent.) If spending continues to rise past this point, the responsible authorities (normally the central bank) will intervene to bring it back down.

This is the story you’ll find in any good undergraduate macroeconomics textbook. It’s a reasonable story, as far as these things go. In the strong form it’s usually given in, it implies a hard limit to how much demand can increase before inflation starts rising unacceptably. Once the pool of unemployed workers falls to the “full employment” level, any further increase in employment will lead to rapid increases in money wages, which will be passed on one for one to inflation.

One place this chain can break is that new workers are not necessarily drawn from the ranks of the currently unemployed — that is, if the size of the laborforce is endogenous. Insofar as people counted as out of the laborforce are in fact available for employment (or net immigration responds to demand), an increase in output doesn’t have to reduce the ranks of the officially unemployed. In other words, the official unemployment rate may underestimate the space available for raising output via increased employment. This motivates the question of how much the the fall in laborforce participation since 2007 is due to demographics, and how much is due to weak demand.

The conventional story can also break down at two other places if productivity growth is endogenous. First, output can increase without a proportionate increase in employment. And second, wages can rise without a proportionate rise in prices.

It’s useful to think about this in terms of a couple of accounting identities, which in my opinion should be part of every macroeconomics textbook. [4] The first is obvious (but worth spelling out), the second a little less so:

(1) growth in demand = percent change in labor productivity + percent change in employment + inflation

(2) percent change in nominal wages = percent change in labor productivity + percent change in labor share + inflation

The standard story is that productivity change on its own due to technology, and the labor shared is fixed and can be ignored in this context. If productivity and labor share can be taken as given, then an increase in demand (money spent on final goods and services) must lead to higher inflation if either employment fails to rise, or if it rises only with higher wages. In this story, if nominal wages rise thanks to a lower unemployment rats, that will pass on one for one to inflation. Pick up an advanced undergraduate textbook like Blanchard or Krugman or Carlin and Soskice, and you will find a Phillips curve of exactly this form, with exactly this story behind it. [5] Policy discussions at central banks conducted in same terms.

This is what underlies idea of hard supply constraints. Output growth is dictated by the fixed, exogenous growth of the laborforce and of productivity. If changes in demand push the economy off that fixed trajectory, all you’ll get is higher or lower inflation. Concretely: To keep inflation at 2 percent, unemployment must be such as to generate nominal wage growth 2 points above the technologically-determined growth of productivity.

But an alternative story is that variation in demand can lead to adjustment in one of the other terms. One possibility is that the laborforce adjusts, as participation rates vary in response to demand conditions. This is what is most often meant by hysteresis: persistent deviations in unemployment from the “natural” level lead to people entering or exiting the laborforce. That implies that even when headline unemployment rates are fairly low, further increases in employment may be possible without a rise in wages. Another possibility is that while higher employment will lead to (or require) higher wages, the wage increase is not passed on to prices but comes at the expense of profits instead. This is Anwar Shaikh’s classical Phillips curve; I’ve written about it here before.

A third possibility is that higher wages are accompanied by higher productivity. Again, this appears as a problem when we are talking about wage increases from legislation, union contracts, or similar developments. But it’s not a problem if the wage increases are thanks to low unemployment. In this case, the joint movement of wages and productivity just means that output can rise higher — that supply constraints are softer. That’s what I want to focus on now.

There are a number of reasons why productivity might rise with wages. Some of them simply amount to mismeasurement of employment — it appears that output per worker is rising but really the effective number of workers is. Others are more fundamental. If productivity responds strongly and persistently to demand, it blurs the distinction between aggregate supply and aggregate demand, to the point that it’s not clear what “potential output” even means.

Suppose we do find a consistent pattern where, if demand is strong, unemployment is low, and wages are rising rapidly, then productivity growth is high. What could be happening?

1. Increased hours. If we measure productivity as output per worker, as we usually do, then an increase in average hours worked will show up as an increase in productivity. There is a cyclical component to this — in recessions, employers reduce hours as well as laying off workers. According to the BLS, seasonally adjusted weekly hours fell from 34.4 prior to the recession to a low of 33.7 in summer 2009. While a 2 percent fall in hours might seem small, it’s a big change in less than two years, especially when you consider that real output per worker normally rises by less than 2 percent a year.

2. Workers moving into real jobs from pseudo-employment or disguised unemployment. In any economy there are activities that are formally classified as jobs but are not employment in any substantive sense — you can take these “jobs” without anyone making a decision to hire you, and they don’t come with a wage or any similar claim on any established production process. Joan Robinson’s examples were someone who gathers firewood in a poor country, or sells pencils on streetcorners in a richer one. You could add work in family businesses and various kinds of self-employment and commission-based work to this category. In countries with traditional rural sectors — not the US — work on a family farm is the big item here. These activities absorb people who are unable to find formal jobs; the marginal product of additional workers here is normally very low. So if higher demand draws people from this kind of disguised unemployment back into regular jobs, measured productivity will rise.

3. Workers may be more fully utilized at their existing jobs. Because hiring and firing is costly, business don’t immediately adjust staffing in response to changes in sales. when demand falls, businesses will initially keep some redundant workers because paying them is cheaper than laying them off and replacing them later; and when demand rises, businesses will first try to get more work out of existing employees rather than paying the costs of hiring more. Some of this takes the form of the hours adjustment above, but some of it simply takes the form of hiring “too little” or “too much” labor for the current level of production. These changes in the utilization of existing labor will show up as changes in labor productivity.

4. Higher wages may lead to more capital-intensive production. This is the McDonald’s story: When labor gets more expensive (or scarcer), businesses use more capital instead. This is presumably what people mean when they say “Econ 101” shows that rising wages lead to less employment (assuming they mean anything at all). This may be seen as a negative when it’s a question of raising wages through legislation or unions, but it shouldn’t be when it’s a question of rising wages due to labor scarcity. Insofar as businesses can substitute machines for labor, rising wages will not be passed on to prices, so there is more space to push unemployment down.

5. Productivity-boosting innovations may be more likely when demand is strong and wages rise. This is a variant of the previous story. Now instead of high wage leading business to adopt more capital-intensive techniques from those already available, they redirect innovation toward developing new labor-saving techniques. Conceptually this is not a big difference, but it implies a different signal in the data. In the previous case we would expect the productivity improvements to be associated with higher investment and to be concentrated at the firms actually experiencing higher wages costs; in this case they might not be.

6. The composition of employment may shift toward higher-productivity sectors. This might happen for either of two reasons. First, higher wages will disproportionately raise costs for more labor-intensive sectors; these higher costs may be absorbed by profits or by prices, but either way they will presumably depress growth in those sectors to the benefit of less labor-intensive, more productive ones. Second, it may so happen that the more income-elastic sectors are also higher-productivity ones. In the short run this is presumably true since durables and investment goods are both capital-intensive and income-elastic. Over the longer run, the opposite is more likely — the composition of demand slowly but steadily shifts toward lower-productivity sectors.

7. The composition of employment may shift toward higher-productivity firms. This sounds similar but it’s a different story. Technical change isn’t an ineffable output-raising essence diffusing across society, it’s embodied in specific new production processes and new businesses — Schumpeter’s new plant, new firms, new men. This means that productivity increases often require new or growing firms to attract workers away from established ones. Given the “frictions” in the labor market, this will require offering a wage significantly above the going rate. And on the other side the fact that the least productive firms can’t afford to pay higher wages will cause them to decline or exit, which also raises average productivity. When wages are flat, on the other hand, low-productivity firms can continue operating. In this sense, higher wages are an integral part of productivity growth. [6]

8. There may be increasing returns in production. It may literally be the case that output per worker rises — at the firm, industry or economy-wide level — when the number of workers rises. Or this may be a more abstract version of some of the stories above. It’s worth noting that increasing returns is an area where the intuitions of people with economics training diverge sharply from people who look at the economy through other lenses. To almost anyone except an economist, it’s obvious that costs normally fall as more of something is produced. [7]

All of these stories imply that higher demand should lead to higher measured labor productivity. But to figure out how strong this relationship is in reality, we’ll look at different data depending on which of these stories we think it works through.

Another important difference between the stories is they imply different domains over which the relationship should operate. The first three suggest a more or less immediate response of productivity to changes in demand, but also one that cannot continue indefinitely. There’s limits to how much hours per worker can rise and how much additional effort can be extracted from the existing workforce, and a limited pool of disguised unemployment to draw from. (The last is not true in developing countries, where the “latent reserve army” in subsistence agriculture may be effectively unlimited.) The other mechanisms are presumably slower, requiring a sustained “high-pressure economy.” With these stories, increased demand may push the economy up against supply constraints, with rising inflation, bottlenecks, and so on; but if it keeps pushing against them, eventually they’ll give. In this case, potential output is a medium-term constraint — over longer periods it can adjust to actual output, rather than the reverse. So in the opposite of conventional story, a temporary increase in inflation can lead to a permanent increase in output. People like Laurence Ball say exactly this about hysteresis, but they are usually thinking of the longer-run adjustment coming on the laborforce side.

If we follow this a step further, we could even say that in the long run, the big problem isn’t that excessively high wages do lead to the substitution of capital for labor but that excessively low wages don’t. People like Arthur Lewis argue that it’s the low wages of poor countries that have led to low productivity there, and not vice versa; there’s a well-known argument that the reason the industrial revolution happened first in Britain rather than in China or India (or Italy or France) is not that that the necessary technical innovations were present only in Britain. They were present many places; it was the uniquely high cost of British labor that made them profitable to adopt for production.

I think that productivity does respond to demand. I think this is a good reason to doubt whether the US economy close to “potential output” today, and to doubt what, if anything, this concept actually means. But I also think we need to be clearer about how they are linked concretely. If we want to tell a story about productivity responding to demand, it makes a difference which of the stories above we have in mind. Heterodox people, it seems to me, are too quick to just invoke Verdoorn’s law (productivity rises with output), and justify it with some vague comments about how labor is used more efficiently when it is scarce. [8] Does this apparent law work via substitution of machines for labor, or through fuller utilization of existing employees’ times, or through reallocation of labor to more productive firms and/or industries, or through a labor-saving-bias in technical change, or pure increasing returns, or what? If you’re just making a formal model it may not matter. But if we want to connect the model to concrete historical developments, it certainly does.

Personally, I am most interested in the reallocation stories. They shift our idea of the fundamental constraint on capitalist economies from biophysical resources, to coordination. The great difficulty for any program of raise or transform production — industrialization, wartime mobilization, decarbonization — isn’t the limited supply of “real” resources, but the speed at which people’s productive activity can be redirected in a coordinated way. This connects with the historical fact that the more rapid and the larger scale is economic development, the more it requires some form of central planning. And it implies that at the most basic level, what the capitalist provides is not money or means of production, but cooperation.

To tell this story, it would be nice if big shifts in productivity growth took the form of changes in the composition of employment, rather than higher output per worker in given jobs. That may or may not be there in the data. For the more immediate question of how much space there is in the US for further expansion, it doesn’t matter as much which of these stories is at work, as long as we can show that at least some of them are. [9]

In the next post or two — which I hope to write in the next week, but we’ll see — I will ask what we can say about the link between demand and productivity based on historical US data. In particular, it’s fairly straightforward to decompose changes in output per worker into three components: within-industry output per hour, within-industry hours per worker, and shifts in the employment between industries. Splitting up productivity growth this way cannot, of course, directly establish a causal link with demand. but it can help clarify which stories are plausible and which are not.

[1] Throughout this discussion, I use “productivity” to mean labor productivity — output per worker or per hour. There is also “total factor productivity,” which purports to be a measure of output for a given input of labor and capital. This concept, which IMF chief economist Paul Romer memorably called “phlogiston,” is measured as the residual from a production function — the output growth the function does not explain. Since construction of the production function requires several unobseravable parameters, total factor productivity cannot be derived even in principle from economic data. It’s a fun toy for economic theory but useless for describing the behavior of actual economies.

Nonetheless it is widely used — for instance by the CBO as discussed here. As Nathan Tankus pointed out to me the other day, under the ARRA Medicare payments to hospitals are reduced each year based on an estimate of TFP growth for the economy as a whole. It’s a great example of the crackpot wonkery of the law’s authors.

[2] Unless productivity improvements all take the form of higher quality, rather than higher output per worker.

[3] This unemployment-money wages relationship was the original Phillips curve, but it’s better now to refer to it as a wage curve.

[4] It’s a topic for another time, but I think it would be very natural to replace the “aggregate supply” framework of the textbooks with these two identities.

[5] Other textbooks, like Mankiw, base the wage-unemployment relationship on a labor-supply curve rather than a bargaining relationship. Graduate textbooks, of course, replace the institutional detail of workers and employers with a single representative agent, in order to make more space for playing with math.

[6] Andrew Glyn and his coauthors have a good discussion of this in the context of the postwar boom in Capitalism Since 1945 (p. 122-123).

[7] For example, here’s Laurie Winkless in Science and the City, which happens to be sitting nearby:

Bessemer’s system rapidly began to change the world of steel manufacturing, and by 1875, costs had dropped to $32 (£23) per tonne. as always, in the supply-and-demand equation, the availability of cheap, high-quality steel made it immensely popular, leading to another huge drop in the price per tonne.

Winkless has made the mistake of studying the actual history of the steel history. If she were an economist, she would know that in the world of supply and demand, immense popularity makes prices rise, not fall!

[8] In Shaikh’s Capitalism, for example, there are a number of models that rely on the claim that productivity rises with output. It’s a big book and I may well have missed a part where he explains more fully why this is true. But as far as I can tell, all he says is that higher unit labor costs “provide a strong incentive for firms to raise productivity.”

[9] The politics of this question under Trump are for another time. But certainly Jeff Spross is right that we don’t want to oppose Trump’s (dubious) plans for a big stimulus by embracing the politics of austerity. We should not respond to Trump by reflexively insisting that the US is already at full employment, and by mocking “vulgar Keynesians” who think there might still be problems for macro policy to solve.

EDIT: Fixed the footnote numbering, which was garbled before.

Lost in Fiscal Space

Arjun and Jayadev and I have a working paper up at the Washington Center for Equitable Growth on the conflict between conventional macroeconomic policy and Lerner-style functional finance. Here’s the accompanying blogpost, cross-posted from the WCEG blog.

One pole of current debates about U.S. fiscal policy is occupied by the “functional finance” position—the view usually traced back to the late economist Abba Lerner—that a government’s budget balance can be set at whatever level is needed to stabilize aggregate demand, without worrying about the level of government debt. At the other pole is the conventional view that a government’s budget balance must be set to keep debt on a sustainable trajectory while leaving the management of aggregate demand to the central bank. Both sides tend to assume that these different policy views come from fundamentally different ideas about how the economy works.

A new working paper, “Lost in Fiscal Space,” coauthored by myself and Arjun Jayadev, suggests that, on the contrary, the functional finance and the conventional approaches can be understood in terms of the same analytic framework. The claim that fiscal policy can be used to stabilize the economy without ever worrying about debt sustainability sounds radical. But we argue that it follows directly from the standard macroeconomic models that are taught to undergraduates and used by policymakers.

Here’s the idea. There are two instruments: first, the interest rate set by the central bank; and second, the fiscal balance—the budget surplus or deficit. And there are two targets: the level of aggregate demand consistent with acceptable levels of inflation and unemployment; and a stable debt-to-GDP ratio. Each instrument affects both targets—output depends on both the interest rate set by monetary authorities and on the fiscal balance (as well as a host of other factors) while the change in the debt depends on both new borrowing and the interest paid on existing debt. Conventional policy and functional finance represent two different choices about which instrument to assign to which target. The former says the interest rate instrument should focus on demand and the fiscal-balance instrument should focus on the debt-ratio target, the latter has them the other way around.

Does it matter? Not necessarily. There is always one unique combination of interest rate and budget balance that delivers both stable debt and price stability. If policy is carried out perfectly then that’s where you will end up, regardless of which instrument is assigned to which target. In this sense, the functional finance position is less radical than either its supporters or its opponents believe.

In reality, of course, policies are not followed perfectly. One common source of problems is when decisions about each instrument are made looking only at the effects on its assigned target, ignoring the effects on the other one. A government, for example, may adopt fiscal austerity to bring down the debt ratio, ignoring the effects this will have on aggregate demand. Or a central bank may raise the interest rate to curb inflation, ignoring the effects this will have on the sustainability of the public debt. (The rise in the U.S. debt-to-GDP ratio in the 1980s owes more to Federal Reserve chairman Paul Volcker’s interest rate hikes than to President Reagan’s budget deficits.) One natural approach, then, is to assign each target to the instrument that affects it more powerfully, so that these cross-effects are minimized.

So far this is just common sense; but when you apply it more systematically, as we do in our working paper, it has some surprising implications. In particular, it means that the metaphor of “fiscal space” is backward. When government debt is large, it makes more sense, not less, to use active fiscal policy to stabilize demand—and leave the management of the public debt ratio to the central bank. The reason is simple: The larger the debt-to-GDP ratio, the more that changes in the ratio depend on the difference in between the interest rate and the growth rate of GDP, and the less those changes depend on current spending and revenue (a point that has been forcefully made by Council of Economic Adviser s Chair Jason Furman). This is what we see historically: When the public debt is very large, as in the United States during and immediately after the Second World War, the central bank focused on stabilizing the public debt rather than on stabilizing demand, which means responsibility for aggregate demand fell to the budget authorities.

We hope this paper will help clarify what’s at stake in current debates about U.S. fiscal policy. The question is not whether it’s economically feasible to use fiscal policy as our primary instrument to manage aggregate demand. Any central bank that is able to achieve its price stability and full employment mandates is equally able to keep the debt-to-GDP ratio constant while the budget authorities manage demand. The latter task may even be easier, especially when debt is already high. The real question is who we, as a democratic society, trust to make decisions about the direction of the economy as a whole.

UPDATE: Nick Rowe has an interesting response here. (And an older one here, with a great comments thread following it.)

Links for October 14

Now we are making progress. This piece by CEA chair Jason Furman on “the new view” of fiscal policy seems like a big step forward for mainstream policy debate. He goes further than anyone comparably prominent in rejecting the conventional macro-policy wisdom of the past 30 years. From where I’m sitting, the piece advances beyond the left edge of the current mainstream discussion in at least three ways.

First, it abandons the idea of zero interest rates as a special state of exception and accepts the idea of fiscal policy as a routine tool of macroeconomic stabilization. Reading stuff like this, or like SF Fed President John Williams saying that fiscal policy should be “a first responder to recessions,” one suspects that the post-1980s consensus that stabilization should be left to the central banks may be gone for good. Second, it directly takes on the idea that elected governments are inherently biased toward stimulus and have to be institutionally restrained from overexpansionary policy. This idea — back up with some arguments about the“time-inconsistency” of policy that don’t really make sense — has remained a commonplace no matter how much real-world policy seems to lean the other way. It’s striking, for instance, to see someone like Simon Wren-Lewis rail against “the austerity con” in his public writing, and yet in his academic work take it as an unquestioned premise that elected governments suffer from “deficit bias.” So it’s good to see Furman challenge this assumption head-on.

The third step forward is the recognition that the long-run evolution of the debt ratio depends on GDP growth and interest rates as well as on the fiscal balance. Some on the left will criticize his assumption that the debt ratio is something policy should be worried about at all — here the new view has not yet broken decisively with the old view; I might have some criticisms of him on this point myself. But it’s very important to point out, as he does, that “changes in the debt ratio depend on two factors: the difference between the interest rate and the growth rate… and the primary balance… The larger the debt is, the more changes in r – g dwarf the primary balance in the determination of debt dynamics.” (Emphasis added.) The implication here is that the “fiscal space” metaphor is backward — if the debt ratio is a target for policy, then a higher current ratio means you should focus more on growth, and that responsibility for the “sustainability” of the debt rests more with the monetary authority than the fiscal authority. Admittedly Furman doesn’t follow this logic as far as Arjun and I do in our paper, but it’s significant progress to foreground the fact the debt ratio has both a numerator and a denominator.

If you’re doubting whether there’s anything really new here, just compare this piece with what his CEA chair predecessor Christina Romer was saying a decade ago — you couldn’t ask for a clearer statement of what Furman now rejects as “the old view.” It’s also, incidentally, a sign of how far policy discussions — both new view and old view — are from academic macro. DSGE models and their associated analytic apparatus don’t have even a walk-on part here. I think left critics of economics are too quick to assume that there is a tight link — a link at all, really — between orthodox theory and orthodox policy.

Why do stock exchanges exist? I really enjoyed this John Cochrane post on volume and information in financial markets. The puzzle, as he says, is why there is so much trading — indeed, why there is any trading at all. Life cycle and risk preference motivations could support, at best, a minute fraction of the trading we see; but information trading — the overwhelming bulk of actual trading — has winners and losers. As Cochrane puts it:

all trading — any deviation of portfolios from the value-weighted market index — is zero sum. Informed traders do not make money from us passive investors, they make money from other traders. It is not a puzzle that informed traders trade and make money. The deep puzzle is why the uninformed trade, when they could do better by indexing. …

Stock exchanges exist to support information trading. The theory of finance predicts that stock exchanges, the central institution it studies, the central source of our data, should not exist. The tiny amounts of trading you can generate for life cycle or other reasons could all easily be handled at a bank. All of the smart students I sent to Wall Street for 20 years went to participate in something that my theory said should not exist.

At first glance this might seem like one of those “puzzles” beloved of economists, where you describe some real-world phenomena in terms of a toy model of someone maximizing something, and then treat the fact that it doesn’t work very well as a surprising fact about the world rather than an unsurprising fact about your description. But in this case, the puzzle seems real; the relevant assumptions apply in financial markets in a way they don’t elsewhere.

I like that Cochrane makes no claim to have a solution to the puzzle — the choice to accept ignorance rather than grab onto the first plausible answer is, arguably, the starting point for scientific thought and certainly something economists could use more of. (One doesn’t have to accept the suggestion that if we have no idea what social needs, if any, are met by financial markets, or if there is too much trading or too little, that that’s an argument against regulation.) And I like the attention to what actual traders do (and say they do), which is quite different from what’s in the models.

Yes, we know it’s not a “real” Nobel. So the Nobel went to Hart and Holmstrom. Useful introductions to their work are here and here. Their work is on contract theory: Why do people make complex ongoing agreements with each other, instead of just buying the things they want? This might seem like one of those pseudo-puzzles — as Sanjay Reddy notes on Twitter, the question only makes sense if you take economists’ ideal world as your starting point. There’s a whole genre of this stuff: Take some phenomenon we are familiar with from everyday life, or that has been described by other social scientists, and show that it can also exist in a world of exchange between rational monads. Even at its best, this can come across like a guy who learns to, I don’t know, play Stairway to Heaven with a set of spoons. Yes, getting the notes out takes real skill, and it doesn’t sound bad, but it’s not clear why you would play it that way if you weren’t for some reason already committed to the gimmick. Or in this case, it’s not clear what we learn from translating a description of actual employment contracts into the language of intertemporal optimization; the process requires as an input all the relevant facts about the phenomenon it claims to explain. What’s the point, unless you are for some already committed to ignoring any facts about the world not expressed in the formalism of economics? This work — I admit I don’t know it well — also makes me uncomfortable with the way it seems to veer opportunistically between descriptive and prescriptive. Is this about how actual contracts really are optimal given information constraints and so on, or is it about how optimal contracts should be written? Anyway, here’s a more positive assessment from Mark Thoma.

Still far from full employment. Heres’ a helpful report from the Center for Economics and Policy Research on the state of the labor market. They look at a bunch of alternatives to the conventional unemployment rate and find that all of them show a weaker labor market than in 2006-2007. Hopefully the Clinton administration and/or some Democrats in the Senate will put some sharp questions to FOMC appointees over the next few years about whether they think the Fed as fulfilled its employmnet mandate, and on what basis. They’ll find some useful ammunition here.

Saving, investment and the natural rate. Here’s a new paper from Lance Taylor taking another swipe at the pinata of the “natural rate”. Taylor points out that if the “natural” interest rate simply means the interest rate at which aggregate demand equals potential output (even setting aside questions about how we measure potential), the concept doesn’t make much sense. If we look at the various flows of spending on goods and services by sector and purpose, we can certainly identify flows that are more or less responsive to interest rates; but there is no reason to think that interest rate changes are the main driver of changes in spending, or that “the” interest rate that balances spending and potential at a given moment is particularly stable or represents any kind of fundamental parameters of the economy. Even less can we think of the “natural” rate as balancing saving and investment, because, among other reasons, “saving” is dwarfed by the financial flows between and within sectors. Taylor also takes Keynes to task (rightly, in my view) for setting us on the wrong track with assumption that households save and “entrepreneurs” invest, when in fact most of the saving in the national accounts takes place within the corporate sector.

On other blogs, other wonders:

At Vox, another reminder that the rise in wealth relative to income that Piketty documents is mainly about the rising value of existing assets, not the savings-and-accumulation process he talks about in his formal models.

Also at Vox: How much did Germany benefit from debt forgiveness after World War II? (A lot.) EDIT: Also here.

Is there really a “global pivot” toward more expansionary fiscal policy? The IMF and Morgan Stanley both say no.

Another one for the short-termism file: Here’s an empirical paper suggesting that when banks become publicly traded, their management starts responding to short-run movements in their stock, taking on more risk as a result.

Matias Vernengo has a new paper on Raul Prebisch’s thought on business cycles and growth. Prebisch would be near the top of my list of twentieth century economists who deserve more attention than they get.

I was just at Verso for the release party for Peter Frase’s new book Four Futures, based on his widely-read Jacobin piece. I don’t really agree with Peter’s views on this — I don’t see the full replacement of human labor by machines as the logical endpoint of either the historical development of capitalism or a socialist political project — but he makes a strong case. If the robot future is something you’re thinking about, you should definitely buy the book.

EDIT: Two I meant to include, and forgot:

David Glasner has a follow-up post on the inconsistency of rational expectations with the “shocks” and comparative statics they usually share models with. It’s probably not worth beating this particular dead horse too much more, but one more inconsistency. As I can testify first-hand, at most macroeconomic journals, “lacks microfoundations” is sufficient reason to reject a paper. But this requirement is suspended as soon as you call something a “shock,” even though technology, the markup, etc. are forms of behavior just as much as economic quantities or prices are. (This is also one of Paul Romer’s points.)

And speaking of people named Romer, David and and Christina Romer have a new working paper on US monetary policy in the 1950s. It’s a helpful paper — it’s always worthwhile to reframe abstract, universal questions as concrete historical ones — but also very orthodox in its conclusions. The Fed did a good job in the 1950s, in their view, because it focused single-mindedly on price stability, and was willing to raise rates in response to low unemployment even before inflation started rising. This is a good example of the disconnect between the academic mainstream and the policy mainstream that I mentioned above. It’s perfectly possible to defend orthodoxy macroeconomic policy without any commitment to, or use of, orthodox macroeconomic theory.

EDIT: Edited to remove embarrassing confusion of Romers.

Links for October 6

More methodenstreit. I finally read the Romer piece on the trouble with macro. Some good stuff in there. I’m glad to see someone of his stature making the point that the Solow residual is simply the part of output growth that is not explained by a production function. It has no business being dressed up as “total factor productivity” and treated as a real thing in the world. Probably the most interesting part of the piece was the discussion of identification, though I’m not sure how much it supports his larger argument about macro. The impossibility of extracting causal relationships from statistical data would seem to strengthen the argument for sticking with strong theoretical priors. And I found it a bit odd that his modus ponens for reality-based macro was accepting that the Fed brought down output and (eventually) inflation in the early 1980s by reducing the money supply — the mechanisms and efficacy of conventional monetary policy are not exactly settled questions. (Funnily enough, Krugman’s companion piece makes just the opposite accusation of orthodoxy — that they assumed an increase in the money supply would raise inflation.) Unlike Brian Romanchuk, I think Romer has some real insights into the methodology of economics. There’s also of course some broadsides against the policy views of various rightwing economists. I’m sympathetic to both parts but not sure they don’t add up to less than their sum.

David Glasner’s interesting comment on Romer makes in passing a point that’s bugged me for years — that you can’t talk about transitions from one intertemporal equilibrium to another, there’s only the one. Or equivalently, you can’t have a model with rational expectations and then talk about what happens if there’s a “shock.” To say there is a shock in one period, is just to say that expectations in the previous period were wrong. Glasner:

the Lucas Critique applies even to micro-founded models, those models being strictly valid only in equilibrium settings and being unable to predict the adjustment of economies in the transition between equilibrium states. All models are subject to the Lucas Critique.

Here’s another take on the state of macro, from the estimable Marc Lavoie. I have to admit, I don’t care for way it’s framed around “the crisis”. It’s not like DSGE models were any more useful before 2008.

Steve Keen has his own view of where macro should go. I almost gave up on reading this piece, given Forbes’ decision to ban on adblockers (Ghostery reports 48 different trackers in their “ad-light” site) and to split the article up over six pages. But I persevered and … I’m afraid I don’t see any value in what Keen proposes. Perhaps I’ll leave it at that. Roger Farmer doesn’t see the value either.

In my opinion, the way forward, certainly for people like me — or, dear reader, like you — who have zero influence on the direction of the economics profession, is to forget about finding the right model for “the economy” in the abstract, and focus more on quantitative description of concrete historical developments. I expressed this opinion in a bunch of tweets, storified here.

The Gosplan of capitalism. Schumpeter described banks as capitalism’s equivalent of the Soviet planning agency — a bank loan can be thought of as an order allocating part of society’s collective resources to a particular project. This applies even more to the central banks that set the overall terms of bank lending, but this conscious direction of the economy has been hidden behind layers of ideological obfuscation about the natural rate, policy rules and so on. As DeLong says, central banks are central planners that dare not speak their name. This silence is getting harder to maintain, though. Every day there seems to be a new news story about central banks intervening in some new credit market or administering some new price. Via Ben Bernanke, here is the Bank of Japan announcing it will start targeting the yield of 10-year Japanese government bonds, instead of limiting itself to the very short end where central banks have traditionally operated. (Although as he notes, they “muddle the message somewhat” by also announcing quantities of bonds to be purchased.) Bernanke adds:

there is a U.S. precedent for the BOJ’s new strategy: The Federal Reserve targeted long-term yields during and immediately after World War II, in an effort to hold down the costs of war finance.

And in the FT, here is the Bank of England announcing it will begin buying corporate bonds, an unambiguous step toward direct allocation of credit:

The bank will conduct three “reverse auctions” this week, each aimed at buying the bonds from particular sectors. Tuesday’s auction focuses on utilities and industries. Individual companies include automaker Rolls-Royce, oil major Royal Dutch Shell and utilities such as Thames Water.

Inflation or socialism. That interventions taken in the heat of a crisis to stabilize financial markets can end up being steps toward “a more or less comprehensive socialization of investment,” may be more visible to libertarians, who are inclined to see central banks as a kind of socialism already. At any rate, Scott Sumner has been making some provocative posts lately about a choice between “inflation or socialism”. Personally I don’t have much use for NGDP targeting — Sumner’s idée fixe — or the analysis that underlies it, but I do think he is onto something important here. To translate the argument into Keynes’ terms, the problem is that the minimum return acceptable to wealth owners may be, under current conditions, too high to justify the level of investment consistent with the minimum level of growth and employment acceptable to the rest of society. Bridging this gap requires the state to increasingly take responsibility for investment, either directly or via credit policy. That’s the socialism horn of the dilemma. Or you can get inflation, which, in effect, forces wealthholders to accept a lower return; or put it more positively, as Sumner does, makes it more attractive to hold wealth in forms that finance productive investment. The only hitch is that the wealthy — or at least their political representatives — seem to hate inflation even more than they hate socialism.

The corporate superorganism. One more for the “finance-as-socialism” files. Here’s an interesting working paper from Jose Azar on the rise of cross-ownership of US corporations, thanks in part to index funds and other passive investment vehicles.

The probability that two randomly selected firms in the same industry from the S&P 1500 have a common shareholder with at least 5% stakes in both firms increased from less than 20% in 1999Q4 to around 90% in 2014Q4 (Figure 1).1 Thus, while there has been some degree of overlap for many decades, and overlap started increasing around 2000, the ubiquity of common ownership of large blocks of stock is a relatively recent phenomenon. The increase in common ownership coincided with the period of fastest growth in corporate profits and the fastest decline in the labor share since the end of World War II…

A common element of theories of the firm boundaries is that … either firms are separately owned, or they combine. In stock market economies, however, the forces of portfolio diversification lead to … blurring firm boundaries… In the limit, when all shareholders hold market portfolios, the ownership of the firms becomes exactly identical. From the point of view of the shareholders, these firms should act “in unison” to maximize the same objective function… In this situation the firms have in some sense become branches of a larger corporate superorganism.

The same assumptions that generate the “efficiency” of market outcomes imply that public ownership could be just as efficient — or more so in the case of monopolies.

The present paper provides a precise efficiency rationale for … consumer and employee representation at firms… Consumer and employee representation can reduce the markdown of wages relative to the marginal product of labor and therefore bring the economy closer to a competitive outcome. Moreover, this provides an efficiency rationale for wealth inequality reduction –reducing inequality makes control, ownership, consumption, and labor supply more aligned… In the limit, when agents are homogeneous and all firms are commonly owned, … stakeholder representation leads to a Pareto efficient outcome … even though there is no competition in the economy.

As Azar notes, cross-ownership of firms was a major concern for progressives in the early 20th century, expressed through things like the Pujo committee. But cross-ownership also has been a central theme of Marxists like Hilferding and Lenin. Azar’s “corporate superorganism” is basically Hilferding’s finance capital, with index funds playing the role of big banks. The logic runs the same way today as 100 years ago. If production is already organized as a collective enterprise run by professional managers in the interest of the capitalist class as a whole, why can’t it just as easily be managed in a broader social interest?

Global pivot? Gavyn Davies suggests that there has been a global turn toward more expansionary fiscal policy, with the average rich country fiscal balances shifting about 1.5 points toward deficit between 2013 and 2016. As he says,

This seems an obvious path at a time when governments can finance public investment programmes at less than zero real rates of interest. Even those who believe that government programmes tend to be inefficient and wasteful would have a hard time arguing that the real returns on public transport, housing, health and education are actually negative.

I don’t know about that last bit, though — they don’t seem to find it that hard.

Taylor rule toy. The Atlanta Fed has a cool new gadget that lets you calculate the interest rate under various versions of the Taylor Rule. It will definitely be useful in the classroom. Besides the obvious pedagogical value, it also dramatizes a larger point — that macroeconomic variables like “inflation” aren’t objects simply existing in the world, but depend on all kinds of non-obvious choices about measurement and definition.

The new royalists. DeLong summarizes the current debates about monetary policy:

1. Do we accept economic performance that all of our predecessors would have characterized as grossly subpar—having assigned the Federal Reserve and other independent central banks a mission and then kept from them the policy tools they need to successfully accomplish it?

2. Do we return the task of managing the business cycle to the political branches of government—so that they don’t just occasionally joggle the elbows of the technocratic professionals but actually take on a co-leading or a leading role?

3. Or do we extend the Federal Reserve’s toolkit in a structured way to give it the tools it needs?

This is a useful framework, as is the discussion that precedes it. But what jumped out to me is how he reflexively rejects option two. When it comes to the core questions of economic policy — growth, employment, the competing claims of labor and capital — the democratically accountable, branches of government must play no role. This is all the more striking given his frank assessment of the performance of the technocrats who have been running the show for the past 30 years: “they—or, rather, we, for I am certainly one of the mainstream economists in the roughly consensus—were very, tragically, dismally and grossly wrong.”

I think the idea that monetary policy is a matter of neutral, technical expertise was always a dodge, a cover for class interests. The cover has gotten threadbare in the past decade, as the range and visibility of central bank interventions has grown. But it’s striking how many people still seem to believe in a kind of constitutional monarchy when it comes to central banks. They can see people who call for epistocracy — rule by knowers — rather than democracy as slightly sinister clowns (which they are). And they can simultaneously see central bank independence as essential to good government, without feeling any cognitive dissonance.

Did extending unemployment insurance reduce employment? Arin Dube, Ethan Kaplan, Chris Boone and Lucas Goodman have a new paper on “Unemployment Insurance Generosity and Aggregate Employment.” From the abstract:

We estimate the impact of unemployment insurance (UI) extensions on aggregate employment during the Great Recession. Using a border discontinuity design, we compare employment dynamics in border counties of states with longer maximum UI benefit duration to contiguous counties in states with shorter durations between 2007 and 2014. … We find no statistically significant impact of increasing unemployment insurance generosity on aggregate employment. … Our point estimates vary in sign, but are uniformly small in magnitude and most are estimated with sufficient precision to rule out substantial impacts of the policy…. We can reject negative impacts on the employment-to-population ratio … in excess of 0.5 percentage points from the policy expansion.

Media advisory with synopsis is here.

On other blogs, other wonders

Larry Summers: Low laborforce participation is mainly about weak demand, not demographics or other supply-side factors.

Nancy Folbre on Greg Mankiw’s claims that the one percent deserves whatever it gets.

At Crooked Timber, John Quiggin makes some familiar — but correct and important! — points about privatization of public services.

In the Baffler, Sam Kriss has some fun with the new atheists. I hadn’t encountered Kierkegaard’s parable of the madman who tells everyone who will listen “the world is round!” but it fits perfectly.

A valuable article in the Washington Post on cobalt mining in Africa. Tracing out commodity chains is something we really need more of.

Buzzfeed on Blue Apron. The reality of the robot future is often, as here, just that production has been reorganized to make workers less visible.

At Vox, Rachelle Sampson has a piece on corporate short-termism. Supports my sense that this is an area where there may be space to move left in a Clinton administration.

Sven Beckert has edited a new collection of essays on the relationship between slavery and the development of American capitalism. Should be worth looking at — his Empire of Cotton is magnificent.

At Dissent, here’s an interesting review of Jefferson Cowie’s and Robert Gordon’s very different but complementary books on the decline of American growth.

Links for September 23

I am going to strive to make these posts weekly. People need things to read.

The trouble with macro. I haven’t yet read any of the latest big-name additions to the “what’s wrong with macroeconomics?” pile: Romer (with update), Kocherlakota, Krugman, Blanchard. I should read them, maybe I will, maybe you should too. Here’s my own contribution, from a few years ago.

Tankus notes. You may know Nathan Tankus from around the internet. I’ve been telling him for a while that he should have a blog. He’s finally started one, and it’s very much worth reading. I’m having some trouble with one of his early posts. Well, that’s how it works: You comment on what you disagree with, not the things you think are smart and true and interesting — which in this case is a lot.

The shape of the elephant. Branko Milanovic’s “elephant graph” shows the changes in the global distribution of income across persons since 1980, as distinct from the more-familiar distribution of income within countries or between countries. The big story here is that while there has been substantial convergence, it isn’t across the board: The biggest gains were between the 10th and 75th percentiles of the global distribution, and at the very top; gains were much smaller in the bottom 10 percent and between the 70th and 99th percentiles. One question about this has been how much of this is due to China; as David Rosnick and now Adam Corlett of the Resolution Fondation note, if you exclude China the central peak goes away; it’s no longer true that growth was unusually fast in the middle of the global distribution. Corlett also claims that the very slow growth in the upper-middle part of the distribution — close to zero between the 75th and 85th percentiles — is due to big falls in income in the former Soviet block and Japan. Initially I liked the symmetry of this. But now I think Corlett is just wrong on this point; certainly he gives no real evidence for it. In reality, the slow growth of that part of the distribution seems to be almost entirely an artifact due to the slow growth of population in the upper part of the distribution; correct for that, as Rosnick does here, and the non-China distribution is basically flat between the 10th and 99th percentiles:

Yes, there does seem to be slightly slower growth just below the top. But given the imprecision of the data we shouldn’t put much weight on it. And in any case whatever the effect of falling incomes in Japan and Eastern Europe (and blue-collar incomes in the US and western Europe), it’s trivial compared to the increase in China. Outside of China, the global story seems to be the familiar one of the very rich pulling ahead, the very poor falling behind, and the middle keeping pace. Of course, it is true, as the original elephant graph suggested, that the share of income going to the upper-middle has fallen; but again, that’s because of slower population growth in the countries where that part of the distribution is concentrated, not because of slower income gains.

It’s important to stress that no one is claiming that Branko’s figures are wrong, and also that Branko is on the side of the angels here. He’s been fighting the good fight for years against the whiggish presumption of universal convergence.

Equality of opportunity and revolution. Speaking of Branko, here he is on the problem with equality of opportunity:

Upward mobility for some implies downward mobility for the others. But if those currently at the top have a stronghold on the top places in society, there will no upward mobility however much we clamor for it. … In societies that develop quickly even if a lot of mobility is about positional advantages, … it can be compensated by creating enough new social layers, new jobs and by making people richer. …

In more stagnant societies, mobility becomes a zero-sum game. To effect real social mobility in such societies, you need revolutions that, while equalizing chances or rather improving dramatically the chances of those on the bottom, do so at the cost of those on the top. … The French Revolution, until Napoleon to some extent reimposed the old state of affairs, was precisely such an upheaval: it oppressed the upper classes (clergy and nobility) and promoted the poorer classes. The Russian revolution did the same thing; it introduced an explicit reverse discrimination against the sons and daughters of former capitalists, and even of the intellectuals, in the access to education.

I think this is right. The principle of equality of opportunity is incompatible, not just practically but logically, with the principle of inheritance. The only way to realize it is to deprive those at the top of their power and privileges, which by definition is possible only in a revolutionary situation. This is one reason why I have no interest in a political program defined, even in its incremental first steps, in terms of equality of income or wealth. The goal isn’t equality but the abolition of the system which makes quantitative comparisons of people’s life-situations possible.

The post continues:

There is also an age element to such revolutions which fundamentally alter societies and lift those from below to the top. The young people benefit. In a beautiful short novel entitled “The élan of our youth” Alexander Zinoviev, a Russian logician and later dissident, describes the Stalinist purges from a young man’s perspective. The purges of all 40- or 50-year old “Trotskyites” and “wreckers” opened suddenly incredible vistas of upward mobility for those who were 20- or 25-year old. They could hope, at best, to come to the positions of authority in ten or fifteen years; now, that were suddenly thrown in charge of hundreds of workers, became chief designers of airplanes, top engineers of the metro. What was purge and Gulag for some, was upward mobility for others.

As this suggests, the overturning ofhierarchies didn’t stop with the revolutions themselves — that was the essential content of the various purges, to prevent a new elite from consolidating itself. I’ve always wondered how much vitality revolutionary France and Russia gained from these great overturnings. There are an enormous number of working-class people in our society, I have no doubt, who would be much more capable of running governments and factories, designing airplanes and subways, or teaching economics for that matter, than the people who get to do it.

We simply do not know — but we can fake it. Aswath Damodaran has a delicious post on the valuations that Elon Musk’s bankers came up with to justify Tesla’s acquisition of Solar City. The basic problem in these kinds of exercises is that the same price has to look high to the shareholders of the acquired company and low to the shareholders of the acquiring company. In this case, the Solar City shareholders have to believe that the 0.11 Tesla shares they are getting are worth more than the Solar City share they are giving up, while the Tesla shareholders have to believe just the opposite — that one Solar City share is worth more than the 0.11 Tesla shares they are giving for it. You can square this circle by postulating some gains from the combination — synergies! efficiencies! or, sotto voce, market power — that allows the acquirer to pay a premium over the market price while still supposedly getting a bargain. Those gains may be bullshit but at least there’s a story that makes sense. But as Damodaran explains, that isn’t even attempted here. Instead the two sets of advisors (both ultimately hired by Musk) simply use different assumptions for the growth rates and cost of capital for the two companies, generating two different valuations. For instance, Tesla’s advisors assume that Solar City’s existing business will grow at 3-5% in perpetuity, while Solar City’s advisors assume the same business will grow at 1.5-3%. So one set of shareholders can be told that a Solar City share is definitely worth less than 0.11 Tesla shares, while the other set of shareholders can be told that it is definitely worth more.

So what’s the interest here? Obviously, it’s always fun to se someone throwing shoes at the masters of the universe. But with my macroeconomist hat on, the important thing is it’s a snapshot of the concrete sociology behind the discounting of future cashflows. Whenever we talk about “the market” valuing some project or business, we are ultimately talking about someone at Lazard or Evercore plugging values into a spreadsheet. This is something people who imagine that production decisions are or can be based on market signals — including my Proudhonist friends — would do well to keep in mind. Solar City lost money last year. It lost money this year. It will lose money next year. It keeps going anyway not because “the market” wants it to, but because Musk and his bankers want it to. And their knowledge of the future isn’t any better founded than the rest of ours. Now, you could argue that this case is noteworthy because the projections are unusually bogus. Damodaran suggests they aren’t really, or only by degree. And in any case this sort of special pleading wouldn’t work if there were an objective basis for computing the true value of future cashflows. I suspect it was precisely Keynes’ experience with real-world financial transactions like this that made him stress the fundamental unknowability of the future.

Uber: The bar mitzvah moment. While we’re reading Damodaran, here’s another well-aimed shoe, this one at Uber. As he says, pushing down costs is not enough to make profits. You also need some way of charging more than costs. You need some kind of monopoly power, some source of rents: network externalities; increasing returns, and the financing to take advantage of them; proprietary technology; brand loyalty; explicit or implicit collusion with your competitors. Which of these does Uber have? maybe not any? Uber’s foray into self-driving cars is perhaps a way to generate rents, though they’re more likely to accrue to the companies that actually own the technology; I think it’s better seen as a ploy to convince investors for another quarter or two that there are rents there to be sought.

Izabella Kaminska covers some of the same territory in what may be the definitive Uber takedown at FT Alphaville. Though perhaps she focuses overmuch on how awful it would be if Uber’s model worked, and not enough on how unlikely it is to.

On other blogs, other wonders.

San Francisco Fed president John Williams writes, “during a downturn, countercyclical fiscal policy should be our equivalent of a first responder to recessions.” Does this mean that MMT has won?

Mike Konczal: Trump is full of policy.

My friend Sarah Jaffe interviews my friend Vamsi, on the massive strikes going on in India.

The Harry Potter books are bad books and and have a bad, childish, reactionary view of the world. So does J. K. Rowling.

The Mason-Tanebaum household has its first byline in the New York Times this week, with Laura’s review of the novel Black Wave in the Sunday books section.

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.

Trump’s Tariffs: A Dissent

Last week, the Washington Post ran an article by Jim Tankersley on what would happen if Trump got his way and the US imposed steep tariffs on goods from Mexico and China. I ended up as the objectively pro-Trump voice in the piece. The core of it was an estimates from Mark Zandi at Moody’s that a 45% tariff on goods from China and a 35% tariff on goods from Mexico (I don’t know where these exact numbers came from) would have an effect on the US comparable to the Great Recession, with output and employment both falling by about 5 percent relative to the baseline. About half this 5 percent fall in GDP would be due to retaliatory tariffs from China and Mexcio, and about half would come from the US tariffs themselves. As I told the Post, I think this is nuts.

Let me explain why I think that, and what a more realistic estimate would look like. But first, I should say that Tankersley did exactly what one ought to do with this story — asked the right question and went to a respected expert to help him answer it. The problem is with what that expert said, not the reporting. I should also say that my criticisms were presented clearly and accurately in the piece. But of course, there’s only so much you can say in even a generous quote in a newspaper article. Hence this post.

I haven’t seen the Moody’s analysis (it’s proprietary). All I know is what’s in the article, and the general explanation that Tankersley gave me in the interview. But from what I can tell, Zandi and his team want to tell a story like this. When the US imposes a tariff, it boosts the price of imported goods but leads to no substitution away from them. Instead, higher import prices just mean lower real incomes in the US. Then, when China and Mexico retaliate, that does lead to substitution away from US goods, and the lost exports reduce US real incomes further. But only under the most extreme assumptions can you get Zandi’s numbers out of this story.

While this kind of forecasting might seem mysterious, it mostly comes down to picking values for a few parameters — that is, making numerical guesses about relationships between the variables of interest. In this case, we have to answer three questions. The first question is, how much of the tariff is paid by the purchasers of imported goods, as opposed to the producers? The second question is, how do purchasers respond to higher prices — by substituting to domestic goods, by substituting to imports from other countries, or by simply paying the higher prices? Substitution to domestic goods is expansionary (boosts demand here), substitution to imports from elsewhere is neutral, and paying the higher prices is contractionary, since it reduces the income available for domestic spending. And the third question is, how much does a given shift in demand ultimately move GDP? The answer to the first question gives us the passthrough parameter. The answer to the second question gives us two price elasticities — a bilateral elasticity for imports from that one country, and an overall elasticity for total imports. The answer to the third question gives us the multiplier. Combine these and you have the change in GDP resulting from the tariff. Of course if you think the initial tariffs will provoke retaliatory tariffs from the other countries, you have to do the same exercise for those, with perhaps different parameters.

Let’s walk through this. Suppose the US — or any country — increases taxes on imports: What can happen? The first question is, how is the price of the imported good set — by costs in the producing country, or by market conditions in the destination? If conditions in the destination country affect price — if the producer is unable or unwilling to raise prices by the full amount of the tariff — then they will have to accept lower revenue per unit sold. This is referred to as pricing to market or incomplete passthrough, and empirical studies suggest it is quite important in import prices, especially in the US. Incomplete passthrough may result in changing profit margins for producers, or they may be able to adjust their own costs — wages especially — in turn. Where trade is a large fraction of GDP, some of the tax may eventually be translated into a lower price level in the exporting country.

Under floating exchange rates, the tariff may also lead a depreciation of the exporting country currency relative to the currency of the country imposing the tariff. This is especially likely where trade between the two countries is a large share of total trade for one or both of them. In this case, a tariff is more likely to cause a depreciation of the Mexican peso than of the Chinese renminbi, since the US accounts for a higher fraction of Mexico’s exports than of China’s, and the renminbi is actively managed by China’s central bank.

Taking all these effects together, passthrough for US imports is probably less than 0.5. In other words, the majority of a tariff’s impact will probably be on dollar revenue for producers, rather than dollar costs for consumers. So a 10 percent tariff increases costs of imported goods by something less than 5 percent and reduces the revenue per unit of producers by something more than 5 percent.

The fraction of the tax that is not absorbed by lower exporter profit margins, lower wages in the export industry or a lower price level in the exporting country, or by exchange rate changes, will be reflected in higher prices in the importing country. The majority of trade goods for the US (as for most countries) are intermediate and capital goods, and even imported consumption goods are almost never purchased directly by the final consumer. So on the importing side, too, there will be firms making a choice between accepting lower profit margins, reducing wages and other domestic costs, or raising prices. Depending on exactly where we are measuring import prices, this might further reduce passthrough.

Let’s ignore this last complication and assume that a tax that is not absorbed on the exporting-country side is fully passed on to final price of imported goods. Purchasers of imported goods now respond to the higher price either by substituting to domestic goods, or substituting to imported goods from some third country not subject to the tax, or continuing to purchase the imports at the higher price. To the extent they substitute to domestic goods, that will boost demand here; to the extent they substitute to third-country goods, the tax will have no effect here.

These rates of substitution are described by the price elasticity of imports, computed as the ratio of the percentage change in the price, to the resulting percentage change in the quantity imported. So for instance if we thought that a 1 percent increase in the price of imported goods leads to a 2 percent fall in the quantity purchased, we would say the price elasticity is 2. There are two elasticities we have to think about — the bilateral elasticity and the overall elasticity. For example, we might think that the bilateral elasticity for US imports from China was 3 while the overall price elasticity for was 1. In that case, a 1 percent increase in the price of Chinese imports would lead to a 3 percent fall in US imports from China but only one-third of that would be through lower total US imports; the rest would be through higher imports from third countries.

To the extent the higher priced imported goods are purchased, this may result in a higher price of domestic goods for which the imports are an input or a substitute; to the extent this happens, the tax will raise domestic inflation but leave real income unchanged. For the US, import prices have a relatively small effect on overall inflation, so we’ll ignore this effect here. If we included it, we would end up with a smaller effect.

To the extent that the increase in import prices neither leads to any substitution away from the imported goods, nor to any price increase in domestic goods, it will reduce real incomes in the importing country, and leave incomes in the exporting country unchanged. Conversely, to the extent that the tariff is absorbed by lower wages or profit margins in the exporting country, or leads to substitution away from that country’s goods, it reduces incomes in the exporting country, but not in the importing country. And of course, to the extent that there is no substitution away from the taxed goods, government revenue will increase. Zandi does not appear to have explicitly modeled this last effect, but it is important in thinking about the results — a point I’ll return to.

Whether the increase in import prices increases domestic incomes (by leading to substitution to domestic goods) or reduces them, the initial effect will be compounded as the change in income leads to changes in other spending flows. If, let’s say, an increase in the price of Chinese consumer goods forces Americans to cut back purchases of American-made goods, then the workers and business owners in the affected industries will find themselves with less income, which will cause them to reduce their spending in turn. This is the familiar multiplier. The direct effect may be compounded or mitigated by financial effects — the multiplier will be larger if you think (as Zandi apparently does) that a fall in income will be accompanied by a fall in asset prices with a further negative effect on credit and consumption, and smaller if you think that a trade-induced change in income will be offset by a change in monetary (or fiscal) policy. In the case where central bank’s interest rate policy is always able to hold output at potential, the multiplier will be zero — shocks to demand will have no effect on output. This extreme case looked more reasonable a decade ago than it does today. In conditions where the Fed can’t or won’t offset demand impacts, estimates of the US multiplier range as high as 2.5; a respectable middle-of-the-road estimate would be 1.5.

Let’s try this with actual numbers.

Start with passthrough. The overwhelming consensus in the empirical literature is that less than half of even persistent changes in exchange rates are passed through to US import prices. This recent survey from the New York Fed, for instance, reports a passthrough of about 0.3:

following a 10 percent depreciation of the dollar, U.S. import prices increase about 1 percentage point in the contemporaneous quarter and an additional 2 percentage points over the next year, with little if any subsequent increases.

The factors that lead to incomplete passthrough of exchange rate movements — such as the size of the US market, and the importance exporters of maintaining market share — generally apply to a tariff as well, so it’s reasonable to think passthrough would be similar. So a 45% tariff on Chinese goods would probably raise prices to American purchasers by only about 15%, with the remainder absorbed by profits and/or wages at Chinese exporters.

Next we need to ask about the effect of that price on American purchases. There is a large literature estimating trade price elasticities; a sample is shown in the table below. As you can see, almost all the import price elasticities are between 0.2 and 1.0. (Price elasticities seem to be greater for US exports than for imports; they also seem to be higher for most other countries than for the US.) The median estimates is around 0.5 for overall US imports. Country-specific estimates are harder to find but I’ve seen values around 1.0 for US imports from both China and Mexico. Using those estimates, we would expect a 15% increase in the price of Chinese imports to lead to a 15% fall in imports from China, with about half of the substitution going to US goods and half going to imports from other countries. Similarly, a 10% increase in the price of goods from Mexico (a 35% tariff times passthrough of 0.3) would lead to a 10% fall in imports from Mexico, with half of that being a switch to US goods and half to imports from elsewhere.

Screen Shot 2016-03-23 at 4.31.18 PM — Selected trade elasticity estimates for the US. The last column indicates if “price” was measured with an import price index (P), the exchange rate (E), or competitiveness, i.e. relative wages (C). The “P” estimates are most relevant for a tariff.

Finally, we ask how the combination of substitution away from imports from Mexico and China, and the rise in price of the remaining imports, would affect US output. US imports from China are about 2.7 percent of US GDP, and imports from Mexico are about 1.7 percent of GDP. So with the parameters above, substitution to US goods raises GDP by 7.5% x 2.7% (China) plus 5% x 1.7% (Mexico), or 0.29% of GDP. Meanwhile the higher prices of the remaining imports from China and Mexico reduce US incomes by 0.22 percent, for a net impact of a trivial one twentieth of one percent of GDP. Apply a standard multiplier of 1.5, and the tariffs boost GDP by 0.08 percent.

You could certainly get a larger number than this, for instance if you thought that passthrough of a tariff would be substantially greater than passthrough of exchange rate changes. And making US import demand just a bit less price-elastic is enough to turn the small positive impact into a small negative one. But it would be very hard to get an impact of even one percent of GDP in either direction. And it would be almost impossible to get a negative impact of the kind that Zandi describes. If you assume both that the tariffs are fully passed through to final purchasers, and that US import demand is completely insensitive to price then with a multiplier of 1.5, you get a 2.7 percent reduction in US GDP. Since this is close to Zandi’s number, this may be what he did. But again, these are extreme assumptions, with no basis in the empirical literature. That doesn’t mean you can’t use them, but you need to justify them; just saying the magic word “proprietary” is not enough. (Imagine all the trouble Jerry Friedman could have saved himself with that trick!)

And the very low price elasticity you need for this result has some funny implications. For instance, it implies that when China intervenes to weaken their currency, they are just impoverishing themselves, since — if demand is really price-inelastic — they are now sending us the same amount of goods and getting fewer dollars for each one. I doubt Zandi would endorse this view, but it’s a logical corollary of the ultra-low elasticity he needs to get a big cost to the US from the initial tariff. Note also that the low-elasticity assumption means that the tariff creates no costs for China or Mexico: their exporters pass the increased tariff on completely to US consumers, and lose no sales as a result. It’s not clear why they would “retaliate” for this.

Let’s assume, though, that China and Mexico do impose tariffs on US goods. US exports to China and Mexico equal 0.7 and 1.3 percent of US GDP respectively. Passthrough is probably higher for US exports — let’s say 0.6 rather than 0.3. Price elasticity is also probably higher — we’ll say 1.5 for both bilateral elasticities and for overall export elasticity. (In the absence of exchange-rate changes, there’s no reason to think that a fall in exports to China and Mexico will lead to a rise in exports to third countries.) And again, we’ll use a multiplier of 1.5. This yields a fall in US GDP from the countertariffs of just a hair under 1 percent. Combine that with the small demand boost from the tariff, and we get an overall impact of -0.9 percent of GDP.

I admit, this is a somewhat larger hit than I expected before I worked through this exercise. But it’s still much smaller than Zandi’s number.

My preferred back-of-the-envelope for the combined impact of the tariffs and countertariffs would be a reduction in US GDP of 0.9 percent, but I’m not wedded to this exact number. I think reasonable parameters could get you an impact on US GDP anywhere from positive 1 percent to, at the worst, negative 2 percent or so. But it’s very hard to get Zandi’s negative 5 percent. You need an extremely high passthrough for both import and export prices, plus extremely price-inelastic US import demand and extremely price-elastic demand for US exports — all three parameters well outside the range in the empirical literature. At one point a few years ago, I collected about 20 empirical estimates of US trade elasticities, and none of them had a price elasticity for US exports greater than 1.5. But even with 100% passthrough, and a generous multiplier of 2.0, you need an export price elasticity of 4 or so to get US GDP to fall by 5 points.

Still, while Zandi’s 5 percent hit to GDP seems beyond the realm of the plausible, one could perhaps defend a still-substantial 2 percent. Let’s think for a moment, though, about what this would mean.

First of all, it’s worth noting — as I didn’t, unfortunately, to the Post reporter — that tariff increases are, after all, tax increases. Whatever its effect on trade flows, a big increase in taxes will be contractionary. This is Keynes 101. Pick any activity accounting for 5 percent of GDP and slap a 40 percent tax on it, and it’s a safe bet that aggregate income will be lower as a result. The logic of the exercise would have been clearer if the tariff revenue were offset by a cut in some other tax, or increase in government spending. (Maybe this is what Trump means when he says Mexico will pay for the wall?) Then it would be clearer how much of the predicted impact comes from the tariff specifically, as opposed to the shift toward austerity that any such a big tax increase implies. The point is, even if you decide that a 2 percent fall in US GDP is the best estimate of the tariff’s impact, it wouldn’t follow that tariffs as such are a bad idea. It could be that a big tax increase is.

Second, let’s step back for a moment. While Mexico and China are two of our largest trade partners, they still account for less than a quarter of total US trade. Given passthrough of 0.3, the 45/35 percent tariff on Chinese/Mexican goods would raise overall US import prices by about 3 percent. Even with 100 percent passthrough, the tariffs would raise overall import prices by just 10 percent. The retaliatory tariffs would raise US export prices by about half this — 5 percent with full passthrough. (The difference is because these two countries account for a smaller share of US exports than of US imports). Now, let’s look at the movements of the dollar in recent years.

Since 2014, the dollar has risen 15 percent. That’s a 15 percent increase in the price of US goods in all our export markets — three times the impact of the hypothetical Mexican and Chinese tariffs. But before that, from 2002 to 2008, the dollar fell by over 20 percent. That raised the price of US imports by twice as much as the hypothetical Trump tariff. And so on on back to the 1970s. If you believe Zandi’s numbers, then the rise in the dollar over the past two years should already have triggered a severe recession. Of course it has not. It would be foolish to deny that movements of the dollar have had some effect on US output and employment. But no one, I think, would claim impacts on anything like this scale. Still, one thing is for sure: If you believe anything like Zandi’s numbers on the macro impacts of trade price changes, then it’s insane to allow exchange rates to be set by private speculators.

So if Zandi is wrong about the macro impact of tariffs, does that mean Trump is right? No. First of all, while I don’t think there’s any way to defend Zandi’s claim of a very large negative impact on GDP of a tariff (or of a more respectable, but economically equivalent, depreciation of the dollar), it’s almost as hard to defend a large positive impact. Despite all the shouting, the relative price of Chinese goods is just not a very big factor for aggregate demand in the US. If the goal is stronger demand and higher wages here, there are various things we can do. A more favorable trade balance with China (or Mexico, or anywhere else) is nowhere near the top of that list. Second, the costs of the tariff would be substantial for the rest of the world. It’s important not to lose sight of the fact that China, over the past generation, has seen perhaps the largest rise in living standards in human history. We can debate how critical exports to the US were in this process, but certainly the benefits to China of exports to the US were vastly greater than whatever costs they created here.

But the fact that an idea is wrong, doesn’t mean that we can ignore evidence and logic in refuting it. Trumpism is bad enough on the merits. There’s no need to exaggerate its costs.

UPDATE: My spreadsheet is here, if you want to play with alternative parameter values.

Links for March 14

A few things elsewhere on the web, relevant to recent conversations here.

1. Michael Reich and his colleagues at the Berkeley Center for Labor Research have a new report out on the impacts of a $15 minimum wage in New York. It does something I wish all studies of the minimum wage and employment would do: It explicitly decomposes the employment impact into labor productivity, price, demand and labor share effects. Besides being useful for policy, this links nicely to the macro discussion of alternative Phillips curves.

2. I like Susan Schroeder’s idea of creating a public credit-rating agency. It’s always interesting how the need to deal with immediate crises and dysfunctions creates pressure to socialize various aspects of the financial system. The most dramatic recent example was back in the fall of 2008, when the Fed began lending directly to anyone who needed to roll over commercial paper; but you can think of lots of examples, including QE itself, which involves the central bank taking over part of banks’ core function of maturity transformation.

3. On the subject of big business’s tendency to socialize itself, I should have linked earlier to Noah Smith’s discussion of “new industrialism” (including my work for the Roosevelt Institute) as the next big thing in economic policy. Eric Ries’ proposal for creating a new, nontransferable form of stock ownership reminded me of this bit from Keynes: “The spectacle of modern investment markets has sometimes moved me towards the conclusion that the purchase of an investment [should be] permanent and indissoluble, like marriage, except by reason of death or other grave cause… For this would force the investor to direct his mind to the long-term prospects and to those only.”

4. In comments to my recent post on the balance of payments, Ramanan points to a post of his, making the same point, more clearly than I managed to. Also worth reading is the old BIS report he links to, which explicitly distinguishes between autonomous and accommodative financial flows. Kostas Kalaveras also had a very nice post on this topic a while ago, noting that in Europe TARGET2 balances function as a buffer allowing private financial flows and current account balances to move independently from each other.

5. I’m teaching intermediate macroeconomics here at John Jay, as I do most semesters, and I’ve put some new notes I’m using up on the teaching page of this website. It’s probably mostly of interest to people who teach this stuff themselves, but I did want to call attention to the varieties of business cycles handout, which is somewhat relevant to current debates. It’s also an example of how I try to teach macro — focus on causal relationships between observable aggregates, rather than formal models based on equilibrium conditions.

Varieties of the Phillips Curve

In this post, I first talk about a variety of ways that we can formalize the relationship between wages, inflation and productivity. Then I talk briefly about why these links matter, and finally how, in my view, we should think about the existence of a variety of different possible relationships between these variables.

My Jacobin piece on the Fed was, on a certain abstract level, about varieties of the Phillips curve. The Phillips curve is any of a family graphs with either unemployment or “real” GDP on the X axis, and either the level or the change of nominal wages or the level of prices or the level or change of inflation on the Y axis. In any of the the various permutations (some of which naturally are more common than others) this purports to show a regular relationship between aggregate demand and prices.

This apparatus is central to the standard textbook account of monetary policy transmission. In this account, a change in the amount of base money supplied by the central bank leads to a change in market interest rates. (Newer textbooks normally skip this part and assume the central bank sets “the” interest rate by some unspecified means.) The change in interest rates leads to a change in business and/or housing investment, which results via a multiplier in a change in aggregate output. [1] The change in output then leads to a change in unemployment, as described by Okun’s law. [2] This in turn leads to a change in wages, which is passed on to prices. The Phillips curve describes the last one or two or three steps in this chain.

Here I want to focus on the wage-price link. What are the kinds of stories we can tell about the relationship between nominal wages and inflation?

The starting point is this identity:

(1) w = y + p + s

That is, the percentage change in nominal wages (w) is equal to the sum of the percentage changes in real output per worker (y; also called labor productivity), in the price level (p, or inflation) and in the labor share of output (s). [3] This is the essential context for any Phillips curve story. This should be, but isn’t, one of the basic identities in any intermediate macroeconomics textbook.

Now, let’s call the increase in “real” or inflation-adjusted wages r. [4] That gives us a second, more familiar, identity:

(2) r = w – p

The increase in real wages is equal to the increase in nominal wages less the inflation rate.

As always with these kinds of accounting identities, the question is “what adjusts”? What economic processes ensure that individual choices add up in a way consistent with the identity? [5]

Here we have five variables and two equations, so three more equations are needed for it to be determined. This means there are large number of possible closures. I can think of five that come up, explicitly or implicitly, in actual debates.

Closure 1:

First is the orthodox closure familiar from any undergraduate macroeconomics textbook.

(3a) w = pE + f(U); f’ < 0

(4a) y = y*

(5a) p = w – y

Equation 3a says that labor-market contracts between workers and employers result in nominal wage increases that reflect expected inflation (pE) plus an additional increase, or decrease, that reflects the relative bargaining power of the two sides. [6] The curve described by f is the Phillips curve, as originally formulated — a relationship between the unemployment rate and the rate of change of nominal wages. Equation 4a says that labor productivity growth is given exogenously, based on technological change. 5a says that since prices are set as a fixed markup over costs (and since there is only labor and capital in this framework) they increase at the same rate as unit labor costs — the difference between the growth of nominal wages and labor productivity.

It follows from the above that

(6a) w – p = y

and

(7a) s = 0

Equation 6a says that the growth rate of real wages is just equal to the growth of average labor productivity. This implies 7a — that the labor share remains constant. Again, these are not additional assumptions, they are logical implications from closing the model with 3a-5a.

This closure has a couple other implications. There is a unique level of unemployment U* such that w = y + p; only at this level of unemployment will actual inflation equal expected inflation. Assuming inflation expectations are based on inflation rates realized in the past, any departure from this level of unemployment will cause inflation to rise or fall without limit. This is the familiar non-accelerating inflation rate of unemployment, or NAIRU. [7] Also, an improvement in workers’ bargaining position, reflected in an upward shift of f(U), will do nothing to raise real wages, but will simply lead to higher inflation. Even more: If an inflation-targetting central bank is able to control the level of output, stronger bargaining power for workers will leave them worse off, since unemployment will simply rise enough to keep nominal wage growth in line with y* and the central bank’s inflation target.

Finally, notice that while we have introduced three new equations, we have also introduced a new variable, pE, so the model is still underdetermined. This is intended. The orthodox view is that the same set of “real“ values is consistent with any constant rate of inflation, whatever that rate happens to be. It follows that a departure of the unemployment rate from U* will cause a permanent change in the inflation rate. It is sometimes suggested, not quite logically, that this is an argument in favor of making price stability the overriding goal of policy. [8]

If you pick up an undergraduate textbook by Carlin and Soskice, Krugman and Wells, or Blanchard, this is the basic structure you find. But there are other possibilities.

Closure 2: Bargaining over the wage share

A second possibility is what Anwar Shaikh calls the “classical” closure. Here we imagine the Phillips curve in terms of the change in the wage share, rather than the change in nominal wages.

(3b) s = f(U); f’ < 0

(4b) y = y*

(5b) p = p*

Equation 3b says that the wage share rises when unemployment is low, and falls when unemployment is high. In this closure, inflation as well as labor productivity growth are fixed exogenously. So again, we imagine that low unemployment improves the bargaining position of workers relative to employers, and leads to more rapid wage growth. But now there is no assumption that prices will follow suit, so higher nominal wages instead translate into higher real wages and a higher wage share. It follows that:

(6b) w = f(U) + p + y

Or as Shaikh puts it, both productivity growth and inflation act as shift parameters for the nominal-wage Phillips curve. When we look at it this way, it’s no longer clear that there was any breakdown in the relationship during the 1970s.

If we like, we can add an additional equation making the change in unemployment a function of the wage share, writing the change in unemployment as u.

(7b) u = g(s); g’ > 0 or g’ < 0

If unemployment is a positive function of the wage share (because a lower profit share leads to lower investment and thus lower demand), then we have the classic Marxist account of the business cycle, formalized by Goodwin. But of course, we might imagine that demand is “wage-led” rather than “profit-led” and make U a negative function of the wage share — a higher wage share leads to higher consumption, higher demand, higher output and lower unemployment. Since lower unemployment will, according to 3b, lead to a still higher wage share, closing the model this way leads to explosive dynamics — or more reasonably, if we assume that g’ < 0 (or impose other constraints), to two equilibria, one with a high wage share and low unemployment, the other with high unemployment and a low wage share. This is what Marglin and Bhaduri call a “stagnationist” regime.

Let’s move on.

Closure 3: Real wage fixed.

I’ll call this the “Classical II” closure, since it seems to me that the assumption of a fixed “subsistence” wage is used by Ricardo and Malthus and, at times at least, by Marx.

(3c) w – p = 0

(4c) y = y*

(5c) p = p*

Equation 3c says that real wages are constant the change in nominal wages is just equal to the change in the price level. [9] Here again the change in prices and in labor productivity are given from outside. It follows that

(6c) s = -y

Since the real wage is fixed, increases in labor productivity reduce the wage share one for one. Similarly, falls in labor productivity will raise the wage share.

This latter, incidentally, is a feature of the simple Ricardian story about the declining rate of profit. As lower quality land if brought into use, the average productivity of labor falls, but the subsistence wage is unchanged. So the share of output going to labor, as well as to landlords’ rent, rises as the profit share goes to zero.

Closure 4:

(3d) w = f(U); f’ < 0

(4d) y = y*

(5d) p = p*

This is the same as the second one except that now it is the nominal wage, rather than the wage share, that is set by the bargaining process. We could think of this as the naive model: nominal wages, inflation and productivity are all just whatever they are, without any regular relationships between them. (We could even go one step more naive and just set wages exogenously too.) Real wages then are determined as a residual by nominal wage growth and inflation, and the wage share is determined as a residual by real wage growth and productivity growth. Now, it’s clear that this can’t apply when we are talking about very large changes in prices — real wages can only be eroded by inflation so far. But it’s equally clear that, for sufficiently small short-run changes, the naive closure may be the best we can do. The fact that real wages are not entirely a passive residual, does not mean they are entirely fixed; presumably there is some domain over which nominal wages are relatively fixed and their “real” purchasing power depends on what happens to the price level.

Closure 5:

One more.

(3e) w = f(U) + a pE; f’ < 0; 0 < a < 1

(4e) y = b (w – p); 0 < b < 1

(5e) p = c (w – y); 0 < c < 1

This is more generic. It allows for an increase in nominal wages to be distributed in some proportion between higher inflation, an increase in the wage share, and faster productivity growth. The last possibility is some version of Verdoorn’s law. The idea that scarce labor, or equivalently rising wages, will lead to faster growth in labor productivity is perfectly admissible in an orthodox framework. But somehow it doesn’t seem to make it into policy discussions.

In other word, lower unemployment (or a stronger bargaining position for workers more generally) will lead to an increase in the nominal wage. This will in turn increase the wage share, to the extent that it does not induce higher inflation and/or faster productivity growth:

(6e) s = (1 – b – c) w

This closure includes the first two as special cases: closure 1 if we set a = 0, b = 0, and c = 1, closure 2 if we set a = 1, b = 0, and c < 1. It’s worth framing the more general case to think clearly about the intermediate possibilities. In Shaikh’s version of the classical view, tighter labor markets are passed through entirely to a higher labor share. In the conventional view, they are passed through entirely to higher inflation. There is no reason in principle why it can’t be some to each, and some to higher productivity as well. But somehow this general case doesn’t seem to get discussed.

Here is a typical example of the excluded middle in the conventional wisdom: “economic theory suggests that increases in labor costs in excess of productivity gains should put upward pressure on prices; hence, many models assume that prices are determined as a markup over unit labor costs.” Notice the leap from the claim that higher wages put some pressure on prices, to the claim that wage increases are fully passed through to higher prices. Or in terms of this last framework: theory suggests that b should be greater than zero, so let’s assume b is equal to one. One important consequence is to implicitly exclude the possibility of a change in the wage share.

So what do we get from this?

First, the identity itself. On one level it is obvious. But too many policy discussions — and even scholarship — talk about various forms of the Phillips curve without taking account of the logical relationship between wages, inflation, productivity and factor shares. This is not unique to this case, of course. It seems to me that scrupulous attention to accounting relationships, and to logical consistency in general, is one of the few unambiguous contributions economists make to the larger conversation with historians and other social scientists. [10]

For example: I had some back and forth with Phil Pilkington in comments and on twitter about the Jacobin piece. He made some valid points. But at one point he wrote: “Wages>inflation + productivity = trouble!” Now, wages > inflation + productivity growth just means, an increasing labor share. It’s two ways of saying the same thing. But I’m pretty sure that Phil did not intend to write that an increase in the labor share always means trouble. And if he did seriously mean that, I doubt one reader in a hundred would understand it from what he wrote.

More consequentially, austerity and liberalization are often justified by the need to prevent “real unit labor costs” from rising. What’s not obvious is that “real unit labor costs” is simply another word for the labor share. Since by definition the change real unit labor costs is just the change in nominal wages less sum of inflation and productivity growth. Felipe and Kumar make exactly this point in their critique of the use of unit labor costs as a measure of competitiveness in Europe: “unit labor costs calculated with aggregate data are no more than the economy’s labor share in total output multiplied by the price level.” As they note, one could just as well compute “unit capital costs,” whose movements would be just the opposite. But no one ever does, instead they pretend that a measure of distribution is a measure of technical efficiency.

Second, the various closures. To me the question of which behavioral relations we combine the identity with — that is, which closure we use — is not about which one is true, or best in any absolute sense. It’s about the various domains in which each applies. Probably there are periods, places, timeframes or policy contexts in which each of the five closures gives the best description of the relevant behavioral links. Economists, in my experience, spend more time working out the internal properties of formal systems than exploring rigorously where those systems apply. But a model is only useful insofar as you know where it applies, and where it doesn’t. Or as Keynes put it in a quote I’m fond of, the purpose of economics is “to provide ourselves with an organised and orderly method of thinking out particular problems” (my emphasis); it is “a way of thinking … in terms of models joined to the art of choosing models which are relevant to the contemporary world.” Or in the words of Trygve Haavelmo, as quoted by Leijonhufvud:

There is no reason why the form of a realistic model (the form of its equations) should be the same under all values of its variables. We must face the fact that the form of the model may have to be regarded as a function of the values of the variables involved. This will usually be the case if the values of some of the variables affect the basic conditions of choice under which the behavior equations in the model are derived.

I might even go a step further. It’s not just that to use a model we need to think carefully about the domain over which it applies. It may even be that the boundaries of its domain are the most interesting thing about it. As economists, we’re used to thinking of models “from the inside” — taking the formal relationships as given and then asking what the world looks like when those relationships hold. But we should also think about them “from the outside,” because the boundaries within which those relationships hold are also part of the reality we want to understand. [11] You might think about it like laying a flat map over some curved surface. Within a given region, the curvature won’t matter, the flat map will work fine. But at some point, the divergence between trajectories in our hypothetical plane and on the actual surface will get too large to ignore. So we will want to have a variety of maps available, each of which minimizes distortions in the particular area we are traveling through — that’s Keynes’ and Haavelmo’s point. But even more than that, the points at which the map becomes unusable, are precisely how we learn about the curvature of the underlying territory.

Some good examples of this way of thinking are found in the work of Lance Taylor, which often situates a variety of model closures in various particular historical contexts. I think this kind of thinking was also very common in an older generation of development economists. A central theme of Arthur Lewis’ work, for example, could be thought of in terms of poor-country labor markets that look like what I’ve called Closure 3 and rich-country labor markets that look like Closure 5. And of course, what’s most interesting is not the behavior of these two systems in isolation, but the way the boundary between them gets established and maintained.

To put it another way: Dialectics, which is to say science, is a process of moving between the concrete and the abstract — from specific cases to general rules, and from general rules to specific cases. As economists, we are used to grounding concrete in the abstract — to treating things that happen at particular times and places as instances of a universal law. The statement of the law is the goal, the stopping point. But we can equally well ground the abstract in the concrete — treat a general rule as a phenomenon of a particular time and place.

[1] In graduate school you then learn to forget about the existence of businesses and investment, and instead explain the effect of interest rates on current spending by a change in the optimal intertemporal path of consumption by a representative household, as described by an Euler equation. This device keeps academic macroeconomics safely quarantined from contact with discussion of real economies.

[2] In the US, Okun’s law looks something like Delta-U = 0.5(2.5 – g), where Delta-U is the change in the unemployment rate and g is inflation-adjusted growth in GDP. These parameters vary across countries but seem to be quite stable over time. In my opinion this is one of the more interesting empirical regularities in macroeconomics. I’ve blogged about it a bit in the past and perhaps will write more in the future.

[3] To see why this must be true, write L for total employment, Z for the level of nominal GDP, Y for per-capita GDP, W for the average wage, and P for the price level. The labor share S is by definition equal to total wages divided by GDP:

S = WL / Z

Real output per worker is given by

Y = (Z/P) / L

Now combine the equations and we get W = P Y S. This is in levels, not changes. But recall that small percentage changes can be approximated by log differences. And if we take the log of both sides, writing the log of each variable in lowercase, we get w = y + p + s. For the kinds of changes we observe in these variables, the approximation will be very close.

[4] I won’t keep putting “real” in quotes. But it’s important not to uncritically accept the dominant view that nominal quantities like wages are simply reflections of underlying non-monetary magnitudes. In fact the use of “real” in this way is deeply ideological.

[5] A discovery that seems to get made over and over again, is that since an identity is true by definition, nothing needs to adjust to maintain its equality. But it certainly does not follow, as people sometimes claim, that this means you cannot use accounting identities to reason about macroeconomic outcomes. The point is that we are always using the identities along with some other — implicit or explicit — claims about the choices made by economic units.

[6] Note that it’s not necessary to use a labor supply curve here, or to make any assumption about the relationship between wages and marginal product.

[7] Often confused with Milton Friedman’s natural rate of unemployment. But in fact the concepts are completely different. In Friedman’s version, causality runs the other way, from the inflation rate to the unemployment rate. When realized inflation is different from expected inflation, in Friedman’s story, workers are deceived about the real wage they are being offered and so supply the “wrong” amount of labor.

[8] Why a permanently rising price level is inconsequential but a permanently rising inflation rate is catastrophic, is never explained. Why are real outcomes invariant to the first derivative of the price level, but not to the second derivative? We’re never told — it’s an article of faith that money is neutral and super-neutral but not super-super-neutral. And even if one accepts this, it’s not clear why we should pick a target of 2%, or any specific number. It would seem more natural to think inflation should follow a random walk, with the central bank holding it at its current level, whatever that is.

[9] We could instead use w – p = r*, with an exogenously given rate of increase in real wages. The logic would be the same. But it seems simpler and more true to the classics to use the form in 3c. And there do seem to be domains over which constant real wages are a reasonable assumption.

[10] I was just starting grad school when I read Robert Brenner’s long article on the global economy, and one of the things that jumped out at me was that he discussed the markup and the wage share as if they were two independent variables, when of course they are just two ways of describing the same thing. Using s still as the wage share, and m as the average markup of prices over wages, s = 1 / (1 + m). This is true by definition (unless there are shares other than wages or profits, but none such figure in Brenner’s analysis). The markup may reflect the degree of monopoly power in product markets while the labor share may reflect bargaining power within the firm, but these are two different explanations of the same concrete phenomenon. I like to think that this is a mistake an economist wouldn’t make.

[11] The Shaikh piece mentioned above is very good. I should add, though, the last time I spoke to Anwar, he criticized me for “talking so much about the things that have changed, rather than the things that have not” — that is, for focusing so much on capitalism’s concrete history rather than its abstract logic. This is certainly a difference between Shaikh’s brand of Marxism and whatever it is I do. But I’d like to think that both approaches are called for.

EDIT: As several people pointed out, some of the equations were referred to by the wrong numbers. Also, Equation 5a and 5e had inflation-expectation terms in them that didn’t belong. Fixed.

EDIT 2: I referred to an older generation of development economics, but I think this awareness that the territory requires various different maps, is still more common in development than in most other fields. I haven’t read Dani Rodrik’s new book, but based on reviews it sounds like it puts forward a pretty similar view of economics methodology.