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:

Source: David Rosnick
Source: David Rosnick

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.)

potentialGDPThe 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.

dollar exrate

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.

How Strong Is Business Investment, Really?

DeLong rises to defend Ben Bernanke, against claims that unconventional monetary policy in recent years has discouraged businesses from investing. Business investment is doing just fine, he says:

As I see it, the Fed’s open-market operations have produced more spending–hence higher capacity utilization–and lower interest rates–has more advantageous costs of finance–and we are supposed to believe that its policies “have hurt business investment”?!?! … As I have said before and say again, weakness in overall investment is 100% due to weakness in housing investment. Is there an argument here that QE has reduced housing investment? No. Is nonresidential fixed investment below where one would expect it to be given that the overall recovery has been disappointing and capacity utilization is not high?

As evidence, DeLong points to the fact that nonresidential investment as a share of GDP is back where it was at the last two business cycle peaks.

As it happens, I agree with DeLong that it’s hard to make a convincing case that unconventional monetary policy is holding back business investment. Arguments about the awfulness of low interest rates seem more political or ideological, based on the real or imagined interests of interest-receivers than any identifiable economic analysis. But there’s a danger of overselling the opposite case.

It is certainly true that, as a share of potential GDP, nonresidential investment is not low by historical standards. But is this the right measure to be looking at? I think not, for a couple of reasons, one relatively minor and one major. The minor reason is that the recent redefinition of investment by the BEA to include various IP spending makes historical comparisons problematic. If we define investment as the BEA did until 2013, and as businesses still do under GAAP accounting standards, the investment share of GDP remains quite low compared to previous expansions. The major reason is that it’s misleading to evaluate investment relative to (actual or potential GDP), since weak investment will itself lead to slower GDP growth. [1]

On the first point: In 2013, the BEA redefined investment to include a variety of IP-related spending, including the commercial development of movies, books, music, etc. as well as research and development. We can debate whether, conceptually, Sony making Steve Jobs is the same kind of thing as Steve Jobs and his crew making the iPhone. But it’s important to realize that the apparent strength of investment spending in recent expansions is more about the former kind of activity than the latter.  [2] More relevant for present purposes, since this kind of spending was not counted as investment — or even broken out separately, in many cases — prior to 2013, the older data are contemporary imputations. We should be skeptical of comparing today’s investment-cum-IP-and-R&D to the levels of 10 or 20 years ago, since 10 or 20 years ago it wasn’t even being measured. This means that historical comparisons are considerably more treacherous than usual. And if you count just traditional (GAAP) investment, or even traditional investment plus R&D, then investment has not, in fact, returned to its 2007 share of GDP, and remains well below long-run average levels. [3]

investment

More importantly, using potential GDP as the yardstick is misleading because potential GDP is calculated simply as a trend of actual GDP, with a heavier weight on more recent observations. By construction, it is impossible for actual GDP to remain below potential for an extended period. So the fact that the current recovery is weak by historical standards automatically pulls down potential GDP, and makes the relative performance of investment look good.

We usually think that investment spending the single most important factor in business-cycle fluctuations. If weak investment growth results in a lower overall level of economic activity, investment as a share of GDP will look higher. Conversely, an investment boom that leads to rapid growth of the economy may not show up as an especially high investment share of GDP. So to get a clear sense of the performance of business investment, its better to look at the real growth of investment spending over a full business cycle, measured in inflation-adjusted dollars, not in percent of GDP. And when we do this, we see that the investment performance of the most recent cycle is the weakest on record — even using the BEA’s newer, more generous definition of investment.

investmentcycles_broad
Real investment growth, BEA definition

The figure above shows the cumulative change in real investment spending since the previous business-cycle peak, using the current (broad) BEA definition. The next figure shows the same thing, but for the older, narrower GAAP definition. Data for both figures is taken from the aggregates published by the BEA, so it includes closely held corporations as well as publicly-traded ones. As the figures show, the most recent cycle is a clear outlier, both for the depth and duration of the fall in investment during the downturn itself, and even more for the slowness of the subsequent recovery.

investmentcycles_narrow
Real investment growth, plant and equipment only

Even using the BEA’s more generous definition, it took over 5 years for inflation-adjusted investment spending to recover its previous peak. (By the narrower GAAP definition, it took six years.) Five years after the average postwar business cycle peak, BEA investment spending had already risen 20 percent in real terms. As of the second quarter of 2015 — seven-and-a-half years after the most recent peak, and six years into the recovery — broad investment spending was up only 10 percent from its previous peak. (GAAP investment spending was up just 8.5 percent.) In the four previous postwar recoveries that lasted this long, real investment spending was up 63, 24, 56, and 21 percent respectively. So the current cycle has had less than half the investment growth of the weakest previous cycle. And it’s worth noting that the next two weakest investment performances of the ten postwar cycles came in the 1980s and the 2000s. In recent years, only the tech-boom period of the 1990s has matched the consistent investment growth of the 1950s, 1960s and 1970s.

So I don’t think it’s time to hang the “Mission Accomplished” banner up on Maiden Lane quite yet.

As DeLong says, it’s not surprising that business investment is weak given how far output is below trend. But the whole point of monetary policy is to stabilize output. For monetary policy to work, it needs to able to reliably offset lower than normal spending in other areas with stronger than normal investment spending. If after six years of extraordinarily stimulative monetary policy (and extraordinarily high corporate profits), business investment is just “where one would expect given that the overall recovery has been disappointing,” that’s a sign of failure, not success.

 

[1] Another minor issue, which I can’t discuss now, is DeLong’s choice to compare “real” (inflation-adjusted) spending to “real” GDP, rather than the more usual ratio of nominal values. Since the price index for investment goods consistent rises more slowly than the index for GDP as a whole, this makes current investment spending look higher relative to past investment spending.

[2] This IP spending is not generally counted as investment in the GAAP accounting rules followed by private businesses. As I’ve mentioned before, it’s problematic that national accounts diverge from private accounts this way. It seems to be part of a troubling trend of national accounts being colonized by economic theory.

[3] R&D spending is at least reported in financial statements, though I’m not sure how consistently. But with the other new types of IP investment — which account for the majority of it — the BEA has invented a category that doesn’t exist in business accounts at all. So the historical numbers must involve more than usual amount degree of guesswork.

Mixed Messages from The Fed and the Bond Markets

It’s conventional opinion that the Fed will begin to raise its policy rate by the end of 2015, and continue raising rates for the next couple years. In the FT, Larry Summers argues that this will be a mistake. And he observes that bond markets don’t seem to share the conventional wisdom: “Long term bond markets are telling us that real interest rates are expected to be close to zero in the industrialised world over the next decade.”

The Summers column inspired me to take a look at bond prices and flesh out this observation. It is straightforward to calculate how much the value of a bond change in response to a change in interest rates. So by looking at the current yields on bonds of different maturities, we can see what expectations of future rate changes are consistent with profit-maximizing behavior in bond markets. [1]

The following changes shows the yields of Treasury bonds of various maturities, and the capital loss for each bond from a one-point rise in yield over the next year. (All values are in percentage points.)

Maturity Yield as of July 2015 Value Change from 1-Point Rise
30 year 3.07 -17.1
20 year 2.77 -13.9
10 year 2.32 -8.4
5 year 1.63 -4.6
1 year 0.30 -0.0

So if the 30-year rate rises by one point over the next year, someone who just bought a 30-year bond will suffer a 17 percent capital loss.

It’s clear from these numbers that Summers is right. If, over the next couple of years, interest rates were to “normalize” to their mid-90s levels (about 3 points higher than today), long bonds would lose half their value. Obviously, no one would hold bonds at today’s yields if they thought there was an appreciable chance of that happening.

We can be more precise. For any pair of bonds, the ratio of the difference in yields to the difference in capital losses from a rate increase, is a measure of the probability assigned by market participants to that increase. For example, purchasing a 20-year bond rather than a 30-year bond means giving up 0.3 percentage points of yield over the next year, in return for losing only 14 percent rather than 17 percent if there’s a general 1-point increase in rates. Whether that looks like a good or bad tradeoff will depend on how you think rates are likely to change.

For any pair of bonds, we can calculate the change in interest rates (across the whole yield curve) that would keep the overall return just equal between them. Using the average yields for July, we get:

30-year vs 20-year: +0.094%

30-year vs. 10-year: +0.086%

30-year vs. 5-year: +0.115%

20-year vs. 10-year +0.082%

20-year vs. 5 year: + 0.082%

Treasury bonds seem to be priced consistent with an expected tenth of a percent or so increase in interest rates over the next year.

In other words: If you buy a 30 year bond rather than a 20-year one, or a 20-year rather than 10-year, you will get a higher interest rate. But if it turns out that market rates rise by about 0.1 percentage points (10 basis points) over the next year, the greater capital losses on longer bonds will just balance their higher yields. So if you believe that interest rates in general will be about 10 basis points higher a year from now than they are now, you should be just indifferent between purchasing Treasuries of different maturities. If you expect a larger increase in rates, long bonds will look overpriced and you’ll want to sell them; if you expect a smaller increase in rates than this, or a decrease, then long bonds will look cheap to you and you’ll want to buy them. [2]

A couple of things to take from this.

First, there is the familiar Keynesian point about the liquidity trap. When long rates are low, even a modest increase implies very large capital losses for holders of long bonds. Fear of these losses can set a floor on long rates well above prevailing short rates. This, and not the zero lower bound per se, is the “liquidity trap” described in The General Theory.

Second,  compare the implied forecast of a tenth of a point increase in rates implied by today’s bond prices, to the forecasts in the FOMC dot plot. The median member of the FOMC expects an increase of more than half a point this year, 2 points by the end of 2016, and 3 points by the end of 2017. So policymakers at the Fed are predicting a pace of rate increases more than ten times faster than what seems to be incorporated into bond prices.

FOMC dotplot

If the whole rate structure moves in line with the FOMC forecasts, the next few years will see the biggest losses in bond markets since the 1970s. Yet investors are still holding bonds at what are historically very low yields. Evidently either bond market participants do not believe that Fed will do what it says it will, or they don’t believe that changes in policy rate will have any noticeable effect on longer rates.

And note: The belief that long rates unlikely to change much, may itself prevent them from changing much. Remember, for a 30-year bond currently yielding 3 percent, a one point change in the prevailing interest rate leads to a 17 point capital loss (or gain, in the case of a fall in rates). So if you have even a moderately strong belief that 3 percent is the most likely or “normal” yield for this bond, you will sell or buy quickly when rates depart much from this. Which will prevent such departures from happening, and validate beliefs about the normal rate. So we shouldn’t necessarily expect to see the whole rate structure moving up and down together. Rather, long rates will stay near a conventional level (or at least above a conventional floor) regardless of what happens to short rates.

This suggests that we shouldn’t really be thinking about a uniform shift in the rate structure. (Though it’s still worth analyzing that case as a baseline.) Rather, an increase in rates, if it happens, will most likely be confined to the short end. The structure of bond yields seems to fit this prediction. As noted above, the yield curve at longer maturities implies an expected rate increase on the order of 10 basis points (a tenth of a percentage point), the 10-year vs 5 year, 10 year vs 1 year, and 5 year vs 1 year bonds imply epected increases of 18, 24 and 29 basis points respectively. This is still much less than dot plot, but it is consistent with idea that bond markets expect any rate increase to be limited to shorter maturities.

In short: Current prices of long bonds imply that market participants are confident that rates will not rise substantially over the next few years. Conventional wisdom, shared by policymakers at the Fed, says that they will. The Fed is looking at a two point increase over the next year and half, while bond rates imply that it will take twenty years. So either Fed won’t do what it says it will, or it won’t affect long rates, or bondholders will get a very unpleasant surprise. The only way everyone can be right is if trnasmission from policy rate to long rates is very slow — which would make the policy rate an unsuitable tool for countercyclical policy.

This last point is something that has always puzzled me about standard accounts of monetary policy. The central bank is supposed to be offsetting cyclical fluctuations by altering the terms of loan contracts whose maturities are much longer than typical business cycle frequencies. Corporate bonds average about 10 years, home mortgages, home mortgages of course close to 30. (And housing seems to be the sector most sensitive to policy changes.) So either policy depends on systematically misleading market participants, to convince them that cyclical rate changes are permanent; or else monetary policy must work in some completely different way than the familiar interest rate channel.

 

 

[1] In the real world things are more complicated, both because the structure of expectations is more complex than a scalar expected rate change over the next period, and because bonds are priced for their liquidity as well as for their return.

[2] I should insist in passing, for my brothers and sisters in heterodoxy, that this sort of analysis does not depend in any way on “consumers” or “households” optimizing anything, or on rational expectations. We are talking about real markets composed of profit-seeking investors, who certainly hold some expectations about the future even if they are mistaken.

New Article in the Review of Keynesian Economics

My paper with Arjun Jayadev, “The Post-1980 Debt Disinflation: An Exercise in Historical Accounting,” has now been published in the Review of Keynesian Economics. (There is some other stuff that looks interesting in there as well, but unfortunately most of the content is paywalled, a choice I’ve complained to the editors about.) I’ve posted the full article on the articles page on this site.

Here’s the abstract:

The conventional division of household payment flows between consumption and saving is not suitable for investigating either the causes of changing household debt–income ratios, or the interaction of household debt with aggregate demand. To explain changes in household debt, it is necessary to use an accounting framework that isolates net credit-market flows to the household sector, and that takes account of changes in the debt–income ratio resulting from nominal income growth as well as from new borrowing. To understand the implications of changing household income and expenditure flows for aggregate demand, it is necessary to distinguish expenditures that contribute to demand from expenditures that do not. Applying a conceptually appropriate accounting framework to the historical data reveals that the rise in household leverage over the past 3 decades cannot be understood in terms of increased household borrowing. For both the decade of the 1980s and the full post-1980 period, rising household debt–income ratios are entirely explained by the rise in nominal interest rates relative to nominal income growth. The rise in household debt after 1980 is best thought of as a debt disinflation, analogous to the debt deflation of the 1930s.

You can read the rest here.

The IMF on Investment since 2008

Vox today has a useful piece by five IMF economists on the behavior of business investment during and since the Great Recession. [1] From my point of view, there are three important points here.


1. The most important difference between this cycle and previous ones is the larger fall and slower recovery of private investment. This has always been my view, and I think it’s an especially important point for heterodox folks to take on board because there has been such (excessive, in my opinion) emphasis on the inequality-consumption link in explaining persistent demand weakness.

This relationship between output and investment is consistent with previous recessions: 

business investment has deviated little from what could be expected given the weakness in economic activity. In other words, firms have reacted to weak sales – both current and prospective – by reducing capital spending. Indeed, in surveys, businesses typically report lack of customer demand as the dominant challenge they face.

In other words, the old Keynesian “accelerator” story explains the bulk of the shortfall in investment since 2008.
2. Historically, deviations in output and investment has been persistent; there is no tendency for recessions to be followed by a return to the previous trend. 
The blue line shows the behavior of output and investment in recessions historically, relative to the pre-recession trend. Note that is no tendency for the gap to close, as much as six years after the previous peak.
The authors don’t emphasize this point, but it is important. If we look at recessions across a range of industrialized countries, on average the output losses are permanent. There is no tendency for output to return to the pre-trend. If this is true, there’s no basis for the conventional distinction between a demand-determined “short run” and a supply-determined “long run.” There is just one dynamic process. Steve Fazzari has reached this same conclusion, as I’ve written about here. Roger Farmer has just posted an econometric demonstration that in the postwar US, output changes are persistent — there is no tendency to return to a trend.
 3. There’s no reason to think that the investment deficit is explained by financial constraints. I should say frankly that the paper didn’t move my priors much at all on this point, but it’s still interesting that that’s what it says. By their estimates, firms in more “financially-dependent” sectors (this is a standard technique, but whatever) initially reduced investment more than firms in less financially-dependent sectors, but as of 2013 investment in both groups of firms were the same 40 percent below the pre-crisis trend. If you believe these results — and again, I don’t put much weight on them, except as an indicator of the IMF flavor of received opinion — then while tighter credit may have helped trigger the crisis, it cannot explain the persistent weakness of demand. Or from a policy perspective — and the authors do say this — measures to improve access to credit are unlikely to achieve much, at least relative to measures to boost demand.
Investment by sector

So these are features it might be nice to incorporate into a macro model — investment determined mainly by (changes in) current output; a single system of demand-based dynamics, as opposed to a short-run demand story and a long-run supply-based steady state growth path; a possibility of multiple equilibria, such that (let’s say) a temporary interruption of credit flows can produce a persistent reduction in output.  On one level I don’t especially trust these results. But on another level, I think they provide a good set of stylized facts that macro models should aspire to parsimoniously explain. 

[1] The European Vox, not the Klein-Yglesias one.

UPDATE: Krugman today points to the same work and also interprets it as support for an accelerator story.

New-Old Paper on the Balance of Payments

Four or five years ago, I wrote a paper arguing that the US current account deficit, far from being a cause of the crisis of 2008, was a stabilizing force in the world economy. I presented it at a conference and then set it aside. I recently reread it and I think the arguments hold up well. If anything the case that the US, as the center of the world financial system, ought to run large current account deficits indefinitely looks even stronger now, given the contrasting example of Germany’s behavior in the European system.

I’ve put the paper up as a working paper at John Jay economics department site. Here’s the abstract:

Persistent current account imbalances need not contribute to macroe- conomic instability, despite widespread claims to the contrary by both mainstream and Post Keynesian economists. On the contrary, in a world of large capital inflows, a high and stable level of world output is most likely when the countries with the least capacity to generate capital inflows normally run current account surpluses, while the countries with the greatest capacity to generate capital inflows (the US in particular) normally run current account deficits. An emphasis on varying balance of payments constraints is consistent with the larger Post Keynesian vision, which emphasizes money flows and claims are not simply passive reflections of “real” economic developments, but exercise an important influence in their own right. It is also consistent with Keynes’ own views. This perspective helps explain why the crisis of 2008 did not take the form of a fall in the dollar, and why reserve accumulation in East Asia successfully protected those countries from a repeat of the crisis of 1997. Given the weakness of the “automatic” mechanisms that are supposed to balance trade, income and financial flows, a reduction of the US current account deficit is likely to exacerbate, rather than ameliorate, global macroeconomic instability.

You can read the whole thing here.