Category Archives: PSST and Macro

Simon Wren-Lewis on the Phillips Curve

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He writes,

So we choose a microfoundation because it gives us the aggregate answer suggested by the data, and not because of evidence that this microfoundation is appropriate. We then insist that everything in that model has to be consistent with this microfoundation, and that our model has been built from only thinking about what individual agents do. Have we just replaced ad hoc with post hoc?

Read the whole thing for context. Pointer from Mark Thoma. My comments:

1. My joke is that the Phillips Curve went from being an empirical finding in search of theory to a theory in search of empirical support.

2. Empirically, the only thing of which we can really be sure is that the best predictor of inflation is the lagged dependent variable (this is hardly the only macroeconomic variable to which this applies). After that, the magnitude (and even the sign) of the relationship between wage growth and employment varies quite a bit depending on how you do your specification searching.

3. Once again, let my plug my macro memoir.

Matt Rognlie Proposes a Solution

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In the comments on this post, he suggests a possible way to reconcile secular stagnation with a high return on capital.

One way to reconcile the two is to say that Piketty’s return on capital includes the equity premium (and other premia for privately held businesses, etc.), whereas the secular stagnation idea of a perpetual ZLB deals with only the riskfree rate.

Some remarks:

1. Fischer Black said that finance is about time and risk. The risk-free rate is the price of time. The equity premium might be a proxy for the price of risk.

2. In Keynesian terms, perhaps one can think of a low risk-free rate as reflecting the desire to hoard and a high risk premium as reflecting low animal spirits.

3. As Matt notes, this approach to reconciling secular stagnation with a high return on capital implies that those earning the high returns are being rewarded for taking risks in an economy in which such risk-taking is scarce. Picketty seems to be pretty confident that high earners will not change their behavior much in response to higher taxes. Perhaps this might be true of labor supply. But can one rule out a significant dampening effect on risk-taking?

Read Matt’s entire comment. As he points out, the secular stagnation story is difficult to reconcile with some fairly basic calculations concerning capital and investment.

Working with the Tautology Model

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Scott Sumner writes,

the NGDP approach is a very naive model that treats NGDP sort of like a big pot of money, which is shared out among workers with sticky wages. If some day the pot is smaller, then there’s less money to share, and some workers end up disappointed (unemployed.) It’s completely agnostic about the micro foundations…

Which is fine with me. Again, think of the mineshaft analogy, with real-world observations on the surface and the optimization-equilibrium paradigm buried below. To connect the two, you can try to start inside the mine and tunnel out, or you can start outside and tunnel in. My displeasure with much of macro the past thirty years is that it insists on the inside-out approach.

Consider the tautology model: hours worked = total wages divided by the hourly wage.

If the Fed were to target total wages, what could go wrong? Sumner cites the Lucas critique. In this context that would mean that the sticky nominal wages you observed in the past were due to the Fed not trying to mess with total wages. As soon as the Fed tries to mess with total wages, workers will catch on and start paying closer attention to real wages.

I believe that something else will go wrong. The Fed will not be able to hit its target for total wages! Suppose we write MV = W, where W is total wages and V is the velocity of money expressed in terms of total wages rather than nominal GDP. What I am inclined to believe is that moderate changes in M will lead to approximately equal and opposite changes in V.

Picture this as the Fed having a steering wheel, M, that is only loosely connected with the front axle, W. The Fed can turn the wheel quite hard while the axle barely wiggles. It may take extensive turning of the monetary steering wheel over a long period of time to obtain a response of total wages. In fact, the period over which wages are sticky may turn out to be shorter than the lag between shifts in monetary policy and changes in total nominal wages.

We have a complex, sophisticated monetary system, in which people’s ability to undertake transactions is not proportional to the amount of currency in circulation. We have a large financial system, in which the Fed is only one player. I keep trying to hold down people’s estimation of the power of the Fed.

Made Me Think of Garrett Jones

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Ellen R. McGrattan and Edward C. Prescott write,

In 2008, only a small part of all intangible investment was included in the measure of GDP from the Bureau of Economic Analysis (BEA). As a result, the fact that labor productivity rose between 2008 and 2009 is not inconsistent with theoretical predictions. The intuition is simple: during a downturn, measured labor productivity rises if we significantly underestimate the drop in total output. We underestimate the drop in total output if there are large unmeasured investments.

Pointer from Mark Thoma. Recall that Jones once tweeted that most workers do not make widgets. Instead they help to build organizational capital.

The authors, who were let go by the Minneapolis Fed several months ago in what was widely viewed as a “purge,” go on to point out that the Commerce Department recently decided to incorporate investment in intellectual property into its measure of investment, and that in recent decades this category accounts for about 1/3 of all investment. They point out that the government does not include other forms of intangible investment, including “advertising, marketing, and organizational capital.”

On the input side, we measure Garett Jones workers. However, on the output side, we tend not to count what they produce. This creates a mis-measured economy. When firms are undertaking a lot of intangible investment, measured productivity is understated. When they cut back in intangible investment, measured productivity growth is overstated.

I think, though, that in order to explain the reduction in intangible investment, you have to tell a PSST story. That is, I do not think that there was an economy-wide “shock” that reduced productivity. I think that there were firms that came to the realization that the outlook did not warrant continued intangible investment. Think of bookstores, newspapers, and other victims of creative destruction.

Follow-up Questions

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On this post. I will summarize the questions as (1) don’t marginal costs really fall when a sector goes through a structural shift, which should lead to a drop in prices? and (2) why don’t investment booms cause dislocation?

1. In microeconomics, I tell my high school students that price discrimination explains everything. Almost every real-world business case finds firms facing very low marginal costs but needing to recover fixed costs. So you see many efforts to segment the market and charge a higher price to the customer with less elastic demand. For your question, the relevant point is that firms always face very low marginal costs–in either booms or recessions. They choose their price structure so as to maximize revenue. A recession does not fundamentally alter their pricing problem.

As a side note, you give several examples of industries that you argue have mostly production workers. I am not convinced. Take health care, for example. If a hospital or a medical practice experiences a 15 percent decline in demand, which workers become expendable? You still need all the administrative staff–accounting folks, the insurance-billing folks, the IT folks. You can lay off some of the folks who touch patients, but that is not an overwhelming proportion of the health care work force.

2. In the Schumpeterian story of PSST, an investment boom is what you observe when the new opportunity arrives but the legacy industry does not recognize it. So Borders keeps investing in stores while Amazon undertakes expansion. This is unsustainable, since the market is not big enough for both of them. When Borders closes, investment declines. The causal factor is technological change. In the short run, investment and employment rise, because the legacy industry is in denial. When they get the memo, investment and employment fall. It seems to me that the pattern in the legacy industry is for firms to hang on as long as possible, and then crash. You might think that they would decay gradually, but that does not seem to be the pattern.

Recessions and Structural Change

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Ryan Avent writes,

Examining patterns of polarisation in America, Nir Jaimovich and Henry Siu find that displacement of routine work is not a gradual process but occurs almost entirely during recessions. Since the mid-1980s, roughly 92% of job loss in middle-skill, routine jobs has taken place during or within a year of recessions (as dated by the National Bureau of Economic Research). This pattern is linked to the phenomenon of “jobless recoveries”, which followed the recessions of 1990-1, 2001, and 2007-9 but not earlier downturns.

Pointer from Tyler Cowen. My first thought is that this makes it hard to sort out cyclical and structural change.

Avent’s hypothesis is that low inflation raises real wages and induces labor-saving substitution.

I think that there might be a number of hypotheses to explain the phenomenon. For example, what we call a recession could just be a bunching up of the process of shedding ZMP workers. In theory, ZMP workers should be let go at a steady rate, but it could be that firms come to a common realization that it is time to face reality.

But read Avent’s post. It is obvious that he would regard the UK in recent years as supporting his hypothesis more than mine.

The Macro Wars: Inside-out vs. Outside-in

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I remember reading once that it is still not understood how the giraffe manages to pump an adequate blood supply all the way up to its head; but it is hard to imagine that anyone would therefore conclude that giraffes do not have long necks. At least not anyone who had ever been to a zoo.

—Robert M. Solow

Solow wrote those words at the height of the macro wars. I was very much on his side at the time, and this post will explain the sense in which I am still on his side.

Think of the task of macroeconomics as completing a mineshaft between the “outside” (what we observe in the world) and the “inside” (a mathematical model that is “pure” in its microfoundations). The Old Keynesians, including Solow, took an outside-in approach: let’s work from what we observe, build a crude model to handle that, and maybe eventually we can dig deeper and find the microfoundations. Start from the fact that there is a giraffe, and try to figure out how it maintains its blood supply. Do not start from a model of blood supply that precludes the existence of giraffes.

For the Old Keynesians, macroeconometric models were a tool with which to observe the world. They provided the starting point for the outside-in approach. Then Robert Lucas came along with his “critique,” which said that if you took an inside-out approach that included rational expectations, macroeconometric models would break down. The Lucas Critique launched the macro wars.

Lo and behold, macroeconometric models did break down. However, I do not think that the Lucas Critique had much to do with it. You can get more on my perspective by reading this paper and by reading my macro book.

The New Keynesians took up Lucas’ challenge by adopting an inside-out approach. Stan Fischer’s course at MIT was 100 percent inside-out theory, and I viscerally hated it. At the start of one class, I stood up, proclaiming loudly and sarcastically to Fischer and my fellow students how much I enjoyed the topic of “monetary growth models,” which was the particularly pointless mathematical, er, self-abuse that he was teaching us that week.

I chose Solow as my dissertation adviser, and I wrote an outside-in thesis, working backwards from what we observe to a theory of price rigidity. Not having a thesis that focused on rational expectations and not having Fischer plugging for me were career-altering. I was doomed to failure if I tried academia, and so I wound up on a different track. I don’t think I was the one who lost out on that deal.

So if you are trying to follow the methodological discussions among Mark Thoma, Paul Krugman, Noah Smith, and others, you will find me still on the side of the Old Keynesians. I still despise inside-out macro, and I still prefer the outside-in approach.

What has happened to me since I left MIT is that I no longer think that macroeconometric models provide a valid lens into observing the real world, and I no longer think that Keynesianism is the One True Way. The real world is still out there, and I still think it should be our starting point for digging the mineshaft. I still respect the Old Keynesian approach of starting with observations about the world rather than starting at the bottom of the mine with a “pure” model. However, I am willing to entertain theories that differ considerably from the Old Keynesian one. Hence, PSST, which you can also read more about in my essays/papers.

Show Me the Model

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Mark Thoma writes,

There is no grand, unifying theoretical structure in economics. We do not have one model that rules them all. Instead, what we have are models that are good at answering some questions – the ones they were built to answer – and not so good at answering others…

But the New Keynesian model has its limits. It was built to capture “ordinary” business cycles driven by pricesluggishness of the sort that can be captured by the Calvo model model of price rigidity. The standard versions of this model do not explain how financial collapse of the type we just witnessed come about, hence they have little to say about what to do about them (which makes me suspicious of the results touted by people using multipliers derived from DSGE models based upon ordinary price rigidities). For these types of disturbances, we need some other type of model, but it is not clear what model is needed. There is no generally accepted model of financial catastrophe that captures the variety of financial market failures we have seen in the past.

I think that Mark is closer to being on track than are some folks like this fellow or this fellow. A model is not all-or-nothing, right-or-wrong. A model is like a pair of binoculars. It helps you see some things more clearly, at the expense of not seeing other things at all. If you do not have that understanding of the modeling process, then you are missing what I see as a fundamental methodological truth.

Some more comments:

1. In my estimate, the real-world usefulness of New Keynesian and DSGE models is close to zero. Even if it is a bit more positive than that, there is no way to justify the intensity with which those models were pursued. And as much as Paul Krugman wants to blame Minnesota, I keep coming back to the fact that it was Stan Fischer who turned out the grad students who captured probably 75 percent of the available top-tier academic macro posts available for a period of about 15 years, effectively over-running the entire ecosystem. To suggest instead that the profession caved into bullying from Prescott or Sargent or Lucas is to create a false narrative, offering what amounts to an intellectual bailout for MIT. Read my recent macro book to try to get a better sense of the history.

2. Mark Thoma may be optimistic in suggesting that there is a “right model” to use in every situation. It may be that there are important macroeconomic episodes that are beyond the scope of any model to truly capture.

3. If there is a “right model” for what I call the Financial Crisis Aftermath episode, then I think it will have to include a role for malinvestment. Not so much malinvestment because of the Fed’s misbehavior in 2004 (sorry, John Taylor), and even not so much malinvestment in housing. In the financial sector, I suspect that a lot of the malinvestment reflected poor judgment on the part of both private-sector executives and regulators. In the nonfinancial sector, I suspect that the malinvestment included poor choices on the part of people in terms of skill acquisition (a lot of college degrees in psychology and “____ studies” majors) and a lot of malinvestment on the part of firms that took too long to recognize that the Internet was blowing apart their business models.

4. The PSST story emphasizes the lengthy, trial-and-error process involved in finding new patterns of sustainable specialization and trade. It tends to defy the entire “model” genre, because modeling tends to involve solving for equilibrium, rather than describing what may be a laborious process of groping within a state of disequilibrium.

PSST Questions from a Reader

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First,

Suppose that for some reason, the marginal value of many former employees in sector A has gone down nearly to zero. My contention is that whenever this happens, the marginal cost of sector A’s products should be plummeting…The spiffy new technology can only dislocate traditional production if it is so productive that it can outbid firms with access to this cheap labor. Maybe this will happen, but either way we should be seeing a huge decline in marginal cost.

I have a somewhat different perspective on zero marginal product. Remember that nowadays very few workers produce widgets. As Garrett Jones pointed out, they produce organizational capital. In the sense of the neoclassical production function, they are always ZMP. The decision to retain them or unload them depends on management’s assessment of the future value of organizational capital.

Suppose we take the example from Ben Stiller’s mediocre remake of the Walter Mitty story, in which Walter’s job is threatened because the print magazine he works for is looking obsolete. It’s not the case that if you could just bring down the marginal cost of producing copies of the print magazine, everything would be fine. The magazine has a dim future, regardless. To make matters worse for Walter, his skill set involves working with negatives from old-fashioned film cameras.

Second,

we don’t see huge relative price declines in the sectors that are losing workers due to some structural change. The auto industry, one of the very most cyclical industries in terms of output and employment, shows virtually no cyclical pattern in relative prices

The pre-1990 business cycles generally involved accumulation of excess inventories of autos and other durable goods. In hindsight, these seem like timing errors on the part of businesses. An inventory recession is not a permanent disturbance to patterns of sustainable specialization and trade. When the excess inventory has been worked off, you can recall the men on the production line.

The secular change to the auto industry in Detroit and elsewhere in the Midwest, due to more automation and stiff competition from overseas as well as from the South, is quite different from an inventory correction. In theory, the effect could be gradual, with Detroit shedding a few workers each year. In practice, the adjustment tends to be “lumpy,” with an entire plan shutting its doors forever, then a few years of little change, then another plant shutting down forever, etc.

the postwar experience is even more problematic for PSST. Including the prewar arms buildup, at the end of the war in 1945 the economy had just spent 4 to 5 years on an extreme military-oriented path, a vastly distorted pattern of production and consumption. Before that, there was the Great Depression, not exactly a normal time either. The transition to a relatively normal postwar economy following 1945, therefore, was an extraordinary adjustment

I agree, except that I want to be clear that I do not think of it as a transition back to a normal economy by pre-war standards. 1949 was very different from 1929. The agricultural work force has plummeted. The proportion of the work force with only an 8th-grade education has shrunk. The urban factory worker is giving way to the suburban sales clerk.

In my view, the key to the transition was the uprooting that took place during the War. After you have been shipped all over the country (or all over the world) and met all sorts of people from other backgrounds, you are not as committed to returning to that obsolete farm or declining small town or stagnating city. You are much more willing and able to move to where the opportunities are. My guess is that we had a particularly mobile society in the late 1940s, and this contributed to the surprisingly rapid establishment of patterns of sustainable specialization and trade.

But I agree that one of the more interesting questions of economic history is how the U.S. economy managed to undertake the transition to peace time so quickly and smoothly.

The Case Against VARs

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In a comment on this post, Noah Smith commended to me the work of George-Marios Angeletos of MIT. Unfortunately, Angeletos is fond of vector autoregressions (VARs), which I detest.

I got my start in macro working on structural macroeconometric models. I saw them close up, and I am keenly aware of the problems with them. Hence, I wrote Macroeconometrics: The Science of Hubris.

However, I will give the old-fashioned macroeconometricians credit for at least worrying about the details of the data they are using. If there are structural factors that are changing over time, such as trend productivity growth or labor force participation, the macroeconometrician will keep track of these trends. If there are special factors that change quarterly patterns, such as the “cash-for-clunkers” program that shifted automobile purchases around, the macroeconometrician will take these into account.

The VAR crowd cheerfully ignores all the details in macro data. The economist with a computer program that will churn out VARs is like a 25-year-old with a new immersion blender. He does not want to spend time cooking carefully-selected ingredients. He just wants to throw whatever is in the pantry into the blender to make a smoothie or soup. (Note that I am being unfair to people with immersion blenders. I am not being unfair to people who use VARs.)

The VAR appeared because economists became convinced that structural macroeconometric models are subject to the Lucas Critique, which says that as monetary policy attempts to manipulate demand, people will adjust their expectations. My reaction to this is

(a) the Lucas critique is a minor theoretical curiosity. There are much worse problems with macroeconometrics in practice.

(b) How the heck does running a VAR exempt you from the Lucas Critique? A VAR is no less subject to breakdown than is a structural model.

The macroeconometric project that I first worked with is doomed to fail. Implicitly, you are trying to make 1988 Q1 identical to 2006 Q3 except for the one causal factor with which you are concerned. This cannot be done. There is too much Manzian causal density.

The VAR just takes this doomed macroeconometric project and cavalierly ignores details. It is not an improvement over the macroeconometrics that I learned in the 1970s. On the contrary, it is inferior. And if the big names in modern macro all use it, that does not say that there is something right about VAR. It says that there is something wrong with all the big names in modern macro. On this point, Robert Solow and I still agree.