Tag: economics

Does the Fed Still Believe in the NAIRU?

(I write occasional opinion pieces for Barron’s. This one was published there in October 2024. My previous pieces are here.)

Not long ago, there was widespread agreement on how to think about monetary policy. When the Federal Reserve hikes, this story went, it makes credit more expensive, reducing spending on new housing and other forms of capital expenditure. Less spending means less demand for labor, which means higher unemployment. With unemployment higher, workers accept smaller wage gains, and slower wage growth is in turn passed on as slower growth in prices — that is, lower inflation. 

This story, which you still find in textbooks, has some strong implications. One is that there was a unique level of unemployment consistent with stable 2% inflation — what is often called the “nonaccelerating inflation rate of unemployment,” or NAIRU. 

The textbook story also assumes that  wage- and price-setting depend on expectations of future prices. So it’s critical for central banks to stabilize not only current inflation but beliefs about future inflation; this implies a commitment to head off any inflationary pressures even before prices accelerate. On the other hand, if there is a unique unemployment rate consistent with stable inflation, then the Fed’s mandate is dual only in name. In practice, full employment and price stability come to the same thing.

In the early 21st century, all this seemed sufficiently settled that fundamental debates over monetary policy could be treated as a question for history, not present-day economics.

The worldwide financial crisis of 2007-2009 unsettled the conversation. The crisis, and, even more, the glacial recovery that followed it, opened the door to alternative perspectives on monetary policy and inflation. Jerome Powell, who took office as Federal Open Market Committee chair in 2018, was more open than his predecessors to a broader vision of both the Fed’s goals and the means of achieving them. In the decade after the crisis, the idea of a unique, fundamentals-determined NAIRU came to seem less plausible.

These concerns were crystallized in the strategic review process the Fed launched in 2019. That review resulted, among other things, in a commitment to allow future overshooting of the 2% inflation target to make up for falling short of it. The danger of undershooting seemed greater than in the past, the Fed acknowledged.

One might wonder how much this represents a fundamental shift in the Fed’s thinking, and how much it was simply a response to the new circumstances of the 2010s. Had Fed decision-makers really changed how they thought about the economy?

Many of us try to answer these questions by parsing the publications and public statements of Fed officials. 

A fascinating recent paper by three European political scientists takes this approach and carries it to a new level. The authors—Tobias Arbogast, Hielke Van Doorslaer and Mattias Vermeiern—take 120 speeches by FOMC members from 2012 through 2022, and systematically quantify the use of language associated with defense of the NAIRU perspective, and with various degrees of skepticism toward it. Their work allows us to put numbers on the shift in Fed thinking over the decade. 

The paper substantiates the impression of a move away from the NAIRU framework in the decade after the financial crisis. By 2019-2020, references to the natural rate or to the need to preempt inflation had almost disappeared from the public statements of FOMC members, while expressions of uncertainty about the natural rate, of a wait-and-see attitude toward inflation, and concern about hysteresis (long-term effects of demand shortfalls) had become more common. The mantra of “data dependence,” so often invoked by Powell and others, is also part of the shift away from the NAIRU framework, since it implies less reliance on unobservable parameters of economic models. 

Just as interesting as the paper’s confirmation of a shift in Fed language, is what it says about how the shift took place. It was only in small part the result of changes in the language used by individual FOMC members. A much larger part of the shift is explained by the changing composition of the FOMC, with members more committed to the NAIRU gradually replaced by members more open to alternative perspectives. 

The contrast between 2014-2018 Chair Janet Yellen and Powell is particularly noteworthy in this respect. Yellen, by the paper’s metric, was among the most conservative members of the FOMC, most committed to the idea of a fixed NAIRU and the need to preemptively raise rates in response to a strong labor market. Powell is at the opposite extreme — along with former Vice Chair Lael Brainard, he is the member who has most directly rejected the NAIRU framework, and who is most open to the idea that tight labor markets have long-term benefits for income distribution and productivity growth. The paper’s authors suggest, plausibly, that Powell’s professional training as a lawyer rather than an economist means that he is less influenced by economic models; in any case, the contrast shows how insulated the politics of the Fed are from the larger partisan divide.

Does the difference in conceptual frameworks really matter? The article’s authors argue that it does, and I agree. FOMC members may sincerely believe that they are nonideological technicians, pragmatically responding to the latest data in the interests of society as a whole. But data and interests are always assessed through the lens of some particular worldview. 

To take one important example: In the NAIRU framework, the economy’s productive potential is independent of monetary policy, while inflation expectations are unstable. This implies that missing the full employment target has at worst short-term effects, while missing the inflation target grows more costly over time. NAIRU, in other words, makes a preemptive strike on any sign of inflation seem reasonable. 

On the other hand, if you think that hysteresis is real and important, and that inflation is at least sometimes a question of supply disruptions rather than unanchored expectations, then it may be the other way round. Falling short of the employment target may be the error with more lasting consequences. This is a perspective that some FOMC members, particularly Powell and Brainard, were becoming open to prior to the pandemic.

Perhaps even more consequential: if there is a well-defined NAIRU and we have at least a rough idea of what it is, then it makes sense to raise rates in response to a tight labor market, even if there is no sign, yet, of rising inflation. But if we don’t believe in the NAIRU, or at least don’t feel any confidence about its level, then it makes more sense to focus more on actual inflation, and less on the state of the labor market.

By the close of the 2010s, the Fed seemed to be well along the road away from the NAIRU framework. What about today? Was heterodox language on inflation merely a response to the decade of weak demand following the financial crisis, or did it represent a more lasting shift in how the Fed thinks about its mission?

On this question, the evidence is mixed. After inflation picked up in 2022, we did see some shift back to the older language at the Fed. You will not find, in Powell’s recent press conferences, any mention of the longer-term benefits of a tight labor market that he pointed to a few years ago. Hysteresis seems to have vanished from the lexicon. 

On the other hand, the past few years have also not been kind to those who see a tight link between the unemployment rate and inflation. When inflation began rising at the start of 2021, unemployment was still over 6%; two years later, when high inflation was essentially over, unemployment was below 4%. If the Fed had focused on the unemployment rate, it would have gotten inflation wrong both coming and going.

This is reflected in the language of Powell and other FOMC members. One change in central-bank thinking that seems likely to last, is a move away from the headline unemployment rate as a measure of slack. The core of the NAIRU framework is a tight link between labor-market conditions and inflation. But even if one accepts that link conceptually, there’s no reason to think that the official unemployment rate is the best measure of those conditions. In the future, we are likely to see discussion of a broader set of labor-market indicators.

The bigger question is whether the Fed will return to its old worldview where tight labor markets are seen as in themselves an inflationary threat. Or will it stick with its newer, agnostic and data-driven approach, and remain open to the possibility that labor markets can stay much stronger than we are used to, without triggering rising inflation? Will it return to a single-minded focus on inflation, or has there been a permanent shift to giving more independent weight on the full employment target? As we watch the Fed’s actions in coming months, it will be important to pay attention not just to what they do, but to why they say they are doing it.

 

FURTHER THOUGHTS: I really liked the Arbogast et al. paper, for reasons I couldn’t fully do justice to in the space of a column like this.

First of all, in addition to the new empirical stuff, it does an outstanding job laying out the intellectual framework within which the Fed operates. For better or worse, monetary policy is probably more reliant than most things that government does on a consciously  held set of theories.

Second, it highlights — in a way I have also tried to — the ways that hysteresis is not just a secondary detail, but fundamentally undermines the conceptual foundation on which conventional macroeconomic policy operates. The idea that potential output and long-run growth (two sides of the same coin) are determined prior to, and independent of, current (demand-determined) output, is what allows a basically Keynesian short-run framework to coexist with the the long-run growth models that are the core of modern macro. If demand has lasting effects on the laborforce, productivity growth and potential output, then that separation becomes untenable, and the whole Solow apparatus floats off into the ether. In a world of hysteresis, we no longer have a nice hierarchy of “fast” and “slow” variables; arguably there’s no economically meaningful long run at all.1

Arbogast and co don’t put it exactly like this, but they do emphasize that the existence of hysteresis (and even more reverse hysteresis, where an “overheating” economy permanently raises potential) fundamentally undermine the conventional distinction between the short run and the long run.

This leads to one of the central points of the paper, which I wish I’d been able to highlight more: the difference between what they call “epistemological problematization” of the NAIRU, that is doubts about how precisely we can know it and related “natural” parameters; and “ontological problematization,” or doubts that it is a relevant concept for policy at all. At a day to day operational level, the difference may not always be that great; but I think — as do the authors — that it matters a lot for the evolution of policy over longer horizons or in new conditions.

The difference is also important for those of us thinking and writing about the economy. The idea of some kind of “natural” or “structural” parameters, of a deeper model that abstracts from demand and money, deviations from which are both normatively bad and important only in the short term — this is an incubus that we need to dislodge if we want to move toward any realistic theorizing about capitalist economies. It substitutes an imaginary world with none of the properties of the world that matter for most of the questions we are interested — a toy train set to play with instead of trying to solve the very real engineering problems we face.

I appreciate the paper’s concluding agnosticism about how far the Fed has actually moved away form this framework. As I mentioned in the piece, I was struck by their finding that among the past decade’s FOMC members, Powell has moved the furthest away from NAIRU and the rest of it. If nothing else, it vindicates some of my own kind words about him in the runup to his reappointment.2

This is also, finally, an example of what empirical work in economics ought to look like.3 First, it’s frankly descriptive. Second, it asks a question which has a quantitative answer, with substantively interesting variation (across both time and FOMC members, in this case.) As Deirdre McCloskey stressed in her wonderful pamphlet The Secret Sins of Economics, the difference between answers with quantitative and qualitative answers is the difference between progressive social science and … whatever economics is.

What kind of theory would actually contribute to an … inquiry into the world? Obviously, it would be the kind of theory for which actual numbers can conceivably be assigned. If Force equals Mass times Acceleration then you have a potentially quantitative insight into the flight of cannon balls, say. But the qualitative theorems (explicitly advocated in Samuelson’s great work of 1947, and thenceforth proliferating endlessly in the professional journals of academic economics) don’t have any place for actual numbers.

A qualitative question, in empirical work, is a question of the form “are these statistical results consistent or inconsistent with this theoretical claim?” The answer is yes, or no. The specific numbers — coefficients, p-values, and of course the tables of descriptive statistics people rush through on their way to the good stuff — are not important or even meaningful. All that matters is whether the null has been rejected.

McCloskey, insists, correctly in my view, that this kind of work adds nothing to the stock of human knowledge. And I am sorry to say that it is just as common in heterodox work as in the mainstream.

To add to our knowledge of the world, empirical work must, to begin with, tell you something you didn’t know before you did it. “Successfully” confirming your hypothesis obviously fails this test. You already believed it! It also must yield particular factual claims that other people can make use of. In general, this means some number — it means answer a “how much” question and not jsut a “yes or no” question. And it needs to reveal variation in those quantities along some interesting dimension. Since there are no universal constants to uncover in social science, interesting results will always be about how something is bigger, or more important in one time, one country, one industry, etc. than in another. Which means, of course, that the object of any kind of empirical work should be a concrete historical development, something that happened at a specific time and place.

One sign of good empirical work is that there are lots of incidental facts that are revealed along the way, besides the central claim. As Andrew Gelman observed somewhere, in a good visualization, the observations that depart from the relationship you’re illustrating should be as informative as the ones that fit it.

This paper delivers that. Along with the big question of a long term shift, or not, in the Fed’s thinking, you can see other variation that may or may be relevant to the larger question but are interesting facts about the world in their own right. If, for example, you look at the specific examples of language they coded in each category, then a figure like shows lots of interesting fine-grained variation over time.

Also, in passing, I appreciate the fact that they coded the terms themselves and didn’t outsource the job to ChatGPT. I’ve seen a couple papers doing quantitative analysis of text, that use chatbots to classify it. I really hope that does not become the norm!

Anyway, it’s a great paper, which I highly recommend, both for its content and as a model for what useful empirical work in economics should look like.

 

At Barron’s: Thank Full Employment, Not AI, for Rising Productivity

(I write a monthly opinion piece for Barron’s. This one was published there in September. My previous pieces are here.)

New data about productivity are some of the best on record in recent years. That’s good news for economic growth. But just as important, it offers support for the unorthodox idea that demand shapes the economy’s productive potential. Taking this idea seriously would require us to rethink much conventional wisdom on macroeconomic policy. 

Real output per hour grew 2.6% in 2023, according to the Bureau of Labor Statistics, exceeding the highest rates seen between 2010 and the eve of the pandemic. That said, productivity is one of the most challenging macroeconomic outcomes to measure. It is constructed from three distinct series—nominal output, prices, and employment. Short-term movements often turn out to be noise. It’s an open question whether that high rate will be sustained. But if it is, that will tell us something important about economic growth. 

Discussions of productivity growth tend to treat it as the result of unpredictable scientific breakthroughs and new technologies, whose appearance has nothing to do with current economic conditions. This view of technological change as “exogenous,” in the jargon, is entrenched in economics textbooks. And it’s reinforced by the self-mythologizing barons of Silicon Valley, who are only too happy to take credit for economic good news. 

The economic conditions that lead companies to actually adopt new technologies get much less attention, as does the fact that much productivity growth comes from people shifting from lower-value to higher-value activities without the need for any new technology at all.

A recent New York Times article is typical. It discusses faster productivity growth almost entirely in terms of the new technologies — AI, Zoom, internet shopping — that might, or might not, be contributing. Not until 40 paragraphs in is there a brief mention of the strong labor market, and the incentives that rising wages create to squeeze more out of each hour of labor.

What if we didn’t treat this as an afterthought? There’s a case to be made that demand is, in fact, a central factor in productivity growth. 

The economic historian Gavin Wright has made this case for both the 1990s — our modern benchmarks for productivity success stories — and the 1920s, an earlier period of rapid productivity growth and technological change. Wright considers the adoption of general-purpose technologies: electricity in the ‘20s and computers in the ‘90s. Both had existed for some time but weren’t widely adopted until rising labor costs provided the right incentives. He observes that in both periods strong wage growth started before productivity accelerated. 

In the retail sector, for instance, it was in the 1990s that IT applications like electronic monitoring of shelf levels, barcode scanning and electronic payments came into general use. None of these technologies were new at the time; what had changed was the tight market for retail employment that made automation worthwhile.

The idea that demand can have lasting effects on the economy’s productive potential – what economists call hysteresis — has gotten attention in recent years. Discussions of hysteresis tend to focus on labor supply — people dropping out of the labor market when jobs are scarce, and re-entering when conditions improve. The effect of demand on productivity is less often discussed. But it may be even more important.

After the 2007-2009 recession, gross domestic product in the U.S. (and most other rich countries) failed to return to its pre-recession trend. By 2017, a decade after the recession began, real GDP was a full 10% below what prerecession forecasters had expected. There is wide agreement that much, if not all, of this shortfall was the result of the collapse of demand in the recession. Former Treasury Secretary Larry Summers at the time called the decisive role of demand in the slow growth of the 2010s a matter of “elementary signal identification.” 

Why did growth fall short? If you look at the CBO’s last economic forecasts before the recession, the agency was predicting 6% growth in employment between 2007 and 2017. And as it turned out, over those ten years, employment grew by exactly 6%. The entire gap between actual GDP and the CBO’s pre-recession forecasts was from slower growth in output per worker. In other words, this shortfall was entirely due to lower productivity. 

If you believe that slow growth in the 2010s was largely due to the lingering effects of the recession — and I agree with Summers that the evidence is overwhelming on this point — then what we saw in that decade was weak demand holding back productivity. And if depressed demand can slow down productivity growth, then, logically, we would expect strong demand to speed it up.

A few economists have consistently made the case for this link. Followers of John Maynard Keynes often emphasize this link under the name “Verdoorn’s law.” The law, as Keynesian economist Matias Vernengo puts it in a new article, holds that “technical change is the result, and not the fundamental cause of economic growth.” Steve Fazzari, another Keynesian economist, has explored this idea in several recent papers. But for the most part, mainstream economists have yet to embrace it. 

This perspective does occasionally make it into the world of policy debates. In a 2017 report, Josh Bivens of the Economic Policy Institute argued that “low rates of unemployment and rapid wage growth would likely induce faster productivity growth.” Skanda Amarnath and his colleagues at Employ America have made similar arguments. In a 2017 report for the Roosevelt Institute, I discussed a long list of mechanisms linking demand to productivity growth, as well as evidence that this was what explained slower growth since the recession.

If you take these sorts of arguments seriously, the recent acceleration in productivity should not be a surprise. And we don’t need to go looking for some tech startup to thank for it. It’s the natural result of a sustained period of tight labor markets and rising wages.

There are many good reasons for productivity growth to be faster in a tight labor market, as I discussed in the Roosevelt report. Businesses have a stronger incentive to adopt less labor-intensive techniques, and they are more likely to invest when they are running at full capacity. Higher-productivity firms can outbid lower-productivity ones for scarce workers. New firms are easier to start in a boom than in a slump.

When you think about it, it’s strange that concepts like Verdoorn’s law are not part of the economics mainstream. Shouldn’t they be common sense?

Nonetheless, the opposite view underlies much of policymaking, particularly at the Federal Reserve. At his most recent press conference, Fed Chair Jay Powell was asked whether he still thought that wage growth was too high for price stability. Powell confirmed that, indeed, he thought that wage gains were still excessively strong. But, he said, they were gradually moving back to levels “associated — given assumptions about productivity growth — with 2% inflation.”

The Fed’s view that price stability requires limiting workers’ bargaining power is a long-standing problem. But focus now on those assumptions. Taking productivity growth as given, unaffected by policy, risks making the Fed’s pessimism self-confirming. (This is something that Fed economists have worried about in the past.) If the Fed succeeds in getting wages down to the level consistent with the relatively slow productivity growth it expects, that itself may be what stops us from getting the faster productivity growth that the economy is capable of.

The good news is that, as I’ve written here before, the Fed is not all-powerful. The current round of rate hikes has not, so far, done much to cool off the labor market. If that continues to be the case, then we may be in for a period of sustained productivity growth and rising income.

At Jacobin: Review of Beth Popp Berman’s Thinking Like an Economist

(This review appeared in the Summer 2022 edition of Jacobin.)

After the passage of Medicare and Medicaid, universal health insurance seemed to be on its way. In 1971, the New York Times observed that “Americans from all strata of society … are swinging over to the idea that good health care, like good education, ought to be a fundamental right of citizenship.” That same year, Ted Kennedy introduced a bill providing universal coverage with no payments at the point of service, on the grounds that “health care for all our people must now be recognized as a right.” The bill didn’t pass, but it laid down a marker for future health care reform.

But when Democratic presidents and congresses took up health care in later years they chose a different path. Rather than pitching health care as a right of citizenship, the goal was better-functioning markets for health care as a commodity. From the “consumer choice health plan” proposed by Alain Enthoven in the Carter administration, though the 1993 Clinton plan down to Obama’s ACA, the goal of reform was no longer the universal provision of health care, but addressing certain specific failures in the market for health insurance.

The intellectual roots of this shift are the subject of Beth Popp Berman’s new book Thinking Like an Economist: How Efficiency Replaced Equity in U.S. Public Policy. A distinct style of thinking, she argues, reshaped ideas how about how government should work and what it could achieve. This “economic style” of thinking, originating among Democrats rather than on the Right, “centered efficiency and cost-effectiveness, choice and incentives, and competition and the market mechanism… Its implicit theory of politics imagined that disinterested technocrats could make reasonably neutral, apolitical policy decisions.” Rather than see particular domains of public life, like health care or the environment, as embodying their own distinct goals and logics, they were imagined in terms of an idealized market, where the question was what specific market failure, if any, the government should correct.

The book traces this evolution in various policy domains, focusing on the microeconomic questions of regulation, social provision and market governance rather than the higher-profile debates among macroeconomists. Covering mainly the period of the Kennedy through Reagan administrations, with brief discussions of more recent developments, the book documents how the economic style of reasoning displaced alternative ways of thinking about policy questions. The first generation of environmental regulation, for example, favored high, inflexible standards such as simply forbidding emission of certain substances. Workplace and consumer safety laws similarly favored categorical prohibitions and requirements.

But to regulators trained in economics, this made no sense. To an economist, “the optimal level of air pollution, worker illness, or car accidents might be lower than its current level, but it was probably not zero.” As economist Marc Roberts wrote with frustration of the Clean Water Act, “There is no be no case-by-case balancing of costs and benefits, no attempt at ‘fine-tuning’ the process of resource allocation.’”

The book has aroused hostility from economists, who insist that this is an unfairly one-sided portrayal of their profession. I think Berman has the better of the argument here. As anyone who has taken an economics course in college can confirm, there really is such a thing as “thinking like an economist,” even if not every economist thinks that way. Framing every question as a problem of optimization under constraints is a very particular style of reasoning. And, as Berman observes, the most important site of this thinking is not the work of professional economists with their “frontier research,” but undergraduate classes and in schools of public policy where those in government, non-profits, and the press acquire this perspective.

Berman also is right to link this distinctive economic style of reasoning to a narrowing of American political horizons. At the same time, she is appropriately cautious about attributing too much independent influence to it — ideas matter, she suggests, but as tools of power rather than sources of it.

The problem with the book is not that she is unfair to economists; it’s that she concedes too much ground to them. Thinking Like an Economist is attentive to the shifting backgrounds of leaders and staff in federal agencies — if you’re wondering who was the first economics PhD to head the Justice Department’s Antitrust Division, this is the book for you. But this institutional history, while important, sometimes crowds out critical engagement with the ideas being discussed.

Take the term efficiency, which seems to occur on almost every page of the book, starting with the cover. The essence of the economic style, says Berman, is that government should make decisions “to promote efficiency.” But what does that mean?

We know what “efficient” means as applied to, say, a refrigerator. It means comparing a measurable input (electricity, in this case) to a well-defined outcome (a given volume maintained at a given temperature). There is nothing distinct to economics in preferring a more energy-efficient to a less energy-efficient appliance. Unions planning organizing campaigns, socialists running in elections, or public housing administrators all similarly face the problem of getting the most out of their scarce resources.

But what if the question is whether you should have a refrigerator in the first place, or if refrigerators ought to be privately owned? What could “efficient” mean here?

To an economist, the answer is the one that maximizes “utility” or “welfare.” These things, of course, are unobservable. So the measurement of inputs and output that defines efficiency in the every day sense is impossible.

Instead, what we do is start with an abstract model in which all choices involve using or trading property claims, and people know and care about only their own private interests. Then we show that in this model, exchange at market prices will satisfy a particular definition of efficiency — either Pareto, where no one can get a better outcome without someone else getting a worse one, or Kaldor-Hicks, where improvements to one person’s situation at the expense of another’s are allowed as long as the winners could, in principle, make the losers whole. Finally, in a sort of argument by homonym, this specialized and near-tautological meaning of “efficiency” is imported back into real-world settings, where it is used interchangeably with the everyday doing-more-with-less one.

When someone steeped in the economic style of thinking says “efficiency,” they mean something quite different from what normal people would. Rather than a favorable ratio of measurable out- puts to inputs, they mean a desirable outcome in terms of unmeasurable welfare or utility, which is simply assumed to be reached via markets. A great part of the power of economics in policy debates comes through the conflation of these two meanings. A common-sensical wish to get better outcomes with less resources gets turned into a universal rule that economic life should be organized around private property and private exchange.

Berman is well aware of the ambiguities of her key term, and the book contains some good discussions of these different meanings. But that understanding seldom makes it into the primary narrative of the book, where economists are allowed to pose as advocates of an undifferentiated “efficiency,” as opposed to non-economic social and political values. This forces Berman into the position of arguing that making government programs work well is in conflict with making them fair, when in reality an ideological preference for markets is often in conflict with both.

To be sure, there are cases where Berman’s frame works. Health care as a right is fundamentally different from a good that should be delivered efficiently, by whatever meaning. But in other cases, it leads her seriously astray. There are many things to criticize in the United States’ thread- bare welfare state. But is one of them really that it focuses too much on raising recipients’ in- comes, as opposed to relieving their “feelings of anomie and alienation”? Or again, there are many reasons to prefer 1960s and ‘70s style environmental regulation, with simple categorical rules, to the more recent focus on incentives and flexibility. But I am not sure that “the sacredness of Mother Earth” is the most convincing one.

That last phrase is Berman’s, from the introduction. It’s noteworthy that in her long and informative chapter on environmental regulation, we never hear the case for strong, inflexible standards being made in such terms. Rather, the first generation of regulators “built ambitious and relatively rigid rules … because they saw inflexibility as a tool for preventing capture” by industry, and because they believed that “setting high, even seemingly unrealistic standards … could drive rapid improvements” in technology. Meanwhile, their economics-influenced opponents like Charles Schultze (a leading economist in the Johnson and Carter administrations, and a central figure in the book) and Carter EPA appointee Bill Drayton, seem to have been motivated less by measurable policy outcomes than by objections on principle to “command and control” regulation. As one colleague described Drayton’s belief that companies should be allowed to offset emissions at one plant with reductions elsewhere, “What was driving Bill was pure intellectual conviction that this was a truly elegant approach — The Right Approach, with a capital ’T’ and ‘R’.” This does not look like a conflict between the values of equity and efficiency. It looks like a conflict between the goal of making regulation effective on one side, versus a preference for markets as such on the other.

On anti-trust regulation, the subject of another chapter in the book, the efficiency-versus-equity frame also obscures more than it reveals. The fundamental shift here was, as Berman says, away from a concern with size or market share, toward a narrower focus on horizontal agreements between competitors. And it is true that this shift was sometimes justified in terms of the supposed greater efficiency of dominant firms. But we shouldn’t take this justification at face value. As critical anti-trust scholars like Sanjukta Paul have shown, courts were not really interested in evidence for (or against) such efficiency. Rather, the guiding principle was a preference for top-down coordination by owners over other forms of economic coordination. This is why centralized price-setting by Amazon is acceptable, but an effort to bargain jointly with it by publishers was unacceptable; or why manufacturers’ prohibitions on resale of their products were accept- able but the American Medical Association’s limits on advertising by physicians was unacceptable. The issue here is not efficiency versus equity, or even centralized versus decentralized economic decision making. It’s about what kind of authority can be exercised in the economic sphere.

Berman ends the book with the suggestion that rebuilding the public sector calls for rethinking the language in which policies are understood and evaluated. On this, I fully agree. Readers who were politically active in the 2000s may recall the enormous mobilizations against George W. Bush’s proposals for Social Security privatization — and the failure, after those were abandoned, to translate this defensive program into a positive case for expanding social insurance. More recently, we’ve seen heroic labor actions by public teachers across the country. But while these have sometimes succeeded in their immediate goals, they haven’t translated into a broader argument for the value of public services and civil service protections.

As Berman says, it’s not enough to make the case for particular public programs; what we need is better language to make the positive case for the public sector in general.

At Age of Economics: How Should an Economist Be?

The website Age of Economics has been carrying out a series of interviews with economists about what the purpose of the discipline it is, and what its relationship is to capitalism as a historical social system. I believe there will be 52 of these interviews, one each week over the course of 2021. Earlier this spring, they interviewed Arjun Jayadev and myself. You can watch video of the interview here. I’ve pasted the transcript below.

 

Q: Why does economics matter?

JWM: The most obvious way that economics matters is that it has an enormous prestige in our society. Economists have a level of respect and authority that no other social scientist, arguably no other academic discipline possesses. An enormous number of policy debates are conducted in the language of economics. There’s an ability of an economist to speak directly in policy settings, in political settings in a way that most academics simply can’t. And so Joan Robinson has that famous line that the reason you study economics is to avoid being fooled by economists.

And there’s some truth to that. Even if you think that the discipline is completely vacuous, it’s worth learning its language and techniques just in order to be able to at least criticize the arguments that other economists are making. But I would say we don’t think that economics is completely worthless and vacuous because we think it does bring some positive ways of thinking to the larger conversation. One thing that is defining of economics is the insistence on formalizing ideas, expressing your thoughts in some highly abstract way, either as a system of equations or a system of diagrams in a way where you’re explicitly stating all of the causal relationships that you think exist in the story that you’re trying to tell.

And that’s a useful habit of thinking that is not necessarily as widespread outside the economics profession. Sometimes you can learn new things just by writing down your assumptions and working through them. The whole debate in the heterodox field about wage led growth versus profit led growth, what are the circumstances where redistribution from profits to wages is likely to boost demand? And what are the situations where it’s likely to reduce demand? There are real insights that come out of trying to write down your vision of the economy as a system of equations.

The notion of balance of payments-constrained growth, where we think that maybe for a lot of countries, the thing that’s fundamentally driving the rate of growth that they can sustain is how responsive, how income-elastic, their exports are versus their imports is another set of ideas that comes out of writing down a formal model in the first case.

So this is a useful discipline that training as an economist gives you, that people with other kinds of backgrounds don’t have. This effort to make explicit the causal connections that you have in mind.

AJ:  It’s also important to realize that economics has come up with some very useful concepts, to make sense of this world around us: concepts like GDP or employment. These are concepts which are well defined and measured, and help us to have an understanding of the system as a whole.

Admittedly, lots of economics education doesn’t pay as much attention to this side of economics as it should. And maybe the question was an implicit critique — when you ask why does economics matter, there are some people who feel that it doesn’t matter because of what’s happened to the discipline. Josh and I both like this particular quote by the economist Trygve Haavelmo. He said that the reason that you learn economics is to – I believe the phrase is – “to be a master of the happenings of real life”.

And that that’s why one should be doing economics, not as an exercise in and of itself, but to understand what’s happening in the world.

JWM: That’s right. The real secret to doing good economics is to start from somewhere other than economics. You may come into economics with a set of political commitments as Arjun and I both did, but you may also come in with a desire to make money in the business world and you’re associating with people who do that, or you come in because you’re focused on a particular set of public debates that you want to clarify your thinking about. If you come in with some other set of concerns that are going to guide you in terms of what’s important, what’s relevant, what’s reasonable, then you’ll find a lot of useful tools within economics.

The problem arises with people – and, unfortunately, this I’d say is the majority of professional economists – who don’t have any independent intellectual or personal base, their intellectual development is entirely within academic economics. And then it becomes very easy to lose sight of the happenings of real life that this field is supposed to be illuminating.

Q: What are the differences between economic science (academic economics) and economic engineering (policymaking)?

JWM: Today there’s a very wide gap between academic economics and what we might call policy economics, particularly in macro. If you’re a labor economist, maybe the terms that are used in academic studies and the terms that are used in policy debates might be might be closer to each other. But there’s a long standing divide between the questions that academic macroeconomists ask and the questions that come in policy debates which has gotten much wider since the crisis.

The unfortunate fact – and people are going to say this is not fair, but I can tell you, I’ve looked at qualifying exams, recent ones from graduate programs in macroeconomics, and this is a fair characterization, what I’m about to say – that the way academic macroeconomics trains people to think is to imagine a representative agent with perfect knowledge of the probabilities of all future events, who is then choosing the best possible outcome for them in terms of maximizing utility over infinite future time under a given set of constraints. That is literally what you are trained to think about if you are getting an academic training in macroeconomics. For people who are not economists listening to this, you have to study this stuff to understand how weird it is.

Unfortunately that aspect of the profession has not changed very much since the financial crisis of a decade ago. On the other hand, the public debate on macroeconomic questions has moved a lot. So there’s a much wider range of perspectives if you look at people in the policy world or the financial press or even in the business world. So in some ways the public debate has gotten much better over the past decade, but that’s widening the gap between the public debate and academic macroeconomics. I don’t know how exactly this will come about, but at some point we’re going to have to essentially throw out the existing graduate macroeconomics curriculum and start fresh, roll back the clock to 1979 or start from somewhere else, because it does seem like the dominant approach in academic macroeconomics is an intellectual dead end.

AJ: We have friends who are doing a lot of good work in labor economics. People like Arin Dube at UMass Amherst, which is one of these places which takes these things seriously, or my colleague Amit Basole where I am at Azim Premji University. And in some fields there is back and forth between the world that exists and policymaking and the craft of economics and academic economics.

It requires also talking to people from outside the discipline to see how far academic economics and macroeconomics has drifted away from policymaking. And this is why I come back to the Haavalmo point. The reason for us to be doing many of the things we are doing is academic macroeconomist is to try to see if we can have an effect on the world, understand the world. And this distinction has become so sharp right now to make it dysfunctional.

Now, the additional problem that comes with it is that because this kind of theory is hard, it’s complex and it’s weird, people spend a lot of time invested in this activity. When I say this activity, I mean basically solving equations, but for some imaginary state. That’s not only limited to macro, but it’s the worst in macro. And as a result, it becomes very hard for people to pull away from that, and say that there’s something wrong. The emperor’s new clothes moment is extremely painful to face.

But it is interesting that one of the advantages of studying macroeconomics is there are always people who want to understand what’s happening in the world. And what you might call concrete policy macroeconomics has got much more open, much more interesting than in the past. There’s an economic science aspect in concrete policy macroeconomics. I wouldn’t want to separate them so sharply as you might have done in the question.

JWM: And to be fair, there are plenty of prominent mainstream macroeconomists who have a lot of interesting and insightful things to say about real economies. The thing is that when they’re talking about the real world, they ignore what they do in their scholarly work. They’re smart enough and they’ve got time and energy that they can they can follow both tracks at once, but they’re still two separate tracks.

But for most people, that’s not practical. And if you get sucked into the theory, then you stop thinking about the real questions. And the other thing, just to be fair, is that in the world of empirical macroeconomics, there’s more interesting work being done. The problem is that there isn’t a body of theory that the empirical work can link up with.

Q: What role does economics play in society? Does it serve the common good?

JWM: You can certainly criticize economists for being ideological. There are very specific assumptions about how the world works that are baked into the theory in a way that is not even visible to the people who are educated in that theory.

But it’s almost impossible to imagine a non-ideological economics. In principle we could study the economy scientifically in the way we study other areas of existence scientifically. But we can’t do it as long as we live in a capitalist economy because the questions are too close to the basic structures of authority and hierarchy of our society. They are too close to the ways that all the inequalities, all the sources of power in our society are legitimated.

They can’t just be scrutinised in a neutral way from the outside. So as long as we live under capitalism, we are never going to have an established scientific study of capitalism. That’s just not possible. In a way, you could even say that the function of a lot of academic economics is not so much to instill a particular ideological view of capitalism, but just to stop people from thinking about it systematically at all. It gives you something else to think about instead.

That doesn’t mean that on an individual level we should not aspire to be scientific in a broad sense in our approach. We should expose our ideas to critical scrutiny. We should systematically consider alternatives and formulate hypotheses and see if the world is giving us reason to think our hypotheses are right or wrong. we should follow that.

But we should also recognize that you’re going to be on the margins as you do this. That’s OK, because the life of a professional economist is pretty good. So the margins of the profession is still a perfectly fine place to be. But that’s where you’re going to be. Or occasionally in moments of deep crisis, when the survival of the system is at stake, then there will be periods where a more rational perspective on it is tolerated.

But the notion that we’re going to persuade people in the economics profession that we have a better set of ideas and we’re going to win out that way, it misses that there is a deep political reason why economics is the way it is. So again, as we were saying at the beginning, if you want to do good scientific work, you have to have a foot outside the profession to give you a base somewhere else.

Hayek is probably not somebody that neither of us agrees with on very much, but he has a nice line about this, he says, “no one can be a great economist who is only an economist.” And that’s very true.

AJ: The question reminds me of the famous story about Keynes when he finishes being the editor of the Economic Journal, where he raises a toast to the economists who are the trustees of the possibility of civilization. There’s a belief among economists that  they are standing apart and guiding the forces of history.

Well, that sounds a little pompous. Keynes could get away with it. Nowadays we wouldn’t say that, but we’d say that we maximizing social welfare, which is in some ways the same thing. One of the things that you ask is, is it serving the common good? One of the things that economics does in its training is posit a common good. And that immediately takes you away from the space of politics. Because there are many situations in the economy in which there are conflicts of interest.

These are not just conflicts of opinions. It’s conflicts around things like the distribution of income and so on. And these questions become unavoidably political. It’s pulling away from that, which, by the way, the Classical economists never did, that allows you to talk about something abstract like social welfare. So I would say the economics can play a role in trying to understand what we would want to have from a democratic, open, egalitarian society. But positing something like the common good can sometimes obscure that.

Q: Economics provides answers to problems related to markets, efficiency, profits, consumption and economic growth. Does economics do a good job in addressing the other issues people care about: climate change and the wider environment, the role of technology in society, issues of race and class, pandemics, etc.?

JWM: We might turn this question around a little bit. Economics does best when it’s focused on urgent questions like climate change. We do better economics when we’re oriented towards towards real urgent live political questions like around race and class. This is what we’re saying: Economics when it’s focused on questions of markets and efficiency in the abstract, doesn’t contribute very much to the conversation. It quickly loses contact with the real phenomena that it’s supposed to be dealing with.

And what focuses our attention is precisely that second set of questions that you raise. Those are the questions that create enough urgency to force people to adopt a more realistic economics. So in that sense, we do a better job talking about markets, we give a better, more useful definition of things like efficiency when we’re focused on concrete questions like climate change. There’s a good reason that modern macroeconomics begins with the Great Depression, because this is a moment when you do need to look at the economy as it is.

Today, it’s obvious that the existing models aren’t working, and there’s a political urgency to coming up with a better set of stories, a better set of tools. The climate crisis has a good chance to be a similar clarifying moment as the 1930s, more so than the financial crisis of a decade ago or whatever the next financial crisis is.

Climate change may force us to rethink some of our broader economic ideas in a more fundamental way. The truth is established economic theory does not give good answers in general to the problems of profits, economic growth and so on. And a focus on climate change can improve the field in that way.

The other thing you bring up is race, class, and gender. The problem here is that nobody has a God’s eye view of the world. Nobody can step out of their own skin and see things from a perfectly objective view. As a middle class white man in the United States, I have a particular way of looking at the world, which is in some ways a limiting one. Economics as a field would be better if we had more diversity, a broader range of backgrounds and perspectives.

AJ: I’d like to add, there is no reason why a particular set of tools that you use in one sphere should automatically be something that you can use in another sphere. The way that modern economics is set up is just a set of maximization problems, it allows people to seamlessly say that they are studying on the one hand buying oranges and apples, and on the other side solving the problems of climate change.

So there is an issue in the way that you posit, that  it is using tools which it may be – I agree with Josh, it’s not very good at – but it may be better than its applications in other spheres. A famous example is the choice of discount rate for climate change. And that’s been such a long-standing disaster in the amount of time we’ve spent to think about this particular issue for which that analysis is completely inappropriate.

So, yes, there are places when it may be more appropriate, but maybe it’s not even very appropriate in those spheres. I would agree with Josh that this current moment and other moments of crisis – you mentioned 2008 – has opened up the space to think much more carefully about specific issues. And when you have a crisis that confronts you, it forces you to come up with a different economics or use other traditions of economics which have better answers than the ones that are there presently.

Q: As we live in an age of economics and economists – in which economic developments feature prominently in our lives and economists have major influence over a wide range of policy and people – should economists be held accountable for their advice?

JWM: As Arjun was saying earlier, this question is almost giving economics as a field too much credit, in the sense that it suggests that a lot of economic outcomes are directly dependent on the advice given by economists. Economics, as we’ve said, has an enormous prestige in terms of the presence of economists in all sorts of public debates. But a lot of times if you look at how views change, it’s not the economists who are leading the way. It’s the politicians or the broader public who’ve shifted. And then the economist come in to justify this after the fact.

There’s a certain sense, as a concrete example, where a lot of the development in macroeconomic theory over the past generation has been an after-the-fact effort to justify the policies that central banks were already following. Like a way of demonstrating that what central banks were already doing in terms of inflation target, using something like the Taylor Rule was the socially optimal thing. And that generalizes pretty widely.

So I’m not sure that we should be blaming or crediting economists for policy outcomes that they probably do more to legitimate or help with the execution of than to shift. The other reason I don’t personally see this as a particularly productive direction to go in is: who’s going to impose the accountability, who’s going to step in and say, all right, you were wrong and that had consequences and now you’re going to pay a penalty.

There’s no consensus position from which to do that. So we all just have to go on making our arguments the best we can and we’re not going to reach agreement. And so we try to shift the debate our way and somebody else shifts it their way, and there’s never going to be an impartial referee who’s going to come in and say that one side was right and the other was wrong.

AJ: Having been practicing economist for 10-15 years, broadly one has to realize that whatever you say and whatever you think and whatever you do, is strictly circumscribed by what the world is open to at that point of time. That’s something that’s sometimes hard for us to accept. There are many people who for years made the argument that we shouldn’t be so concerned about supply constraints, and it was only after 2012, 13, 14, 15- when the world started to move away from austerity or the costs of austerity became well known, that space was made for these arguments. And it’s always like that.

Spaces are there in some moments and not in other moments. And there are those people who for whatever reason in some universities, in some spaces, seem to capture elite opinion. They’re the ones who you see again and again and again. It doesn’t matter if they’re right or wrong, they’re the ones who are opinion makers.

I don’t think this is distinct from any other kind of marketing. There are always going to be a few people who are opinion and market leaders. Having said that, it would be good to have a list of when people were wrong. And sometimes it would be good to take people down a peg or two.

But again, I don’t think it’s an important thing. I don’t think that we should necessarily valorise economics and economists one way or the other.

6. Does economics explain Capitalism? How would you define Capitalism?

AJ: If you want to think about capitalism as a system, you need to go back to Karl Marx. You don’t have to call yourself a Marxist, but if you want to think about the questions like the ones that you just posed, you have to take him very seriously because his work is the foundation of many of the ways that we think about capitalism. Josh and I are working on a book and we take up this question about what capitalism means, and in our minds it has a clear definition. It has three elements, or three phases.

The first is the conversion of all kinds of human activities and their products into commodities, this thing that you buy and sell, this alienated thing that is sold in markets. That’s the first. The second is the endless accumulation of money as an end to itself. That’s the drive of the system, which seems to be out of human control. And then finally, something which is very critical and which gives it some of its emotional heft, there is the hierarchy in the workplace where people work under the authority of the boss.

All three of these elements are there historically. But their fusion in this incredibly changeable system that we’ve had for 200 years, that has been unique. That’s the central aspect that we want to focus on, the combination of these three things. And it’s the fact that when combined it gives you this dynamism, this ability to transform society, in far reaching ways that seem out of human control. That’s what I would say capitalism is.

JWM: I agree, that’s the correct definition of capitalism as a system. The problem comes when you try to pull out one of those elements in isolation and think that’s what defines the system. It’s the fusion of the three of them.

The other piece, which maybe isn’t quite as defining but historically has been very important, is that the process of endless accumulation has this moment in the middle of it where money is tied up, locked up in long-lived means of production, that you’re not just buying commodity, working it up and then selling it again, but you’ve got machines, you’ve got buildings, you’ve got technology.

So there’s this long gap between the outlay and the final sale. And that’s one of the things that has made this a system that is dynamic and has transformed human productive capacities in ways that we would agree with Marx’s judgment that in the long run, expand the space for human freedom and possibilities because it’s broken up the old, local, simple ways of carrying out productive activity and allowed people to have a much more extensive division of labor, much wider scale cooperation and the development of all of these new ways of transforming the world through technology that didn’t exist before or that were much – let’s not say it didn’t exist, but developed much more slowly in limited ways before.

But this is also where a lot of the conflict comes up, because you build up a business and it exists for its own purposes, it has its own norms, it has its own internal logic. And then at some point, you have to turn the products of that back into money to keep the accumulation process going. And so a lot of the tensions around the system come from that.

The other part of your question is, can economics explain capitalism. From our point of view economics is part of the larger set of social phenomena that grow out of the generalisation of capitalism as a way of organizing human life and productive activity. In that sense, you can’t use the tools of economics to explain capitalism, because economics is within capitalism. The categories of economics are specific to capitalism. If you want to explain the origins of it, you need a different set of tools. It’s a historical question rather than one that you can answer with the tools of economics.

Q: Is Capitalism, or whatever we should call the current system, the best one to serve the needs of humanity, or can we imagine another one?

JWM: We don’t have to imagine other systems, they’re all around us. As Arjun was saying earlier, we all of us experience every day systems where productive activity is organized through some collective decision making process. An enormous amount of our productive work, our reproductive labor that keeps us going individually and collectively, is carried out in the family. Some families are more egalitarian, some families are more hierarchical, but no family is organized on the basis of the pursuit of profit – well, let’s not say none, but a trivially small fraction of them are.

So we all have firsthand experience that this is a way that we can organize our activity. We all know that within the workplace you personally don’t make decisions based on some profit maximizing criteria. And your immediate boss isn’t doing it that way either. Probably they’re just following orders and some bureaucratic system, or perhaps there’s an element of voluntary cooperation going on.

But either way, it’s a different way of organizing our activity than the notion of markets and the pursuit of profit. As academics, we’re fortunate enough to have a collective decision making process that covers a lot of the traditional roles of the capitalist employer. We collectively decide on hiring and we collectively organize our work schedules and so on. 

Obviously, very few workers in the world are as fortunate as academics in that way. But the point is that this is a model that exists. It works. Certainly here in the United States, higher education is one of our big industrial success stories. And it’s organized as a bunch of little worker co-ops!

In any workplace, there are moments when people sit down to make a decision together, where people do stuff because that’s just what makes sense and what they’ve agreed to do, as opposed to somebody making a calculation of self-interest. This is what David Graeber in his wonderful book, Debt, talks about as “everyday communism.” Even in the most traditional workplace if somebody says pass me that hammer or can you do some little favor for me, people do it just as a way of cooperating and not because they’ve been ordered to or because they’re calculating that it will pay off for them.

And then we have a huge public sector in the world as well. We have public schools and public libraries and public transit and fire and police services and so on. So we already have an enormous amount of non-capitalist organization of production around us. We don’t have to imagine it.

The challenge intellectually is to generalize from this stuff, to recognize how these principles can be applied more broadly. We don’t have to create something new, but we do have to bring in general principles. For people on the left, or people who support individual public sector programs or individual non- capitalist ways of organizing particular activities, there’s often a tendency to make the argument in terms of that specific activity: well, here’s why we want public schools and we want better funding for our public schools. As opposed to trying to articulate what is the general principle that makes markets and the pursuit of profit a bad way to organize that. What is the general principle that says teachers should have autonomy?

We want less authority of the boss in the classroom. That’s why we have civil service protection, that’s why we have professions, because we want workers to have autonomy. But we need to be able to say why.

We want to move away from the model of proletarian labor where you’re completely under the authority of the boss. We do that in a lot of specific cases already. The intellectual challenge is to generalize that and see how we can apply it more broadly to the areas of society where it’s not not currently organized that way.

AJ: The question is nicely posed, because most people would broadly agree that capitalism generates a lot of good. But there’s been a sense right from the beginning that it may not be serving the needs of humanity. That the only word that describes this is a drive, an alien drive which sometimes intersects with the need of human beings and very often doesn’t.

When we think about  what happens in farms, for example, and how so many people spend their entire lives working as drones, it’s very tragic history.  Yes, people are richer and healthier as well. But capitalism, the way that it’s developed, has not served the needs of humanity. 

We don’t have to look historically. Let’s look at what’s happening right now with vaccination. The belief that you needed intellectual property and you can only solve this by the genius of a few pharmaceutical companies when in fact, what happened in all of this innovation was that it was the public sector backing all of this, which made certainly some of the vaccines even viable in the first place. And so now you have this perverse situation where some people are prevented from access because we want to maintain whatever capitalist institutions that we’ve built up.

So it’s important to realize that capitalism, while it’s done many great things as Marx and others recognized, it’s never been a force which has very nicely dovetailed with human needs. But that what’s useful now to think about is, as Josh said, we don’t need to imagine an alternative – we have a model and a system that’s already there, that we’re going to replace it with.

This thing will happen incrementally. Maybe this is radical optimism, but we both believe that the domain organized around these arbitrary hierarchies – the market and so on, is shrinking. Maybe in the next few generations with the challenge of climate change, with more crises and with a truly global world, the responses to those will mean that the domain of collective freedom will be much greater in the future than now.

And the domain of capitalism will be smaller. 

JWM:  I want to amplify something Arjun just said — the vaccine is a perfect example of this dynamic. On the one hand, we have a urgent collective problem, this pandemic. And the solution is directed by the public. It’s a collective decision mediated by governments to devote our common resources to solving this problem.

And it’s incredibly effective when you want to solve this problem and you have a political decision to do it. You can work wonders. And it’s carried out by scientists who have a whole set of professional norms around the conduct of science, which is precisely in order to suppress market incentives. We don’t want scientists thinking about how to get rich. Now, we do get that because that’s ubiquitous in our society, but the reason we have a whole set of professional norms around science is precisely because we think that this is the activity that people carry out better when they’re insulated from market incentives.

And then we have a centralized public direction to mobilize their activity. But the problem is that the fruits of that still have to be squeezed into this box of private property. Somebody has to have a property right over all this collective labor and public resources in the form of a patent.

And that then limits the value of this work. It makes the success much less than it could have been. We already are seeing that conflict and we’re going to continue seeing it even more so as we deal with problems like the pandemic and climate change and so on.

When we urgently need to solve a problem, we find we do it by suppressing the logic of the market and making decisions collectively. But then as long as we still have this overarching insistence on organizing our claims on each other in the form of property rights, it creates a conflict, it gets in the way of that. And over time, again, just the necessity of solving our urgent problems is going to force us to move away from the private property model and away from the pursuit of profit, and towards more rational collective ways of dealing with the problems that face us.

A new macroeconomics?

UPDATE: The video of this panel is here.

[On Friday, July 2, I am taking part in a panel organized by Economics for Inclusive Prosperity on “A new macroeconomics?” This is my contribution.]

Jón Steinsson wrote up some thoughts about the current state of macroeconomics. He begins:

There is a narrative within our field that macroeconomics has lost its way. While I have some sympathy with this narrative, I think it is a better description of the field 10 years ago than of the field today. Today, macroeconomics is in the process of regaining its footing. Because of this, in my view, the state of macroeconomics is actually better than it has been for quite some time.

I can’t help but be reminded of Olivier Blanchard’s 2008 article on the state of macroeconomics, which opened with a flat assertion that “the state of macro is good.” I am not convinced today’s positive assessment is going to hold up better than that one. 

Where I do agree with Jón is that empirical work in macro is in better shape than theory. But I think theory is in much worse shape than he thinks. The problem is not some particular assumptions. It is the fundamental approach.

We need to be brutally honest: What is taught in today’s graduate programs as macroeconomics is entirely useless for the kinds of questions we are interested in. 

I have in front of me the macro comp from a well-regarded mainstream economics PhD program. The comp starts with the familiar Euler equation with a representative agent maximizing their utility from consumption over an infinite future. Then we introduce various complications — instead of a single good we have a final and intermediate good, we allow firms to have some market power, we introduce random variation in the production technology or markup. The problem at each stage is to find what is the optimal path chosen by the representative household under the new set of constraints.

This is what macroeconomics education looks like in 2021. I submit that it provides no preparation whatsoever for thinking about the substantive questions we are interested in. It’s not that this or that assumption is unrealistic. It is that there is no point of contact between the world of these models and the real economies that we live in.

I don’t think that anyone in this conversation reasons this way when they are thinking about real economic questions. If you are asked how serious inflation is likely to be over the next year, or how much of a constraint public debt is on public spending, or how income distribution is likely to change based on labor market conditions, you will not base your answer on some kind of vaguely analogous questions about a world of rational households optimizing the tradeoff between labor and consumption over an infinite future. You will answer it based on your concrete institutional and historical knowledge of the world we live in today. 

To be sure, once you have come up with a plausible answer to a real world question, you can go back and construct a microfounded model that supports it. But so what? Yes, with some ingenuity you can get a plausible Keynesian multiplier out of a microfounded model. But in terms of what we actually know about real economies, we don’t learn anything from the exercise that the simple Keynesian multiplier didn’t already tell us.

The heterogenous agent models that Jón talks about are to me symptoms of the problem, not signs of progress. You start with a fact about the world that we already knew, that consumption spending is sensitive to current income. Then you backfill a set of microfoundations that lead to that conclusion. The model doesn’t add anything, it just gets you back to your starting point, with a lot of time and effort that you could have been using elsewhere. Why not just start from the existence of a marginal propensity to consume well above zero, and go forward from there?

Then on the other hand, think about what is not included in macroeconomics education at the graduate level. Nothing about national accounting. Nothing about about policy. Nothing about history. Nothing about the concrete institutions that structure real labor and product markets. 

My personal view is that we need to roll back the clock at least 40 years, and throw out the whole existing macroeconomics curriculum. It’s not going to happen tomorrow, of course. But if we want a macroeconomics that can contribute to public debates, that should be what we’re aiming for.

What should we be doing instead? There is no fully-fledged alternative to the mainstream, no heterodox theory that is ready to step in to replace the existing macro curriculum. Still, we don’t have to start from scratch. There are fragments, or building blocks, of a more scientific macroeconomics scattered around. We can find promising approaches in work from earlier generations, work in the margins of the profession, and work being done by people outside of economics, in the policy world, in finance, in other social sciences.  

This work, it seems to me, shares a number of characteristics.

First, it is in close contact with broader public debates. Macroeconomics exists not to study “the economy” in the abstract — there isn’t any such thing — but to help us address concrete problems with the economies that we live in. The questions of what topics are important, what assumptions are reasonable, what considerations are relevant, can only be answered from a perspective outside of theory itself. A useful macroeconomic theory cannot be an axiomatic system developed from first principles. It needs to start with the conversations among policymakers, business people, journalists, and so on, and then generalize and systematize them. 

A corollary of this is that we are looking not for a general model of the economy, but a lot of specialized models for particular questions. 

Second, it has national accounting at its center. Physical scientists spend an enormous amount of time refining and mastering their data collection tools. For macroeconomics, that means the national accounts, along with other sources of macro data. A major part of graduate education in economics should be gaining a deep understanding of existing accounting and data collection practices. If models are going to be relevant for policy or empirical work, they need to be built around the categories of macro data. One of the great vices of today’s macroeconomics is to treat a variable in a model as equivalent to a similarly-named item in the national accounts, even when they are defined quite differently.

Third, this work is fundamentally aggregative. The questions that macroeconomics asks involve aggregate variables like output, inflation, the wage share, the trade balance, etc. No matter how it is derived, the operational content of the theory is a set of causal relationships between these aggregate variables. You can certainly shed light on relationships between aggregates using micro data. But the questions we are asking always need to be posed in terms of observable aggregates. The disdain for “reduced form” models is something we have to rid ourselves of. 

Fourth, it is historical. There are few if any general laws for how “an economy” operates; what there are, are patterns that are more or less consistent over a certain span of time and space. Macroeconomics is also historical in a second sense: It deals with developments that unfold in historical time. (This, among other reasons, is why the intertemporal approach is fundamentally unsuitable.) We need fewer models of “the” business cycle, and more narrative descriptions of individual cycles. This requires a sort of figure-ground reversal in our thinking — instead of seeing concrete developments as case studies or tests of models, we need to see models as embedded in concrete stories. 

Fifth, it is monetary. The economies we live in are organized around money commitments and money flows, and most of the variables we are interested in are defined and measured in terms of money. These facts are not incidental. A model of a hypothetical non-monetary economy is not going to generate reliable intuitions about real economies. Of course it is sometimes useful to adjust money values for inflation, but it’s a bad habit to refer to the result quantities as “real” — it suggests that there is some objective quantity lying behind the monetary one, which is in no way the case.

In my ideal world, a macroeconomics education would proceed like this. First, here are the problems the external world is posing to us — the economic questions being asked by historians, policy makers, the business press. Second, here is the observable data relevant to those questions, here’s how the variables are defined and measured. Third, here are how those observables have evolved in some important historical cases. Fourth, here are some general patterns that seem to hold over a certain range  — and just as important, here is the range where they don’t. Finally, here are some stories that might explain those patterns, that are plausible given what we know about how economic activity is organized.

Well, that’s my vision. Does it have anything to do with a plausible future of macroeconomics?

I certainly don’t expect established macroeconomists to throw out the work they’ve been doing their whole careers. Among younger economists, at least those whose interest in the economy is not strictly professional, I do think there is a fairly widespread recognition that macroeconomic theory is at an intellectual dead end. But the response is usually to do basically atheoretical empirical work, or go into a different field, like labor, where the constraints on theory are not so rigid. Then there is the heterodox community, which I come out of. I think there has been a great deal of interesting and valuable work within heterodox economics, and I’m glad to be associated with it. But as a project to change the views of the rest of the economics profession, it is clearly a failure.

As far as I can see, orthodox macroeconomic theory is basically unchallenged on its home ground. Nonetheless, I am moderately hopeful for the future, for two reasons. 

First, academic macroeconomics has lost much of its hold on public debate. I have a fair amount of contact with policymakers, and in my experience, there is much less deference to mainstream economic theory than there used to be, and much more interest in alternative approaches. Strong deductive claims about the relationships between employment, inflation, wage growth, etc. are no longer taken seriously.

To be sure, there was always a gulf between macroeconomic theory and practical policymaking. But at one time, this could be papered over by a kind of folk wisdom — low unemployment leads to inflation, public deficits lead to higher interest rates, etc. — that both sides could accept. Under the pressure of the extraordinary developments of the past dozen years, the policy conversation has largely abandoned this folk wisdom — which, from my point of view, is real progress. At some point, I think, academic economics will recognize that it has lost contact with the policy conversation, and make a jump to catch up. 

Keynes got a lot of things right, but one thing I think he got wrong was that “practical men are slaves to some defunct economist.” The relationship is more often the other way round. When practical people come to think about economy in new ways, economic theory eventually follows.

I think this is often true even of people who in their day job do theory in the approved style. They don’t think in terms of their models when they are answering real world questions. And this in turn makes our problem easier. We don’t need to create a new body of macroeconomic theory out of whole cloth. We just need to take the implicit models that we already use in conversations like this one, and bring them into scholarship. 

That brings me to my second reason for optimism. Once people realize you don’t have to have microfoundations, that you don’t need to base your models on optimization by anyone, I think they will find that profoundly liberating. If you are wondering about, say, the effect of corporate taxation on productivity growth, there is absolutely no reason you need to model the labor supply decision of the representative household as some kind of intertemporal optimization. You can just, not do that. Whatever the story you’re telling, a simple aggregate relationship will capture it. 

The microfounded approach is not helping people answer the questions they’re interested in. It’s just a hoop they have to jump through if they want other people in the profession to take their work seriously. As Jón suggests, a lot of what people see as essential in theory, is really just sociological conventions within the discipline. These sorts of professional norms can be powerful, but they are also brittle. The strongest prop of the current orthodoxy is that it is the orthodoxy. Once people realize they don’t have to do theory this way, it’s going to open up enormous space for asking substantive questions about the real world. 

I think that once that dam breaks, it is going to sweep away most of what is now taught as macroeconomics. I hope that we’ll see something quite different in its place.  

Once we stop chasing the will-o-wisp of general equilibrium, we can focus on developing a toolkit of models addressed to particular questions. I hope in the years ahead we’ll see a more modest but useful body of theory, one that is oriented to the concrete questions that motivate public debates; that embeds its formal models in a historical narrative; that starts from the economy as we observe it, rather than a set of abstract first principles; that dispenses with utility and other unobservables; and that is ready to learn from historians and other social scientists.

The Wit and Wisdom of Trygve Haavelmo

I was talking some time ago with my friend Enno about Merijn Knibbe’s series of articles on the disconnect between the variables used in economic models and the corresponding variables in the national accounts.4 Enno mentioned Trygve Haavelmo’s 1944 article The Probability Approach in Econometrics; he thought Haavelmo’s distinction between “theroetical variables,” “true variables,” and “observable variables” could be a useful way of thinking about the slippages between economic reality, economic data and economic theory.

I finally picked up the Haavelmo article, and it turns out to be a deep and insightful piece — for the reason Enno mentioned, but also more broadly on how to think about empirical economics. It’s especially interesting coming from soeone who won the Nobel Prize for his foundational work in econometrics. Another piece of evidence that orthodox economists in the mid-20th century thought more deeply and critically about the nature of their project than their successors do today.

It’s a long piece, with a lot of mathematical illustrations that someone reading it today can safely skip. The central argument comes down to three overlapping points. First, economic models are tools, developed to solve specific problems. Second, economic theories have content only insofar as they’re associated with specific procedures for measurement. Third, we have positive economic knowledge only insofar as we can make unconditional predictions about the distribution of observable variables.

The first point: We study economics in order to “become master of the happenings of real life.” This is on some level obvious, or vacuous, but it'[s important; it functions as a kind of “he who has ears, let him hear.” It marks the line between those who come to economics as a means to some other end — a political commitment, for many of us; but it could just as well come from a role in business or policy — and those for whom economic theory is an end in itself. Economics education must, obviously, be organized on the latter principle. As soon as you walk into an economics classroom, the purpose of your being there is to learn economics. But you can’t, from within the classroom, make any judgement about what is useful or interesting for the world outside. Or as Hayek put it, “One who is only an economist, cannot be a good economist.”5

Here is what Haavelmo says:

Theoretical models are necessary tools in our attempts to understand and explain events in real life. … Whatever be the “explanations” we prefer, it is not to be forgotten that they are all our own artificial inventions in a search for an understanding of real life; they are not hidden truths to be “discovered.”

It’s an interesting question, which we don’t have to answer here, whether or to what extent this applies to the physical sciences as well. Haavelmo thinks this pragmatic view of scientific laws applies across the board:

The phrase “In the natural sciences we have laws” means not much more and not much less than this: The natural sciences have chosen fruitful ways of looking upon physical reality.

We don’t need to decide here whether we want to apply this pragmatic view to the physical sciences. It is certainly the right way to look at economic models, in particular the models we construct in econometrics. The “data generating process” is not an object existing out in the world. It is a construct you have created for one or both of these reasons: It is an efficient description of the structure of a specific matrix of observed data; it allows you to make predictions about some specific yet-to-be-observed outcome. The idea of a data-generating process is obviously very useful in thinking about the logic of different statistical techniques. It may be useful to do econometrics as if there were a certain data generating process. It is dangerously wrong to believe there really is one.

Speaking of observation brings us to Haavelmo’s second theme: the meaningless of economic theory except in the context of a specific procedure for observation.  It might naively seem, he says, that

since the facts we want to study present themselves in the form of numerical measurement, we shall have to choose our models from … the field of mathematics. But the concepts of mathematics obtain their quantitative meaning implicitly through the system of logical operations we impose. In pure mathematics there really is no such problem as quantitative definition of a concept per se …

When economists talk about the problem of quantitative definitions of economic variables, they must have something in mind which has to do with real economic phenomena. More precisely, they want to give exact rules how to measure certain phenomena of real life.

Anyone who got a B+ in real analysis will have no problem with the first part of this statement. For the rest, this is the point: economic quantities come into existence only through some concrete human activity that involves someone writing down a number. You can ignore this, most of the time; but you should not ignore it all of the time. Because without that concrete activity there’s no link between economic theory and the social reality it hopes to help us master or make sense of.

Haavelmo has some sharp observations on the kind of economics that ignores the concrete activity that generates its data, which seem just as relevant to economic practice today:

Does a system of questions become less mathematical and more economic in character just by calling x “consumption,” y “price,” etc.? There are certainly many examples of studies to be found that do not go very much further than this, as far as economic significance is concerned.

There certainly are!

An equation, Haavelmo continues,

does not become an economic theory just by using economic terminology to name the variables invovled. It becomes an economic theory when associated with the rule of actual measurement of economic variables.

I’ve seen plenty of papers where the thought process seems to have been somthing like, “I think this phenomenaon is cyclical. Here is a set of difference equations that produce a cycle. I’ll label the variables with names of parts of the phenomenon. Now I have a theory of it!” With no discussion of how to measure the variables or in what sense the objects they describe exist in the external world.

What makes a piece of mathematical economics not only mathematics but also economics is this: When we set up a system of theoretical relationships and use economic names for the otherwise purely theoretical variables involved, we have in mind some actual experiment, or some design of an experiment, which we could at least imagine arranging, in order to measure those quantities in real economic life that we think might obey the laws imposed on their theoretical namesakes.

Right. A model has positive content only insofar as we can describe the concrete set of procedures that gets us from the directly accessible evidence of our senses. In my experience this comes through very clearly if you talk to someone who actually works in the physical sciences. A large part of their time is spent close to the interface with concrete reality — capturing that lizard, calibrating that laser.  The practice of science isn’t simply constructing a formal analog of physical reality, a model trainset. It’s actively pushing against unknown reality and seeing how it pushes back.

Haavelmo:

When considering a theoretical setup … it is common to ask about the actual meaning of this or that variable. But this question has no sense within the theoretical model. And if the question applies to reality it has no precise answer … we will always need some willingness among our fellow research workers to agree “for practical purposes” on questions of definitions and measurement …A design of experiments … is an essential appendix to any quantitative theory.

With respect to macroeconomics, the “design of experiments” means, in the first instance, the design of the national accounts. Needless to say, national accounting concepts cannot be treated as direct observations of the corresponding terms in economic theory, even if they have been reconstructed with that theory in mind. Cynamon and Fazzari’s paper on the measurement of household spending gives some perfect examples of this. There can’t be many contexts in which Medicare payments to hospitals, for example, are what people have in mind when they construct models of household consumption. But nonetheless that’s what they’re measuring, when they use consumption data from the national accounts.

I think there’s an important sense in which the actual question of any empirical macroeconomics work has to be: What concrete social process led the people working at the statistics office to enter these particular values in the accounts?

Or as Haavelmo puts it:

There is hardly an economist who feels really happy about identifying the current series of “national income, “consumptions,” etc. with the variables by those names in his theories. Or, conversely, he would think it too complicated or perhaps uninteresting to try to build models … [whose] variables would correspond to those actually given by current economic statistics. … The practical conclusion… is the advice that economists hardly ever fail to give, but that few actually follow, that one should study very carefully the actual series considered and the conditions under which they were produced, before identifying them with the variables of a particular theoretical model.

Good advice! And, as he says, hardly ever followed.

I want to go back to the question of the “meaning” of a variable, because this point is so easy to miss. Within a model, the variables have no meaning, we simply have a set of mathematical relationships that are either tautologous, arbitrary, or false. The variables only acquire meaning insofar as we can connect them to concrete social phenomena. It may be unclear to you, as a blog reader, why I’m banging on this point so insistently. Go to an economics conference and you’ll see.

The third central point of the piece is that meaningful explanation requires being able to identify a few causal links as decisive, so that all the other possible ones can be ignored.

Think back to that Paul Romer piece on what’s wrong with modern macroeconomics. One of the most interesting parts of it, to me, was its insistent Humean skepticism about the possibility of a purely inductive economics, or for that matter science of any kind. Paraphrasing Romer: suppose we have n variables, any of which may potentially influence the others. Well then, we have n equations, one for each variable, and n2 parameters (counting intercepts). In general, we are not going to be able to estimate this system based on data alone. We have to restrict the possible parameter space either on the basis of theory, or by “experiments” (natural or otherwise) that let us set most of the parameters to zero on the grounds that there is no independent variation in those variables between observations. I’m not sure that Romer fully engages with this point, whose implications go well beyond the failings of real business cycle theory. But it’s a central concern for Haavelmo:

A theoretical model may be said to be simply a restriction upon the joint variations of a system of quantities … which otherwise might have any value. … Our hope in economic theory and research is that it may be possible to establish contant and relatively simple relations between dependent variables … and a realtively small number of independent variables. … We hope that for each variable y to be explained, there is a realtively small number of explaining factors the variations of which are practically decisive in determining the variations of y. …  If we are trying to explain a certain observable varaible, y, by a system of causal factors, there is, in general, no limit to the number of such factors that might have a potential influence upon y. But Nature may limit the number of fctors that have a nonneglible factual influence to a relatively small number. Our hope for simple laws in economics rests upon the assumption that we may proceed as if such natural limitations of the number of relevant factors exist.

One way or another, to do empirical economic, we have to ignore mst of the logically possible relationships between our variables. Our goal, after all, is to explain variation in the dependent variable. Meaningful explanation is possible only if the number of relevant causal factors is small. If someone asks “why is unemployment high”, a meaningful answer is going to involve at most two or three causes. If you say, “I have no idea, but all else equal wage regulations are making it higher,” then you haven’t given an answer at all. To be masters of the hapennings of real life, we need to focus on causes of effects, not effects of causes.

In other words, ceteris paribus knowledge isn’t knowledge at all. Only unconditional claims count — but they don’t have to be predictions of a single variable, they can be claims about the joint distribution of several. But in any case we have positive knowledge only to the extent we can unconditionally say that future observations will fall entirely in a certain part of the state space. This fails if we have a ceteris paribus condition, or if our empirical works “corrects” for factors whose distribution and the nature of whose influence we have not invstigated.6 Applied science is useful because it gives us knowledge of the kind, “If I don’t turn the key, the car will not start, if I do turn the key, it will — or if it doesn’t there is a short list of possible reasons why not.” It doesn’t give us knowledge like “All else equal, the car is more likely to start when the key is turned than when it isn’t.”7

If probability distributions are simply tools for making unconditional claims about specific events, then it doesn’t make sense to think of them as existing out in the world. They are, as Keynes also emphasized, simply ways of describing our own subjective state of belief:

We might interpret “probability” simply as a measure of our a priori confidence in the occurrence of a certain event. Then the theoretical notion of a probability distribution serves us chiefly as a tool for deriving statements that have a very high probability of being true.

Another way of looking at this. Research in economics is generally framed in terms of uncovering universal laws, for which the particular phenomenon being  studied merely serves as a case study.8 But in the real world, it’s more oftne the other way: We are interested in some specific case, often the outcome of some specific action we are considering. Or as Haavelmo puts it,

As a rule we are not particularly interested in making statements about a large number of observations. Usually, we are interested in a relatively small number of observations points; or perhaps even more frequently, we are interested in a practical statement about just one single new observation.

We want economics to answer questions like, “what will happen if US imposes tariffs on China”? The question of what effects tariffs have on trade in the abstract is, itself, uninteresting and unanswerable.

What do we take from this? How, according to Haavelmo, should empirical economics be?

First, the goal of empirical work is to explain concrete phenomena — what happened, or will happen, in some particular case.

Second, the content of a theory is inseparable from the procedures for measuring the variables in it.

Third, empirical work requires restrictions on the logically possible space of parameters, some of which have to be imposed a priori.

Finally, prediction (the goal) means making unconditional claims about the joint distribution of one or more variables. “Everything else equal” means “I don’t know.”

All of this based on the idea that we study economics not as an end in itself, but in response to the problems forced on us by the world.

Links for October 6

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

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

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

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

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

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

 

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

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

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

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

 

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

 

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

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

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

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

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

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

 

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

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

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

 

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

 

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

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

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

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

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

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

 

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

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

Media advisory with synopsis is here.

 

On other blogs, other wonders

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

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

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

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

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

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

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

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

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

I Don’t See Any Method At All

I’ve felt for a while that most critiques of economics miss the mark. They start from the premise that economics is a systematic effort to understand the concrete social phenomena we call “the economy,” an effort that has gone wrong in some way.

I don’t think that’s the right way to think about it. I think McCloskey was right to say that economics is just what economists do. Economic theory is essentially closed formal system; it’s a historical accident that there is some overlap between its technical vocabulary and the language used to describe concrete economic phenomena. Economics the discipline is to the economy the sphere of social reality as chess theory is to medieval history: The statement, say, that “queens are most effective when supported by strong bishops” might be reasonable in both domains, but studying its application in the one case will not help at all in applying it in in the other. A few years ago Richard Posner said that he used to think economics meant the study of “rational” behavior in whatever domain, but after the financial crisis he decided it should mean the study of the behavior of the economy using whatever methodologies. (I can’t find the exact quote.) Descriptively, he was right the first time; but the point is, these are two different activities. Or to steal a line from my friend Suresh, the best way to think about what most economists do is as a kind of constrained-maximization poetry. Makes no more sense to ask “is it true” than of a haiku.

One consequence of this is, as I say, that radical criticism of the realism or logical consistency of orthodox economics do nothing to get us closer to a positive understanding of the economy. How is a raven unlike a writing desk? An endless number of ways, and enumerating them will leave you no wiser about either corvids or carpentry. Another consequence, the topic of the remainder of this post, is that when we turn to concrete economic questions there isn’t really a “mainstream” at all. Left critics want to take academic orthodoxy, a right-wing political vision, and the economic policy preferred by the established authorities, and roll them into a coherent package. But I don’t think you can. I think there is a mix of common-sense opinions, political prejudices, conventional business practice, and pragmatic rules of thumb, supported in an ad hoc, opportunistic way by bits and pieces of economic theory. It’s not possible to deduce the whole tottering pile from a few foundational texts.

More concretely: An economics education trains you to think in terms of real exchange — in terms of agents who (somehow or other) have come into possession of a bundle of goods, which they trade with each other. You can only use this framework to make statements about real economic phenomena if they are understood in terms of the supply side — if economic outcomes are understood in terms of different endowments of goods, or different real uses for them. Unless you’re in a position to self-consciously take another perspective, fitting your understanding of economic phenomena into a broader framework is going to mean expressing it as this kind of story, about the limited supply of real resources available, and the unlimited demands on them to meet real human needs. But there may be no sensible story of that kind to tell.

More concretely: What are the major macroeconomic developments of the past ten to twenty years, compared, say, with the previous fifty? For the US and most other developed countries, the list might look like:

– low and falling inflation

– low and falling interest rates

– slower growth of output

– slower growth of employment

– low business investment

– slower growth of labor productivity growth

– a declining share of wages in income

If you pick up an economics textbook and try to apply it to the world around you, these are some of the main phenomena you’d want to explain. What does the orthodox, supply-side theory tell us?

The textbook says that lower inflation is normally the result of a positive supply shock — an increase in real resources or an improvement in technology. OK. But then what do we make of the slowdown in output and productivity?

The textbook says that, over the long run interest rates must reflect the marginal product of capital — the central bank (and monetary factors in general) can only change interest rates in the short run, not over a decade or more. In the Walrasian world, the interest rate and the return on investment are the same thing. So a sustained decline in interest rates must mean a decline in the marginal product of capital.

OK. So in combination with the slowdown in output growth, that suggests a negative technological shock. But that should mean higher inflation. Didn’t we just say that lower inflation implies a positive technological shock?

Employment growth in this framework is normally determined by demographics, or perhaps by structural changes in labor markets that change the effective labor supply. Slower employment growth means a falling labor supply — but that should, again, be inflationary. And it should be associated with higher wagess: If labor is becoming relatively scarce, its price should rise. Yes, the textbook combines a bargaining mode of wage determination for the short run with a marginal product story for the long run, without ever explaining how they hook up, but in this case it doesn’t matter, the two stories agree. A fall in the labor supply will result in a rise in the marginal product of labor as it’s withdrawn from the least productive activities — that’s what “marginal” means! So either way the demographic story of falling employment is inconsistent with low inflation, with a falling wage share, and with the showdown in productivity growth.

Slower growth of labor productivity could be explained by an increase in labor supply  — but then why has employment decelerated so sharply? More often it’s taken as technologically determined. Slower productivity growth then implies a slowdown in innovation — which at least is consistent with low interest rates and low investment. But this “negative technology shock” should again, be inflationary. And it should be associated with a fall in the return to capital, not a rise.

On the other hand, the decline in the labor share is supposed to reflect a change in productive technology that encourages substitution of capital for labor, robots and all that. But how is this reconciled with the fall in interest rates, in investment and in labor productivity? To replace workers with robots, someone has to make the robots, and someone has to buy them. And by definition this raises the productivity of the remaining workers.

Which subset of these mutually incompatible stories does the “mainstream” actually believe? I don’t know that they consistently believe any of them. My impression is that people adopt one or another based on the question at hand, while avoiding any systematic analysis through violent abuse of the ceteris paribus condition.

To paraphrase Leijonhufvud, on Mondays and Wednesdays wages are low because technological progress has slowed down, holding down labor productivity. On Tuesdays and Thursdays wages are low because technological progress has sped up, substituting capital for labor. Students may come away a bit confused but the main takeaway is clear: Low wages are the result of inexorable, exogenous technological change, and not of any kind of political choice. And certainly not of weak aggregate demand.

Larry Summers in this actually quite good Washington Post piece, at least is no longer talking about robots. But he can’t completely resist the supply-side lure: “The situation is worse in other countries with more structural issues and slower labor-force growth.” Wait, why would they be worse? As he himself says, “our problem today is insufficient inflation,” so what’s needed “is to convince people that prices will rise at target rates in the future,” which will “require … very tight markets.” If that’s true, then restrictions on labor supply are a good thing — they make it easier to generate wage and price increases. But that is still an unthought.

I admit, Summers does go on to say:

In the presence of chronic excess supply, structural reform has the risk of spurring disinflation rather than contributing to a necessary increase in inflation.  There is, in fact, a case for strengthening entitlement benefits so as to promote current demand. The key point is that the traditional OECD-type recommendations cannot be right as both a response to inflationary pressures and deflationary pressures. They were more right historically than they are today.

That’s progress, for sure — “less right” is a step toward “completely wrong”. The next step will be to say what his argument logically requires. If the problem is as he describes it then structural “problems” are part of the solution.

Posts in Three Lines

There is no long run. This short note from the Fed suggests that the failure of output to return to its earlier trend following the Great Recession is not an anomaly; historically, recessions normally involve permanent output losses. This working paper by Lawrence Summers and Lant Pritchett argues that it is very hard to find persistent growth differences between countries. From opposite directions, these results suggest that there is no reason to think that supposedly “slow” variables are more stable than “fast” ones; in other words, there is no economically meaningful long run.

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Krugman on the archaeology of “price stability.” Here is Paul Krugman’s talk from the same Roosevelt Institute/AFR/EPI even I spoke at last month. The whole thing is quite good but the most interesting part to me was on the (quite recent) origins of the idea that price stability means 2 percent inflation. From Adam Smith until the 1990s, price stability meant just that, zero inflation; but in the postwar decades it was more or less accepted that that was one objective to trade off against others, rather than the sine qua non of policy success.
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Capital is back — or is it? Here’s an interesting figure from Piketty and Zucman’s 2013 paper, showing the long-term evolution of capital and labor shares in the UK and France:
What we see is not a stable or rising capital share, but rather a secular shift in favor of labor income, presumably reflecting the long term growth of political power of working people from the early 19th century, when unions were illegal, labor legislation was unknown and only property owners could vote. What’s funny is that this long-term decline in the power of capital is so clearly visible in Piketty’s data, but so invisible in the discussion of his book.
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Orange is the big lie. Like lots of people, I watched the Netflix show Orange Is the New Black and initially enjoyed it, enough to read the memoir on which it’s based. It’s not often you see ideology operation so visibly: The show systematically omits the book’s depictions of abuse and racism among the guards and solidarity among the prisoners, and introduces violence from the prisoners and compassion from the authorities that is not present in the book. For example, both book and show feature an affair between a female prisoner and a male guard, but in the show nothing happens to the prisoner while the guard is fired and prosecuted, while in reality the prisoner was thrown into solitary confinement and there were no consequences for the guard.

Cochrane on Economic Orthodoxies

John Cochrane has a good post  saying something I’ve been thinking about for a while. There are two disjoint orthodoxies in economics, one in policy and one in scholarship. Both are secure on their own territory, but they have little connection with each other. This isn’t obvious from the outside since many of the same institutions and even individuals contribute to the reproduction of both orthodoxies, but as intellectual projects they are entirely distinct.

Cochrane:

There is … a sharp divide between macroeconomics used in the top levels of policy circles, and that used in academia. 

Static ISLM / ASAD modeling and thinking really did pretty much disappear from academic research economics around 1980. You won’t find it taught in any PhD programs, you won’t find it at any conferences …, you won’t find it in any academic journals…  “New-Keynesian” DSGE (Dynamic Stochastic General Equilibrium) models are much in vogue, but have really nothing to do with static Keynesian ISLM modeling. Many authors would like it to be so, but when you read the equations you will find these are just utterly different models. 

Static ISLM thinking pervades the upper reaches of the policy world. … If you read the analysis guiding policy at the IMF, the Fed, the OECD, the CBO; and the larger policy debate in the pages of the Economist, New York Times, and quite often even the Wall Street Journal, policy analysis is pretty much unchanged from the Keynesian ISLM, ASAD, analysis I learned from Dornbush and Fisher’s textbook, taught in Bob Solow’s undergraduate Macro class at MIT about 1978. 

Note that Cochrane is agnostic about which of these projects is on the wrong track.  This is a habit of mind we should all try to cultivate: The interesting questions are the ones where we can seriously imagine more than one answer.