At one time, a philosopher was someone interested in acquiring knowledge about the world. Over time, specific areas of philosophy developed coherent models and branched off to become separate fields such as physics and astronomy. Later, fields branched off before they had even developed a coherent framework for analysis, or perhaps when they had multiple frameworks (as one typically sees in the social sciences.) Philosophy was left with the remainder, the questions that had not yet spawned separate fields of inquiry.
Tyler Cowen can be viewed as a philosopher, as his interests are too broad to be confined to a single intellectual framework. His new (free online) book entitled The Marginal Revolution: Rise and Decline, and the Pending AI Revolution is economic philosophy, a look at the field of economics from the outside by someone who understands it from the inside.
You might think that’s no big accomplishment, but as a general rule economists are too close to the subject to have an outside perspective of their field and non-economists are too poorly informed. For the most part, you either encounter orthodox economists reflexively defending the field, or heterodox outsiders complaining that economists are wrong because they don’t look at the world the way that this particular critic does. Tyler does neither. He mourns the end of the economics that he and I grew up with but also suggests that in some sense we had it coming.
As with books like The Great Stagnation and Average is Over, I suspect this book will set the agenda for future debate about where economics is and should be going in the 21st century. I do not plan to do a complete book review in this post. Indeed I’ll skip the most important part—AI. Instead, I’ll offer a few observations where I feel that I have something useful to add.
I recall one of my Chicago professors (George Stigler?) suggested that the most difficult task facing economists is not coming up with good answers, rather the real need is for better questions. Once an important question has been identified, the answer is often fairly easy to discern. Thus, Ronald Coase built a career partly based on his discovery of a single interesting question: Why do firms exist? Most people would never think of even asking that question. Coase’s answer (“transactions costs”) proved to have fruitful applications in many different areas.
My favorite part of Tyler’s book is where he asks a very good but non-obvious question: Why did it take so long for economics as a field to develop a coherent model or framework of analysis? Much of the book discusses how three economists simultaneously developed marginal analysis, with a focus on the work of Stanley Jevons. Here I’ll briefly provide the intuition of marginal analysis and then explain why economics is both extremely easy but also quite difficult.
Consider some human activity X. How much of this activity would (should?) we choose to do? A marginalist might suggest doing more of activity X as long as the marginal benefit of one more unit of X exceeds the marginal cost of one more unit of X. You then stop right at the point when the marginal benefit falls below the marginal cost, a position referred to as “equilibrium”.
Activity X might be the consumption of a good, production of a good, number of workers hired by a firm, number of dollars invested in a project, or almost any other type of human endeavor. In recent decades, NBA teams discovered that the marginal benefit of taking more 3-point shots exceeded the marginal cost of foregone 2-point shots and changed their strategies appropriately.
I was a good but not great student in high school and college. I got a lot of As, but also a fair number of Bs and Cs. But once I figured out the basic intuition of marginal analysis, the entire field began to seem quite easy. I stopped taking notes in class and just listened to the lectures.
But there’s also a sense in which economics is quite difficult. STEM-types often mock economists because our models are rather simple in a technical sense, at least compared to the harder sciences. That’s true, but it is also true that if you speak to scientists about economics, their opinions are often absurdly misguided. “Why don’t they just do . . . “ Yeah, you might want to look up “Chesterton’s Fence”.
Imagine a gas station deciding on how to price its product. Draw up a chart with the wholesale price of gasoline in one column and the profit-maximizing retail price charged in the next column. It is pretty obvious that the higher the wholesale price (including excise tax), the higher the profit maximizing retail price. I’m guessing that roughly 100% of the public understands this, at least on some basic level.
From a mathematical perspective, the implication of this monotonically increasing function is obvious. When input prices rise, firms will raise output prices and when input prices fall, firms will lower output prices. Or at least that’s how they’d behave if they were trying to maximize profits. (Admittedly they might behave in some other way if they were trying to go bankrupt.)
Now imagine visiting a convention full of high IQ scientists. Tell them that the government should reduce fees on property developers, because this will allow the developers to reduce the price of newly constructed homes. A significant proportion of them will roll their eyes and tell you not to be naive. “These developers are greedy, and they won’t pass on lower costs to consumers.” Sigh . . .
When teaching, I frequently found myself having to tell students “Yeah, they are greedy, which is precisely why they’ll pass on lower input costs to consumers.” It’s true that implications of economic models are often obvious when you think about them in mathematical terms, but when you don’t have that model in the front of your mind, the world can be a very confusing place. You may fall back on common sense intuitions that are simply false:
“Companies are greedy and higher prices are good for profits.”
Sorry, the first half of that statement is true, but the second half is false. It’s the symmetry, stupid. (And yes, pricing for monopolies is equally symmetrical.)
Economics is full of concepts that on one level are sort of obvious but at another level are deeply counterintuitive. Try explaining to people that price gouging during emergencies is actually good for consumers. We evolved with minds shaped by primitive reciprocal gift giving tribal societies that had norms about right and wrong, and suddenly ask people to think about the optimal amount of pollution, vice, traffic fatalities, etc. It doesn’t feel right.
In my own field of monetary economics, I find that people like to think about inflation by focusing on those goods rising fastest in price. But those are relative price changes, and inflation is a rise in the absolute price level. Inflation can only be explained by considering changes in the supply and demand for money—the medium of account. But that’s deeply counterintuitive, as most people think of inflation as rising prices, not a falling value of the dollar.
Tyler does a great job explaining why Jevon’s model of marginal analysis (which underlies most of modern microeconomics) is elementary on one level, but also something that wasn’t discovered until the 1860s because it was not at all obvious. Here’s how he concludes Chapter 3:
By studying the slow intellectual development of economics, and contrasting it with other fields of study, we can learn the following:
1. Some insights are very hard to grasp, even if they are apparently simple once they are understood. People need to “see around corners” in the right way to understand these insights and incorporate them into their world views.
2. Economics is one of those fields, and that is why it took intuitive economic reasoning so long to evolve, marginalism included. Those of us who are educators, or who spend time talking to policymakers, should take this point very seriously.
3. Even very, very smart people are likely unaware that these “see around the corner” insights are missing – did Euclid rue that he did not have access to proper supply and demand and tax incidence theory? Probably not.
4. Economics is not the only such field that is hard to grasp, some other examples being segments of botany, geology, and evolutionary biology.
5. Scientific revolutions come about when many complementary pieces are in place, such as financial support, intellectual independence, and networks of like-minded others to talk with.
Those conditions help people to understand that “seeing around those corners” can bring both high social and professional returns.
Are there major conceptual corners that today still no one can see around? If so, how might we discover what they are? And why are we not working harder on this? Or are we?
So why does Tyler see marginalism declining in importance? This is the most important part of the book, and the most difficult for me to evaluate. I’m a hedgehog that likes a single powerful explanation and Tyler is a fox that likes to look at problems from multiple angles.
[BTW, it is interesting that Tyler is so interested in AI, as LLMs remind me more of Tyler Cowen than of any other human being. Like Tyler, LLMs have “read everything”. If you ask a typical economist what’s wrong with tariffs, they’ll say something about Harberger triangles. Ask Tyler or an LLM, and they’ll list 12 different problems drawing on the literature from multiple fields.]
Tyler begins by citing the fact that marginal analysis often provides unwelcome policy advice:
The confrontational or “social discomfort” side of marginalism, discussed in chapter one, is now hurting marginalism somewhat. It is not the main reason why marginalism as a series of intuitions is dwindling. Yet (at the margin!), as the economics profession has moved to the left, a diminished role for at least some marginalist intuitions is perhaps not entirely unwelcome. Marginalism may thus have somewhat fewer defenders than might otherwise have been the case, if no political motives had intervened. I am not suggesting anyone is being dishonest here, rather, that their politics induce them to champion other methodological causes than marginalism, mostly because those other causes seem, for normative reasons, more important.
Policymakers in NYC probably don’t wish to be told that spending $81,000 on each homeless person might make homelessness marginally less unpleasant and thus increase the number of homeless New Yorkers.
It occurred to me that Tyler overlooks a previous decline in marginalism during 1933-68, when Chicago style price theory fell out of favor. It was hard to argue that minimum wages were a bad policy when the US was experiencing 25% unemployment in an economy with no minimum wage at all (in 1932), and only 4% unemployment in the late 1960s, when the minimum wage was fairly high. The Great Depression didn’t just seem to discredit capitalism, it also pushed marginalism to the periphery of economics, as the focus shifted to Keynesian models of aggregate demand. Marginalism is often a form of supply-side economics.
In the final decades of the 20th century—the neoliberal era—marginalism made a comeback. Chicago economists won lots of Nobel Prizes. This was mostly due to the fact that policymakers overreached, exposing problems with the Keynesian model. It seemed the supply side did matter after all. Tyler often (correctly) lectures people like me to stop being so pessimistic, but I wonder if Tyler is too pessimistic here about the prospects of another future comeback for marginalism. Indeed, isn’t the recent “abundance” movement largely based on marginalist thinking?
On the other hand, the Great Recession does seem to have been a setback for Chicago price theory. Tyler is right that the profession has recently turned to the left. Elsewhere I’ve argued that stable NGDP growth isn’t just good for the economy; it’s good for the field of economics—raising the prestige of free markets.
In some places, Tyler seems to mourn the decline of marginalism:
Price theory, as an approach, is not identical to marginalism. But so many of the basic economic concepts from intermediate micro use marginalist ideas, so price theory has been a comfortable home in which marginalism has flourished, including marginalism as an active research program.
Sadly, price theory is fading in relevance, and it is taking marginalism down with it. It used to be that some graduate programs favored the axiomatized approach to micro and others (e.g., University of Chicago, UCLA, University of Virginia) favored the price theory approach. These days the axiomatizations have won out pretty much everywhere, except at my own George Mason University. I don’t know of any other exceptions to that, but I do keep looking for them. To the extent I see exceptions to the dominance of the axiomatic approach, it is because empiricism is ascendant, not because price theory is making a comeback.
Although Tyler’s book focuses on microeconomics, reading it helped me to better understand why I’ve gradually lost interest in modern macroeconomics, which has moved in a direction that I find to be of little interest. This is a great observation:
One sign of the decay of interest in marginalism is that “price theory” has moved to being a niche interest in economics. To some economists, especially from a few decades ago, that may sound almost contradictory, almost like saying “economics has become a niche field within economics.” Well, that is a bit true as well.
If Milton Friedman were still alive, I suspect he’d feel the same that way I do:
The other leader of the price theory movement, Steve Levitt of Freakonomics fame, retired from academia and the University of Chicago at age 57, claiming he was having no impact with his research papers. He has stated flat out, “And I think in the marketplace for ideas, I gotta say that the Chicago price theory really has lost.” And “I think it [price theory] is essentially lost to posterity at this point.” Levitt notes that Milton Friedman had such a worry as long ago as the 1990s.
[The quote is about micro, but Friedman would be equally appalled at trends in macro.]
In retrospect, Paul Krugman’s 1998 paper “It’s Baaack” seems like the final important contribution to a 30-year golden age of macroeconomics for the fiat money world, which began in 1968, just as the US adopted a 100% fiat money regime and Friedman/Phelps developed their natural rate models. I’m sure you could point to lots of very high quality 21st century macro papers—but how many actually changed the way we look at the world in any sort of fundamental way?
At times, Tyler suggests that the useful insights of marginalism have already been incorporated into the profession. Since people naturally wish to do work at the frontier, marginalism is now less central to modern research. As an analogy, modern mathematicians haven’t rejected addition and multiplication, but they no longer write papers explaining these elementary concepts.
At other times, Tyler suggests that there are real problems with marginal analysis. My one criticism of the book, at least on a first reading, is that it wasn’t always clear exactly what Tyler saw as the central problem facing marginalism. For instance, minimum wage studies showing no effect on employment might be viewed as being inconsistent with “Chicago price theory”, but they are not necessarily inconsistent with marginal analysis, as they are often based on monopsony models that assume the marginal cost of labor exceeds the wage rate. That’s still marginal analysis. To be fair, Tyler acknowledges this fact in the first chapter, but at other times seems to almost conflate marginalism with Chicago price theory.
Tyler spends quite a bit of time discussing anomalies in modern finance, areas where empirical studies seem to reject the standard models of finance. At one point Tyler suggests that it is an especially big problem that flaws are showing up in the field of financial economics, as this is the field in which we have by far the best data:
For a long time I have thought of finance as the most advanced and most successful branch of economics. It works with the highest quality data, has many of the most rigorous models, and the economic assumption of “people really do want money only” seems relatively justified in that sphere of endeavor.
. . . The ascension of economic portfolio models, which started in the 1960s, is now very far from the relevant frontiers. To put it very bluntly, at the current state of knowledge those models are failing the market test.
This is especially painful for economics, because the original triumphs of economics in that field were explicitly marginalist in their origins.
But one could argue the opposite. All social science models are “false” in the sense of being only an approximation of reality, and hence we’d expect extremely good data to be especially helpful is showing the limits of any model. It took very good data to show the superiority of General Relativity to Newtonian physics.
Consider the case of the minimum wage. Can ambitious researchers find real world examples of markets that deviate slightly from the Chicago school model of perfect competition? Almost certainly yes. Does that mean the government of Pakistan should institute a $15/hour minimum wage as an anti-poverty policy? Obviously not. I think of Chicago price theory as a sort of first pass on a policy question, with more rigorous research demonstrating its limitations in specific cases.
Similarly, the Efficient Market Hypothesis is a sort of first pass on financial issues, not the be-all-and-end-all of financial research. It is often noted that the theory seems to be sort of self-refuting. If markets were truly efficient, then why would anyone gather the information required to make the market efficient? Even EMH proponents like Eugene Fama regard it as merely a useful approximation of reality.
In the past, I’ve been highly skeptical of “anomaly” studies, as I’ve seen so many claims fail to hold up out-of-sample. We were all taught the superiority of “value stocks”. Don’t buy those high-flying tech stocks. How’d that work out?
Perhaps it is best for most people to simply buy index stock funds, even if ambitious researchers using 360,000 factors are able to develop superior models of stock returns:
There is a recent working paper which is perhaps more striking yet, by Antoine Didisheim, Shikun (Barry) Ke, Bryan T. Kelly, and Semyon Malamud. They pick up from Arbitrage Pricing Theory (APT), a well-established idea from financial economics. APT typically looks for “factors” in the data which predict excess returns, and a traditional APT model might have found five or six such factors. Are “inflation” or perhaps “the term structure of interest rates” useful factors? Well, that can be debated, but if so, those results sound pretty intuitive. But those intuitions seem to be disappearing. In a paper by these authors, they apply machine learning methods to look for more factors. As we know, machine learning is very good at finding non-obvious relationships in the data. The largest model they built has 360,000 (!) factors, and it reduces pricing errors by 54.8 percent relative to the classic six-factor model from Fama and French.
Tyler discusses the fact that Wall Street firms often prefer to hire physicists, computer scientists and mathematicians rather than finance grads. But is that actually a problem for economics? We tend to assume that the local pizza joint will produce where marginal revenue equals marginal cost, even if they prefer to hire talented cooks rather than econ majors. If markets are efficient, why would a finance grad be especially valuable? Yes, they are smart and understand the terminology, but STEM people are often even smarter and can quickly be taught the terminology. Again, economics is simple once the basic models have been explained to an intelligent person.
To be fair, there are places where Tyler suggests that research has exposed flaws greater than those found in Newtonian physics, areas where the standard model may not even be a useful approximation of reality:
When financial economists refined the models with more complete specifications, it turned out Beta didn’t predict stock returns much at all. Eugene Fama and Kenneth French delivered one of the final blows to earlier approaches with a 1992 paper that showed Beta didn’t have explanatory power over expected returns at all. Since Fama himself was one of the original architects of CAPM-like reasoning, and French also was a renowned finance economist, these revisions to the model were credible.
For all its original promise, marginalism, and the concomitant notion of diminishing marginal utility, no longer seemed to help explain asset returns. Under one plausible account of intellectual history, you can date the decline of marginalism to that 1992 paper. In the most rigorous, data-oriented, and highest-paying field of economics, namely finance, marginalist constructs had every chance to succeed. In fact, they ran the board for several decades. But over time they failed. In the most prestigious field of economics, marginalism has been in full retreat for over 30 years, and it shows no signs of making a comeback.
Financial economics is not my area of expertise, so I’ll leave this as an open question.
Instead let me summarize what I interpret as the main problems that Tyler is considering:
Marginalism is old hat—researchers want something new.
Marginalism has right wing implications. Most intellectuals are left wing.
Marginalism has been shown to be only an approximation of reality, and younger economists wish to expose its limitations.
Modern empirical research often does better employing big data in an atheoretical fashion.
Marginalism seems to be wrong on at least some important questions, such as the impact of “beta” on stock returns.
That’s a quite a diverse set of claims, with each claim having different implications.
Tyler ends with some very interesting speculation as to how AI may reshape the field of economics. Perhaps I’ll consider those ideas in a future post.
Undoubtedly, there’ll be debate over the meaning of his final paragraph:
There is however a slightly scarier version of this story yet. Maybe our intuitions about the world, including the economic world, were never so strong in the first place. Maybe we put so much value on “intuitive” results, in 20th century microeconomics, as a kind of cope and also security blanket, to make up for this deficiency. But our intuitions, even assuming them to be largely correct, always were just a small corner of understanding, swimming in a larger froth of epistemic chaos. And now the illusion has been stripped bare, and the true complexities of economic reasoning are being revealed.
I can think of any number of interpretations here:
The world is very complex.
The world is constantly changing.
Important concepts like utility cannot be measured.
Behavioral considerations are probably important but are hard to model.
Perhaps our models are more “WEIRD”, more culturally specific, than we have been assuming. How about an economics for contemporary Haiti?
To me, this seems like one of those glass half full/half empty situations, where we’d need to be more specific as to the question at hand before providing any sort of overall evaluation of the state of economics. I suspect that if Tyler were put in a room full of smug orthodox economists, he’d stand out as the critic of complacency. Put in a room full of heterodox critics of economics, and he’d probably tell them they underestimate the usefulness of mainstream economic models.
If this sort of book had been written by a marginalism skeptic—say an MMTer—it might be easily dismissed. The fact that Tyler is obviously a fan of marginal thinking and understands its strengths, gives his pessimistic outlook much more credibility.
Regardless of where you stand on any of these issues, this book will set the agenda for future debate over the direction of economics. But it also has interesting implications for a wide range of fields that are generally viewed as “science” and yet face many of the same problems as economics (widely viewed as a non-science by natural scientists), including botany, geology, meteorology and evolutionary biology. Self-recommending.
PS. People have been calling for more Trump bashing. Honestly, I feel like I’d be insulting your intelligence. But if you insist, here are five good Yglesias tweets from just the past 24 hours.
PPS. You presumably noticed that this post is ungated. In the future, there’ll be a mixture of 100% open posts, and partially gated posts.