JW Mason reflects on the State of macroeconomics:
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 comprehensive exam 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.
He lists 5 changes the curriculum needs:
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.
Read the comments too. Macro is another word for fights!
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