Why teach kids macro at the intro level?

I've been writing some posts about Econ 101 (post 1, post 2, post 3). The basic theme is that kids need to learn a lot more evidence at the intro level, including methods. One response has been that it's actually very hard to teach kids even the simplest methods like OLS. At best, it would take a lot of time, and a one-semester intro course is just not long enough.

That got me thinking: What are the kids doing in the second semester of a year of intro economics? At a lot of schools, they're taking intro macro, often called Econ 102. I used to teach that class at Michigan, actually. And to be honest, I'm starting to think that this class is not really necessary. I think econ departments should think seriously about turning 102 from a macro class into a data/econometrics class.

Why should undergrads learn macro in their first year of econ? If they go on to be econ majors they can easily start out with intermediate macro and not miss anything important. If they just take the first-year econ sequence and then go into the business world, what do they really need to know?

In terms of growth theory, they might as well know the Solow model, so they can understand that capital accumulation by itself won't be a sustainable source of economic growth. Really, the Solow model is just a convenient way of teaching growth accounting, introducing ideas like capital, labor, human capital, and total factor productivity. And it's the one time in intro econ where you use a differential equation, so that could be useful for general math skill. Other than that, there's not really much growth theory an intro student needs.

How about business cycle theory? When kids go into the business world, it will probably help to know the standard Milton Friedman, New Keynesian, AD-AS, accelerationist Phillips Curve theory of monetary policy. That doesn't mean the standard theory is right (maybe Neo-Fisherian theory is better!), but since most people in the business world and at central banks sort of think it's right, kids will benefit from knowing it. It's easy and quick to teach to 101 students, since AD-AS fits right into the supply-and-demand graph stuff they're doing anyway. And if you want to mention RBC, you can just take the AD-AS graph and draw a vertical AS curve.

That's all I can really think of, and it's only about two weeks of material.

We have a lot of macro theories, but none that really work well unless you pick your data set very carefully and squint very hard. We have some methods for gathering evidence, but none that are very satisfying, and none that are simple enough for most intro level kids to understand.

And to make it worse, most of the macro theories that economists take halfway seriously are too hard for intro kids, so they end up learning silly stuff like Mundell-Fleming and Keynesian Cross that no one even halfway believes. Do we want kids going out in the business world and making deals as if interest rates will eventually equalize across all countries? God, I hope not.

So devoting 50% of the first-year econ sequence to macro just seems like a giant waste to me. We tend to think of macro and micro as symmetric things, but really "micro" is a lot bigger and more general than "macro". It affects a lot more policy questions, it has a lot more abundant and reliable evidence, it has a lot more interesting theoretical methodologies (game theory!), and it is more directly relevant to what students will eventually encounter in the business world.

So here's my new proposal for the first-year intro econ sequence. Replace useless macro with useful micro empirics. Either:

A) make 101 about theory and 102 about micro evidence, and stick Solow and AD-AS into 101, or

B) make 101 and 102 both predominantly micro (with Solow and AD-AS thrown in), and intersperse theory and evidence while stretching the sequence over 2 semesters.

And just kill the all-macro 102 course. It's not really doing anyone any good. It's kind of a barbarous relic.


Updates

1. On Twitter, Matt Yglesias says that econ probably has too much prestige tied up in macro to ditch the intro macro class. Maybe that's true. But I wonder if intro macro might now be generating negative prestige for the profession. Since the crisis there have been millions of words written in the media about how macro is bunk, macroeconomists don't know anything, etc. Killing intro macro might actually be saving the field some embarrassment, because a lot of those 102 theories really are obvious bunk, and most of the rest have taken a beating since 2008.

2. Some people (in the comments and on Twitter) have suggested that simply teaching kids the meaning of GDP, inflation, etc., and how these things are measured, could fill a whole semester. My response is: Maybe, but why go looking for ways to fill a whole semester? It sounds to me like status quo bias - because we've always taught an intro semester called "macro", we had better go find some "macro"-y stuff to teach. Sure, learning about growth accounting and NIPA calculations and whatever is cool. But there's a whole bunch more super duper useful stuff they could be learning instead: data analysis! Data analysis is becoming more and more important in econ, and more and more important in the business world. We're doing students a disservice by not teaching it in intro classes, and if we're going to correct that, something will have to make way. And I think the best "something" is macro.

Econ 101 and data (reply to David Henderson)

I wrote a post for Bloomberg View about how Econ 101 needs more empirics (a favorite hobbyhorse of mine). They titled it "Most of What You Learned in Econ 101 is Wrong", which was a catchy but inaccurate title, since the word "wrong" is often unhelpful in describing scientific theories. For example, in the post, when writing about minimum wages, I wrote:

That doesn't mean the [Econ 101] theory is wrong, of course. It probably only describes a small piece of what is really going on in the labor market.

Sometimes you test a theory by looking at policy experiments, and what you find is that the treatment effect is in the direction the theory predicts, but the fit is poor - the percent of the variance explained is small. Does that mean the theory is "right", because the treatment effect is in the expected direction? Or does it mean the theory is "wrong", because the fit is poor? 

The answer, of course, is that "right" and "wrong" are not very descriptive, helpful adjectives in this situation. 

Anyway, there's the question of what to teach kids. Personally, I think that you should teach kids empirics no matter how good your theories are. High school physics and chem classes teach simple theories that are amazingly good at explaining a lot of real phenomena, but they also make sure to include lab experiments, so that kids can see for themselves that the theories work. And those are high school kids; college kids will be even more capable. There's no reason a college econ student shouldn't learn how to run regressions in 101.

But I think this becomes even more important when Econ 101 theories have poor fit. People tend to confuse treatment effects with goodness of fit, so if you teach kids a bunch of theories with poor fit but which get the sign of the treatment effect right, the kids will leave class thinking that these theories explain a lot more of the world than they really do.

This distinction is what some critics of my Bloomberg View post don't seem to get. For example, David Henderson writes:

In other words, in most cases there is a small, presumably negative, effect on employment. And presumably in the other cases there is a large effect. How, exactly, does this contradict the claims that Mankiw makes and that many of us teach in our equivalents of Econ 101? It doesn't.

In this case, the theories that Econ 101 books (like Mankiw's) teach tend to get treatment effects of the right sign - minimum wage hikes of the typical size probably do have a (very small) negative effect on employment. When Henderson says that the evidence doesn't "contradict" the theory, he means that the theory gets the sign of the treatment effect right.

The problem is that by emphasizing theory so much, and by relegating evidence to some brief asides, Econ 101 textbooks (and classes) will tend to trick kids into thinking that the theories have better fit than they do. When you make people learn a theory in detail, I think they naturally tend to believe that the theory has strong empirical fit unless they see evidence to the contrary. 

My other example was welfare. Studies show that the effects of the implicit tax rates in welfare programs like the EITC are very small. That's consistent with the relatively small Frisch elasticity of labor supply found in most micro studies. Even when you get welfare programs with very large implicit tax rates (100%!), the effect is generally not as big as you might expect (with 100% implicit tax rates, you'd expect AFDC to leave income unchanged, when in fact it does boost it somewhat). That implies that welfare affects labor supply through channels other than implicit tax rates and lump-sum payments. For example, Moffitt's survey of theory and evidence on traditional (TANF and AFDC) welfare programs discusses the idea of "welfare stigma". That's an idea that is difficult to explain with an Econ 101 type theory. But it may be important in practice. Thus, it is an idea that can only really be presented by looking at the evidence. (Note that this is a reason welfare programs are probably worse than the labor supply effects would imply!)

Now Mankiw doesn't disregard evidence, and Henderson gives an example of the way that Mankiw presents it:

Although there is some debate about how much the minimum wage affects unemployment, the typical study finds that a 10 percent increase in the minimum wage depresses teenage employment [by] between 1 and 3 percent.

Evidence is given, but it is relegated to a brief aside. The kids don't see the data for themselves. They don't learn how to work with it. They don't learn how the studies tested what they tested. They don't learn how to go verify for themselves how useful econ theories are.

To these kids, econ theories must seem like received wisdom. Even evidence, when presented only as a brief aside with no understanding of methodology, must also seem like received wisdom. Again and again, I talk to econ students who complain that they are expected simply to swallow what they are taught - unlike in their science classes. College kids are smart, and many of them are skeptical. They grow up learning that "science is the belief in the ignorance of experts." That doesn't tend to sit well with the kind of "received wisdom" approach that almost every intro econ textbook takes. Nor should it.

So while I definitely don't want to pick on Mankiw - his books really are excellent, my personal favorites - I think that most intro econ textbooks use this "received wisdom" style of theory-centric education with only brief references to empirical findings. That tends to result in students who either A) believe too much in the power of the theories they learn, or B) disbelieve and distrust econ in general. I see a lot of examples of both (A) and (B). Both of those outcomes do a disservice to the world.

A big sweeping theory of modern history

Here's a Big Sweeping Theory that I've been toying with. There are lots of theories of the cycle of rise and decline of empires in the agricultural, premodern world. I'd like to create a parallel theory of low-frequency cycles (or, more accurately, long-term impulse responses to stochastic technology shocks) in the modern, industrialized world.

It's possible to see the convulsions of the World Wars and the Great Depression as a one-time event - part of the growing pains of the industrial revolution, not to be repeated. But what if some of the core features of those events are actually part of a cycle? Here's a sketch of how that cycle might work:

Phase 1: Technological Change. A huge burst of new stuff gets invented. Growth accelerates. 

Phase 2: Globalization. New tech and growth create new global supply chains. Trade and migration accelerate.  

Phase 3a: Inequality. New tech and globalization offer lots of opportunity for rich people to deploy their capital. New supply chains, products, and markets allow entrepreneurs to evade incumbents, vested interests, and governments. First movers make fortunes. Rich people deploy their wealth to restrain government attempts at regulation and redistribution, to keep the party going. Meanwhile, workers are forced to compete with foreigners and immigrants, and are also forced to pay the costs of reskilling in response to tech changes and globalization. Widespread inequality results.

Phase 3b: Cultural Change. New economic opportunities allow previously disempowered groups to gain power and status. Tech disrupts traditional family structures. Culture changes rapidly.

Phase 3c: Financialization. The need to finance new tech industries and new global supply chains expand the size of the finance sector. This results in large asset bubbles.

Phase 3d: Geopolitical Shifts. New supply chains and new tech mean some previously poor countries are now able to become rich. With wealth comes power. New great powers destabilize the geopolitical order.

Phase 4: Rise of Extremism. Economic inequality precipitates the rise of "leveling" (leftist) movements. Anger at cultural change and fear of competition with immigrants, mixed with displaced anger over inequality, precipitate the rise of reactionary (rightist) movements. Rightists and leftists feed off of each other, each portraying the other as an existential threat in order to frighten the populace into turning to the opposite extreme. Extremist politicians abuse veto points in political systems to paralyze governments and make countries effectively ungovernable.

Phase 5: Economic Slowdown. The collapse of a global bubble (from 3c) begins a protracted worldwide economic slowdown. For whatever reason - overhang of debt? extrapolative expectations? hysteresis? secular stagnation? some weird disruption to trade networks? - the economy does not recover quickly to previous growth rates. Because of extremist control of veto points, policy is unable to respond to the slowdown. Centrists on both the left and right are discredited and toppled. 

Phase 6: War. Extremists may fight each other in civil wars. Alternatively, geopolitical disruptions may lead to international conflict between new and incumbent powers. Extremists push their governments toward fighting external enemies, assassinating or toppling moderate leaders who refuse to fight. If a country is too weak to fight external enemies, or if no such enemies are close by, civil war results instead.

Phase 7: New Order. Out of the chaos and destruction of the wars emerges a new stable geopolitical order. Left-right extremist conflicts cause society to be exhausted by violence, and moderates slowly return to power. The exigencies of war cause governments to reestablish control over their economies, creating a new set of vested interests and protected incumbents. Inequality is dramatically reduced by destruction of wealth in wars. New incumbents provide a new "social model" that creates economic security for the masses.

This is basically a description of what happened in the late 19th and early 20th century, along with a number of assumptions about why it happened. Obviously there will never be enough data to confirm or refute this complex, slow, and sweeping of a theory - not in our lifetime, anyway. 

But it's interesting to think about recent events as possibly corresponding to this sort of cycle. Here's how the modern world fits into the pattern:

Phase 1: Technological Change. The IT revolution, computers, the internet, automation, mobile communication.

Phase 2: Globalization. The huge wave of global growth between 1990 and 2008. Globalized supply chains. A huge Latin American immigration flow into the U.S., and a huge Middle Eastern immigrant flow into Europe.

Phase 3a: Inequality. Rising income and wealth inequality everywhere. Stagnating wages in rich countries. An explosion in the number of billionaires. Soaring college tuition as workers desperately try to get skills. 

Phase 3b: Cultural Change. Greater economic opportunity and equality for women, due to the service economy. A rise in divorce and single parenthood, and a drop in marriage. Sex culture spreading via the Internet. The decline of religion.

Phase 3c: Financialization: The explosion of financial profits and output as percentages of the total.

Phase 3d: Geopolitical Shift: The rise of China and the recovery of Russia, and (most importantly) the de facto alliance between the two.

Phase 4: Rise of Extremism. The steady polarization of American politics. Skyrocketing use of the filibuster. The Tea Party. The debt ceiling crisis. Trump. Sanders. Fox vs. MSNBC. Le Pen. The British National Party. Syriza and Golden Dawn. The Zaitokukai. Campus anti-speech movements. Online wars between leftist "SJWs" and rightists (GamerGate, etc.). The normalization of the terms "fascist" and "socialist". Illiberalism on both sides of the political spectrum.

Phase 5: Economic Slowdown: The 2008 crisis and the Great Recession, the Euro crisis and the China slowdown and the emerging markets slowdown. 

Phase 6: War. Let's hope not...

I know this big sweeping theory, like all such theories, is untestable hand-waving and blatant overfitting. But it's kind of interesting, isn't it? And also disturbing.