Harvard's Greg Mankiw, author of the most popular college introductory economics textbook, is often regarded as America's econ teacher. He famously refers to his "Principles of Economics" as "my favorite textbook," and I must admit that it's also my favorite. It's written in a clear, explanatory style and covers the basics of most important theories in modern economics.
But Mankiw's book, like every introductory econ textbook I know of, has a big problem. Most of what's in it is probably wrong.
In the last three decades, the economics profession has undergone a profound shift. The rise of information technology and new statistical methods has dramatically increased the importance of data and empirics. This means that many professional economists are no longer, as empirical pioneer David Card put it, "mathematical philosophers." Instead, they are more like scientists, digging through mountains of evidence to find precious grains of truth.
And what they have found has often been revolutionary. The simple theories we teach in Econ 101 classes work once in a while, but in many important cases they fail.
For example, Econ 101 theory tells us that minimum wage policies should have a harmful impact on employment. Basic supply and demand analysis says that in a free market, wages adjust so that everyone who wants a job has a job -- supply matches demand. Less productive workers earn less, but they are still employed. If you set a price floor -- a lower limit on what employers are allowed to pay -- then it will suddenly become un-economical for companies to retain all the workers whose productivity is lower than that price floor. In other words, minimum wage hikes should quickly put a bunch of low-wage workers out of a job.
That's theory. Reality, it turns out, is very different. In the last two decades, empirical economists have looked at a large number of minimum wage hikes, and concluded that in most cases, the immediate effect on employment is very small. It's only in the long run that minimum wages might start to make a big difference.
That doesn't mean the theory is wrong, of course. It probably only describes a small piece of what is really going on in the labor market. In reality, employment probably depends on a lot more than just today's wage level -- it depends on predictions of future wages, on long-standing employment relationships and on a host of other things too complicated to fit into the tidy little world of Econ 101.
For academic economists, that's no problem. If existing theories explain only a sliver of reality, they simply roll up their sleeves and get to work. Many labor economists are now working on complex theories that model the process of employees looking for work and employers looking for people to hire. For professional theorists, empirical failures simply mean more work to do.
But for Econ 101 classes, explaining only a small slice of reality isn't good enough. If economics majors leave their classes thinking that the theories they learned are mostly correct, they will make bad decisions in both business and politics. We shouldn't train tomorrow's business elite to have faith in theories that have only a small amount of empirical success.
Another example is welfare. Econ 101 theory tells us that welfare gives people an incentive not to work. If you subsidize leisure, simple theory says you will get more of it.
But recent empirical studies have shown that such effects are usually very small. Occasionally, welfare programs even make people work more. For example, a study in Uganda found that grants for poor people looking to improve their skills resulted in people working much more than before.
This has big political implications. If we train tomorrow's business elites to think that welfare encourages laziness, they may block support for policies that really improve the lives of the poor -- and the economic productivity of the whole nation. But this is precisely what Econ 101 is now doing.
So what's the solution? Complex theories sometimes do a better job of explaining reality than simple ones, but these theories are way beyond the mathematical skill of most undergrad econ majors. A better alternative is to start teaching empirics in 101.
Current textbooks, including Mankiw's, almost all play down the role of data and evidence. They sometimes refer to the results of empirical studies, but they don't give students an in-depth understanding of how those studies worked. Yet this wouldn't be very hard to do. The kind of empirical analysis now taking over the econ profession -- often called the "quasi-experimental" approach -- isn't that hard to understand. Simple examples could even be done in the classroom, or as homework assignments.
In other words, the economics profession has gotten real, and it's time for Econ 101 to do the same. We now have an academic economics profession focused on examining evidence and an Econ 101 curriculum that focuses on telling pleasant but often useless fables. Econ education needs to get with the times.