What Should I Teach First-years?

NOTE: The Growth Economics Blog has moved sites. Click here to find this post at the new site.

I’m doing a little post-mortem on this semesters first-year graduate macro class. I’m thinking about what I should be teaching in this course. The big meta-question is what is the right kind of material to be teaching? I see two perspectives here:

  • Teach the big questions. They need to understand the open issues for macroeconomics, and then can be introduced in 2nd/3rd year to models/techniques that are suited to talking about those issues. A course like this would emphasize intellectual history more than specific mathematical techniques. The problem is that we don’t necessarily screen out people who cannot do the math at a sufficiently advanced level to try and *answer* any interesting questions.
  • Teach the techniques. My course, and most 1st-year courses, lean heavily this way. Once they have some of the “language” down, then we can talk coherently about the big questions with them in the 2nd/3rd year. The problem with this course is that we don’t necessarily screen out people who cannot understand what it means to ask an interesting question. The danger is we get optimization robots, not researchers.

Maybe I should just trust that PhD programs have evolved towards the right solution, and focus on techniques. The cost of having someone incapable of using techniques is so high later on that it must be avoided at all costs. But there is a part of me that feels like techniques are always something that can be learned by force of effort later on. Screening out people who can’t think without being given a specific math problem to do might be more useful.

Of course, if one does want to teach “big questions” to first-years, what are they?

For people who’ve done PhD’s, or are doing them now. What do you *wish* you had learned in first-year macro. What would have been useful?

I am far too lazy to try and think of this all by myself, so I’m posting it here in the hopes that smart people will offer up some suggestions either way. Any ideas are appreciated, will be stolen without shame, and will probably sit unused for years as a scribbled note to myself under a pile of other things on my desk.


7 thoughts on “What Should I Teach First-years?

  1. Professor,
    In my opinion it’s important to understand the bigger picture more than the math in the first year. As you rightly said, one can learn the math at any point. In my case, I realize the importance of coming up with the right questions as against coming up with techniques to solve them. You could argue that there are precedents to math techniques that one can resort to, but the concept of thinking is more abstract and requires skill. Of course, my opinion may be biased by the fact that I am better in math than coming up with bigger questions.

  2. As someone who knows very little I bought an economics ebook by T Taylor to get precise definition of terms. It would seem definitions have to be first then history and techniques in parallel.
    Perhaps your question has behind it the Mankiw and Manchester things. But I would assume more students know less about definitions than is realised and ignore the people who want to change the world. They can change the world on the second year course.

    • Fair point (and sorry for the long delayed reply). We perhaps take for granted that everyone is using the same terms/concepts. So a common language is crucial. But at the same time, you have to motivate *why* that language is worth learning, no?

  3. I think a great deal of this comes down to how one views the science of economics.

    If it is thought of on the model of the physical sciences, then a focus on techniques in introductory courses might be entirely appropriate. It seems to be in nature of these sciences that there is little reflexivity possible or necessary with regards to their aims, objects, and epistemologies. The fact that these priors aren’t generally subject to serious, non-technical doubt, is part of what we understand these sciences to be–part of the way their consensus-supported findings claim our acknowledgement, when we are not ourselves in a position to make a technical assessment of them.

    As a non-economist, it’s my impression that a good many (probably most) economists think of their own fields (macro included I imagine) as being analogous to this. But if one thinks of economics as a social science (what the continentals call a ‘human science’) then it’s not at all clear the techniques are the right place to begin. Because it’s characteristic of the social/human sciences to be in internal disagreement, more or less permanently, about things as fundamental as the aims, objects, and epistemologies of the field in question.

    Now I know that a lot of social scientists desperate wish this weren’t the case. And when social science writing and teaching does bother to acknowledge these chronic controversies, it seems to me that it’s often to sweep them under the rug as rapidly as possible, so that the business of a ‘normal science’ can be gotten on with.

    This has always seemed to me an absolutely fatal mistake in the social sciences. The sciences in which such questions really are more-or-less settled, and in which instruction really can therefore safely and productively begin with techniques, are not subject to this anxiety (almost always brushed aside though it is) about how and where to begin.

    The fatal mistake, it seems to me, lies in thinking this makes those sciences *better* (more coherent, more systematic, more parsimonious, what have you) than the ‘softer’ sciences, and seeking to emulate their path to knowledge. Surely, the social/human sciences don’t have this unending, and unendingly repressed, problem of beginnings because they are somehow technically weaker, epistemologically inferior, more disorganized. They have it because of their subject matter–because of what they are sciences *of*.

    Because the human situation, in all its radical indeterminacy, its unending reflexivity, its perspective-and-value entangled epistemologies, is the very thing we want these sciences to help us understand. Why do we imagine our tools for studying such phenomena as these, which is to say our tools for self-knowledge, are going to be capable of seeing around the corners of this situation, which is after all our situation? I think we need a different way of dealing with these puzzlements, than trying to flatten them with the force of some crystalline pure ideal of what knowledge of humans *must* be.

    • Very nice response, thanks. The tension for me as an instructor is that while I might want to think more broadly about the right way to train social(human) scientists, I have some obligation to train these students to succeed in the field as it stands now. You don’t want to send your grads out there without the expected package of knowledge. Even if you think that package should be different.

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