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Topic bleg: Macro 1

April 4, 2011

We’ll be holding tutorials on Macro 1 shortly. Please comment below with specific questions and/or topics that you would like to see covered.

(note:  the agenda is already set for your Macro 2 tutorial, so there’s no point mentioning that here)


Topic bleg: QM1 & QM2

April 4, 2011

We’ll be holding tutorials on QM1 and QM2 shortly. Please comment below with specific questions and/or topics that you would like to see covered.

The story of economics via Rob

March 18, 2011

Rob correctly notes that the blog is getting a bit thin and sends in the following:

This is the first of a 3 part series on BBC Radio 4 on the ‘story of economics.’ It’s pretty good – he goes to Athens, the London Zoo and speaks to Rowan Williams (who’s one of my favourite people  to listen to).  And also says the following which is quite good:

“But how many of us, like John Kay, are prepared to say that morality might cost us? Because here’s what nags at me.  I’ve seldom met anyone who thinks that the state should help people more, for moral reasons of course, who didn’t also argue that the economy would be better if it did.  And I don’t think I’ve ever met a believer in the morality of self-reliance, keeping the state out of our lifes, who didn’t argue with uncanny conformity that economic prosperity compells us to cut government. Our morality always seems efficient.  Funny that.  My hunch is that this alignment explains a lot – inside economics, even when it pleads dry utility, is often a moral instinct trying to get out.”


February 5, 2011

When the last Superman film came out, Marginal Revolution had a post suggesting that Superman is using his time inefficiently, since most petty crimes are just transfers anyway, and he isn’t doing much to increase the social surplus. The last micro tutorial made me think I should really explore this issue with you guys–would that I could put it on the exam.

What would a central planner do with Superman? Tyler offers four suggestions:

1. Become a research scientist.

2. Collect data for the Fed.

3. Fly around and tell people — politely but very pointedly — when they should accept lower nominal wages.

4. Perform amazing stunts on TV, become a big celebrity, and then preach the virtues of economic literacy; this is Dan Klein’s suggestion.

His commenters offer a few more jewels:

5. He should spend his non-work hours impregnating women, thereby enhancing earth’s human capital stock.

6. Enforce property rights and the rule of law

7. He should play for the Dallas Mavericks in the NBA Finals.

8. Clearly he should offer his services to the highest bidder. He could then not only exploit his comparative advantage (and using the efficiency of the price mechanism in his favour allows him not to have to figure this out; impresive computational skills not being one of his super powers as far as I know).

9. He could stop the Yankees from winning the ALCS.

There are more. Any thoughts?


Search Models

February 3, 2011

The Work Behind the Nobel Prize” is a blog post by Edward Glaeser that gives a good intuitive explanation of the search models of unemployment that Sevi will teach tomorrow or next week.


February 2, 2011

Andrew Gelman (who writes a stats blog I’ve previously praised) has a post called “How to think about instrumental variables when you get confused” which some of you may find helpful. If you read the post, be sure also to read the last two comments (by Hal Varian and Andrew Gelman).

Edge: truth is a model

February 1, 2011

This is a very good argument for why we model:

The most common misunderstanding about science is that scientists seek and find truth. They don’t — they make and test models….

Building models is very different from proclaiming truths. It’s a never-ending process of discovery and refinement, not a war to win or destination to reach. Uncertainty is intrinsic to the process of finding out what you don’t know, not a weakness to avoid. Bugs are features — violations of expectations are opportunities to refine them. And decisions are made by evaluating what works better, not by invoking received wisdom.

These are familiar aspects of the work of any scientist, or baby: it’s not possible to learn to talk or walk without babbling or toddling to experiment with language and balance. Babies who keep babbling turn into scientists who formulate and test theories for a living. But it doesn’t require professional training to make mental models — we’re born with those skills. What’s needed is not displacing them with the certainty of absolute truths that inhibit the exploration of ideas. Making sense of anything means making models that can predict outcomes and accommodate observations. Truth is a model.