A memory: Murray Weidenbaum

In grad schooI, I worked for Murray Weidenbaum, at the Wash U CSAB, as a research assistant.  He gave me a hard assignment, on the costs of trade barriers. 

I did the research, and wrote a draft. It took about a month. 

 

It came back completely covered with changes, amendments, cross-throughs, and requirements for more research. There may have been three or four sentences, total, in ten pages, that were unchanged. (This was 1982, in the days of pen and paper revisions).

 

I was disappointed it was so marked up, and I guess it showed in my face. 

Murray saw that, and laughed. "Look, Mike. This is fine. If it had been bad, I would've made some vague suggestions and told you it was good. That would have been the end of it. And the end of YOU, frankly. I'm don't have time to train RAs."

"Instead, this is a workable draft. Remember: busy people only spend time on good first drafts. You did a competent job, so I spent time on it. Now go finish it." 

He added me as a coauthor (second author, but still). And taught me that no first draft is any good. The GOAL is to have a first draft worth marking up so much that it looks like red spaghetti. That's actually what success looks like!

 

 

 

 

 

"pretense of knowledge + Math = Economics"

"Having proven the theory, both by stating it and imagining it to be true, I want to move directly to policy implications" ~ Zach Weinersmith







Kudos to you sir. Well done.

Marginal Revolution University

LeBron's plan for (voluntary) world dominion proceed apace.

With MRU

Also on facebook...
 

That's a lot of Bi Bim Bop!

Kudos to Thomas Sargent for landing a two year position at Seoul National University for an estimated $1,250,000 per year.

Economists can pull down 7 figures in total compensation when you figure in consulting and speech-giving on top of the academic salary, but this is the biggest salary+"research funds" number that I'm aware of in economics.

Trickle down, baby. Trickle down.

Hat tip to Daniel Lin

Contra the NY Times, Vector Autoregressions are NOT magic

In an interesting human interest story on the newest Econ laureates, the NY Times tosses this into the mix:

Mr. Sims developed a statistical approach called vector autoregression, or V.A.R. It enables the testing of cause and effect — whether, for example, the money supply is affecting interest rates, or vice versa. That is a crucial determination if economic models are to have any accuracy, as the Nobel committee has noted.

So many things wrong here. Lets try to unpack it.

First of all, causality requires identification. VARs do not provide any automatic or free identification. To do policy analysis with a VAR (as opposed to agnostic forecasting) one has to make the same type of untestable identifying assumptions here as one does in the older, explicitly simultaneous equation, Cowles commission approach.

The most common way of identifying a VAR (ordering the variables and performing a Cholesky decomposition) is EXACTLY the same as using exclusion restrictions to identify a system of equations. Other structural VARS do NOT remove the need for identifying assumptions. VARS are not a free lunch.

Second, if the article is referring to Granger causality, then Granger's 1969 Econometrica article predates the VAR.

Third, is causality (i.e. identification) crucial for economic models to have any accuracy? Well that depends on what you mean by accuracy. If you mean on target forecasts of specific aggregates, then no, identification is not really needed (VARS are great for agnostic forecasting of specific variables). If you mean being able to perform convincing counterfactual policy simulations, then yes, identification is vital (but the VAR doesn't give a free lunch here).

Don't get me wrong, I think Sims is *awesome* and well deserving of the Prize (Sargent too!!!), but VARS are not magic.