[zissou]

There are some truths in this article -- for example, it is generally true that economics PhDs don't have a hard time finding jobs. Don't want or can't get an academic job? No problem, there are plenty of consulting/industry/government jobs to go around for economics PhDs.

I'm an economics PhD dropout (after 2nd year) from a top ~40 program. Unlike the authors school, my former PhD program did not have the prestige of his top 10-20 school. I left my program because I didn't have a research match with my professors. Now I'm a computer programmer at a top ~1-5 ranked school and I'm infinitely happier than I was in graduate school. I may eventually go back for a PhD, but it will most likely be in a business school rather than an economics department because I enjoy applied work more than theory.

The main ridiculousness in the current coursework taught in most economics PhD programs is the macro course (e.g. freshwater/Minnesota macro). DSGE (Dynamic Stochastic General Equilibrium) is just stupid. For the uninitiated, here is why DSGE exists and what it means: A while back there was this thing called the Lucas critique, which was the observation that the models used in microeconomics and macroeconomics are very dissimilar -- that is, micro models say 1 agent will make a certain decision, so why isn't it that all agents will make that decision? Macro theorists took this criticism way too seriously and decided that their models needed to have micro foundations, hence giving rise to the macro modeling technique known as DSGE. How does the typical/introductory DSGE model work? It goes something like this: at the beginning of time, everyone in the world meets in a parking lot. At the meeting, they decide on the price of all K goods in the economy at all T periods of time by assigning a present value to each good at each period of time. Once all the prices have been decided, the world starts. That is the gist of this model, but if you want to read more about how silly it is, look up the idea of a representative agent DSGE model.

Anyways, my point here is that depending on what you want to do with an economics PhD, it may or may not be a waste of time. For example, if you study micro and econometrics and emphasize in industrial organization + game theory + experimental, you will make a great candidate for a cushy research scientist job at one of the big tech companies. If you study macro, well, you'll make a good candidate for a job.... doing macroeconomics?

TL;DR If you're going to do economics, don't do macro.

[jonnathanson]

"If you study macro, well, you'll make a good candidate for a job.... doing macroeconomics?"

There's a damned good living to be made as a macroeconomist in D.C. The bar for intellectual rigor is pretty low, and you're basically a lobbyist/speechwriter masquerading as a "policy advisor." It's the sale of your soul, but the price can be attractive.

Alternatively, there are some very handsomely paying "life of the mind" roles available at the think tanks. Of course, this stuff is politics at its most base and animalistic, and so your advancement is 100% predicated on playing the game of thrones. (The modern-day think tank is a lobbying organization given a euphemistic name.)

[pseut]

A few nits to pick:

* Macro's different than micro in that it's the predictions of the models, rather than their intellectual coherence, that matters.[1] They're obviously simplified because otherwise they're intractable. Even now, the emphasis isn't going to be and shouldn't be to make the models "more realistic," it's to make the models more accurate so that they can explain interactions between the economy and the financial sector better. The person or people who improve these models will probably win a nobel prize in ~30 years, so there are strong incentives w/in the discipline to get there.

* The Lucas Critique is the macroeconomist's way of saying "correlation is not causation" -- patterns that you observe under one policy regime may not hold up if you change the policy. It has very little to do with going from one agent to many or partial to general equilibrium.

* The private sector version of "doing macroeconomics" is "work for a bank" or "work for a hedge fund." I've heard it pays pretty well.

[1] Yes, their predictions before and during the financial crisis were shit. That's a valid but separate criticism.

[agravier]

Isn't your criticism of DSGE a little too easy? I don't see the silliness.

Here's my understanding (I am not an expert): DSGE is designed to give an approximate response to exogenous shocks for NL models. For that, it needs to start from an equilibrium.

You seem to say that shocking from an equilibrium is silly. Can you explain me why? I wonder what alternative solution you have in mind that could improve DSGE.

[zissou]

The underlying reason I think most DSGE models are absolute hogwash is that they do economics backwards. Economics is supposed to test theories against data. Instead, in the world of calibration in macroeconomic models, the creator of the model is now testing data against theory by tuning parameters to values they think are good. It is completely backwards.

While I appreciate the attempt to make macroeconomics more computational, I believe DSGE goes about it in the wrong direction. In an ideal world, I'd like to see models like the Leontief Input/Output model come back to fruition. In Leontief's model (which is often given as an example in many undergrad linear algebra classes), the economy is divided into many sectors. Data is organized on each sector to estimate its influence on other sectors. In an age where data is so vast, I just don't understand how one can decide that building deeper macro theories is a good idea. We need better empirical models, not better theoretical models (we have enough of those).

[thomaspaine]

>in the world of calibration in macroeconomic models, the creator of the model is now testing data against theory by tuning parameters to values they think are good. It is completely backwards.

This is a little inaccurate, the purpose of these macroeconomic models is either to make future predictions or run simulations to see what happens when exogenous shocks occur. They're not "testing data against theory", the data is used for parameter estimation and then verifying the accuracy of the models. It's actually very similar to the way certain AI models are developed and trained.

I do agree that these models are usually pretty inaccurate and somewhat useless though.

[agravier]

OK, thanks for the pointer to Leontief's model. I'll pile that on my reading backlog :)

[notahacker]

The main issue with DSGE models is that their simplifying assumptions make them useless for prediction: they replaced essentially atheoretical time-series models with hard, unrealistic theoretical assumptions about agent behaviour (over)fitted to time series and gained only a veneer of sophistication. Arguably no representative agent is better than a badly specified agent.

As an intellectual exercise to show that (for example) menu costs or nominal wage rigidities or technology shocks alone could have the economy's accounted for a shift from a [purely theoretical] equilibrium over a time period they're very interesting. For identifying which aspect contributed most towards economic change they offer little, and as a policymaking tool they're actually worse than useless since the models are generally built on the economists' assumptions about agents' response to policy and fitted to the data to justify those assumptions, rather than using the data to understand how responsive, rational and optimizing agents actually are. As such, their forecasting performance isn't very good either...

[pseut]

Do you know about the recent papers using DSGE models as priors for time series models? e.g. section 4.7.3 here:

http://economics.sas.upenn.edu/~schorf/papers/bayesian_macro...

(this is the closest I could find to a self-contained link, sorry). This stuff's not great, but I don't know what you mean by "useless for prediction". And, given a model, it's pretty trivial to figure out which shocks contributed when; this is the whole point of Impulse Response Functions, variance decompositions, etc.

I've said this elsewhere on the page, but I'll repeat it here: this stuff isn't popular because it's logically airtight and compelling, but because it seemed to have done pretty well empirically. So the criticism that dsge models are unrealistic isn't very interesting; everyone knows that already, especially the people who use the stuff (for the most part. I'm sure there are some dsge truthers too). If anyone has an approach that works better empirically at addressing core macro questions, especially the newly important interplay between the real economy and credit markets, this would be a great time to put it out there. There are a lot of people paying attention.

[gph1]

Here's one: http://www.kickstarter.com/projects/2123355930/minsky-reform...

[fnayr]

That's why you go to Caltech (no macro).

[ekm2]

Do you know of programs other than Caltech that have no macro?

[zissou]

University of Arizona