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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 a
by zissou 13y ago
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.
- agravier 13y agoIsn'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 13y agoThe 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).
- agravier 13y agoOK, thanks for the pointer to Leontief's model. I'll pile that on my reading backlog :)
- thomaspaine 13y ago>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.