It still amazes me that people unironically cite these Taleb quotes without addressing how plainly neurotic these comments are. Does this increase or decrease your prior belief in his actual ability to carefully read, and then entirely dismiss, an economics academic literature that involves nearly ten thousand active young academics with backgrounds from all over the world, an undergraduate education that ranges from mathematics to physics to philosophy, and markedly diverse political beliefs, and who mostly work on topics that have nothing to do with financial math?
Or does it perhaps tell you that this top b-school PhD graduate, who
1. works on similar financial-math topics as the people he viciously smear in the media
2. publishes in the same journals that econ/finance academics publish in
3. had key results inspired or derived from previous economists including Daniel Ellsberg (who, by the way, is a national hero)
4, and was repeatedly hired by top econ/finance departments, but was never able to keep the same appointment for more than a few years
perhaps has deep-seated personal, psychopathic issues that prevent him from simply getting along with other academics in his own discipline, and that the academic world wasn't stacked against him and his insights?
and perhaps his actual academic analysis don't give you the sweeping indictment of his fellow academics that he'd have you believe in his bitter tirades?
and maybe you shouldn't take him that seriously when he periodically goes into his online rants and show a vicious tendency to smear and destroy any individual that's responsible for a perceived slight on him?
His point is that policy data, unlike most sources of data in the sciences/computer-science world, is contaminated by behavioral adjustments. This is a point that was first brought up by the famous (and frequently misunderstood) Lucas critique. https://en.wikipedia.org/wiki/Lucas_critique
And the central tenet of the critique has been reaffirmed by decades of meticulous "natural experimental" studies and small-scaled field experiments which show that real-world economic causal effects do not often correspond to observational data on policy changes.
Believe it or not, both of you, there are plenty of competent economists working on that exact methodological problem and resolving other statistical issues that are rarely encountered in non-behavioral sciences. James Heckman's works on this topic have been so widely influential, and lauded, that his papers are now frequently taught as canonical texts in graduate-level statistics courses. And this is a guy that started out only wanting to estimate returns to early-childhood education and basically carved out the best way to do it over 10 years.
The language is clear, the use of statistical theory and technical concepts is brief but rigorous (the proofs are on p.54 onward), and literally all 80 pages are devoted to reviewing other recent papers on the best statistical methods to analyze policy data towards making accurate causal inferences.
Realize the sheer size of that body of work? Maybe, just maybe, there are good academics in every discipline who aren't hopeless idiots that fit into your grandiose stereotypes. And maybe a random one-liner "omg they should look at policy data" isn't exactly a well-informed criticism in the context of the sheer amount of contemporary empirical work that you've never heard of in a discipline that you aren't familiar with.
Yes, "quants" tend to have undergrad math/physics backgrounds, but "quants" aren't the ones writing academic papers in the Journal of Finance. You, and many others in this thread, seem to have a painful lack of awareness that there are things called PhD programs, and that they select and train students to specifically do research. Here's an analogy: a random comp-sci undergrad/master's isn't going to be publishing in a conference any time soon. Most of you have no chance of getting into a PhD comp-sci program, just as most random econ students have no chance of getting into a PhD econ program. Both of these select heavily from mathematics.
Here's the editorial board of the Journal of Finance:
You can feel free to check their affiliations for yourself, but almost every single person has a PhD in Economics or a PhD in Finance/Financial-Economics from a top department. PhD Finance programs are structured like PhD econ programs (you take the usual micro/macro/metrics), and were historically rooted in economics departments. And for what it's worth, almost all of them will have a bachelor's in mathematics, or a master's in mathematics, or in the case of international students, a master's in economics.
The topic of this thread is about academic economics, yet you and everyone else are attacking it by citing the irrelevance of undergrad economics in the U.S.. Which we're all painfully familiar with. But believe it or not, the best aspiring comp-sci academics in the United States rarely take a full major of comp-sci courses at the undergrad level either, because U.S liberal arts majors are frankly geared towards students who have no interest in academia. This does not imply a single thing about graduate-level comp-sci, economics or finance research.
You seem to at least have some personal experiences/familiarity behind your criticism, unlike almost everyone in this thread. So here's a chance to substantiate your claim. Here is a paper that was recently published in the Journal of Economic Theory https://dl.dropboxusercontent.com/u/17516137/RapidWeaverSite...
This was a co-authored publication of an economist and a political scientist (at the University of Rochester). It's one of their several co-authored pieces; and it was published in a good field journal, but not a top general-interest journal. It has so far received a couple of cites from papers on the same topic. My point is, this paper is fairly "standard" for contemporary economic theory.
It also happens to use a decent amount of measure theory.
Now, I will personally venmo you $200 if you are able to find a single mistake or "abuse" of measure theoretic concepts in that paper in the following sense: a measure-theoretic theorem, definition, or proof technique was unnecessary for mathematical purposes, and you can demonstrate why that's true by writing an alternative proof, with the same generality but without such a concept.
I'm not baiting you, I'm genuinely curious to see if you or anyone else in this thread can do it, because I had taken plenty of measure theory in my PhD days, and this paper's usage of it seems perfectly on point to me. I'm also using it as an example because the authors' language is very clear and meticulous, and you shouldn't have trouble accessing that paper without knowing economic jargon.
I can also link you a few other random economics papers if you want. Alternatively, you could admit your disparagement of economists' intellectual ability, and intellectual honesty, was perhaps misplaced.
Or does it perhaps tell you that this top b-school PhD graduate, who
1. works on similar financial-math topics as the people he viciously smear in the media
2. publishes in the same journals that econ/finance academics publish in
3. had key results inspired or derived from previous economists including Daniel Ellsberg (who, by the way, is a national hero)
4, and was repeatedly hired by top econ/finance departments, but was never able to keep the same appointment for more than a few years
perhaps has deep-seated personal, psychopathic issues that prevent him from simply getting along with other academics in his own discipline, and that the academic world wasn't stacked against him and his insights?
and perhaps his actual academic analysis don't give you the sweeping indictment of his fellow academics that he'd have you believe in his bitter tirades?
and maybe you shouldn't take him that seriously when he periodically goes into his online rants and show a vicious tendency to smear and destroy any individual that's responsible for a perceived slight on him?