Over the years I have seen some interesting work from Econ Journal Watch (EJW), but had not visited their actual site in a long time. In some ways the purpose of their site is the same as mine. I was surprised to notice they even have a similar logo. Theirs is of course related to their mention of journals, whereas mine is a reference to Keynes. As far as I can tell, and despite theirs being specifically an economic website, I could not find any reference to the Keynes quote that is the reason for my logo. Indeed, there are few references to Keynes on the whole site, which is not surprising given its Austrian economics leanings and what seems to be a close association with George Mason University academics. At any rate, the site has some excellent critical views on mainstream economics and I highly recommend it.
Seeing EJW gave rise to several thoughts on GMU, the Austrian School, statistics and academic debates as a source of knowledge.
As an undergraduate interested in economics I felt that mainstream economics made little sense. I looked to heterodox approaches to see if they were any better.
I did not find what I was looking for in Austrian economics but I did find that it has some very good criticisms of mainstream economics, especially the infatuation with mathematical modeling. Years before it was published Bryan Caplan’s excellent Why I am not an Austrian Economist was available online and probably has done more to highlight what is both good and bad about Austrian economics to a generation than any other single paper, and helped shape some of my early views on economics. (At the end of this post I provide a brief excerpt on the use of math in economics).
This brings me to my second thought: How debates such as those between mainstream economists and Austrians, even when both parties are wrong, are highly informative. Mainstream (and other) economists show the flaws, shortcomings, fetishes and blind spots of Austrians, but Austrians quite effectively helped do the same with the mainstream.
Similarly, I came more and more to see that there are fundamental problems with the way inferential statistics are often used in the social sciences. My understanding of the deeper problems with the application of inferential stats to economics came partly from reading debates between frequentists and Bayesians. Basically both schools of thought on statistics are correct in their critique of the other. The clearest writing on what is wrong with each came from the opposing school of thought. That is why Academic Scribblers seeks to document fully as many academic controversies as possible. They are highly instructive (besides the fact they can make for far better reading than the average textbook).
The final thought after looking at EJW – I remembered a fun article (The Secret of George Mason: What its Final Four basketball team and its unusual economics department have in common).on how George Mason became such an influential economics department so quickly from very humble beginnings – it was written at the same time that George Mason surprised everybody in basketball and made it to the 2006 NCAA Final Four.
"GMU has excelled on the court and in the classroom by daring to be different. Its basketball team and academic programs began with the (correct) assumption that they couldn't hope to compete against the top schools in their fields—say, Harvard Law School or the Duke Blue Devils—by directly imitating their methods…instead, GMU has hunted for inefficiencies in its markets. Coach Jim Larranaga follows the Moneyball model of recruitment: hunting for the undervalued players—the ones who everyone else thought were too short, too thin, or too fat—and then building them into a team.
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Among economists perhaps the strangest aspect of the prevalent insistence on mathematical and econometric modeling as opposed to simpler causal language is that the former have perhaps not been near as important to the development of economic theory as is commonly perceived. Discursive arguments rather than mathematical models were the basis for such important concepts as Coase’s theory of the firm, Mundell’s optimal currency area (OCA) theory, and the consideration of the market for ‘lemons’ in used-automobile markets which was the basis for the theory of imperfect competition by George Akerlof, all of which led to Nobel prizes in economics.
Economist Bryan Caplan lists ten of the most influential ideas of mainstream academic economics since 1949:
1. Human capital theory
2. Rational expectations macroeconomics
3. The random walk view of financial markets
4. Signaling models
5. Public choice theory
6. Natural rate models of unemployment
7. Time consistency
8. The prisoners’ dilemma, coordination games, and hawk-dove games
9. The Ricardian equivalence argument for debt-neutrality
10. Contestable markets
Almost none of these ideas originated with mathematical models, but instead through observation of the real world and/or descriptive statistics, intuition, and discursive arguments. ‘Out of the whole list, there are few plausible cases where mathematics was more than an afterthought: maybe idea #2, and possibly #3. Even there, intuition, not math, probably played the leading role.’ (Caplan 2003)
Caplan continues: ‘The contributions of econometrics to economics are similarly meager—particularly because econometrics has "crowded out" traditional qualitative economic history…When simple econometrics failed to yield universal agreement among informed economists, this merely provided the impetus for econometric theorists to supply increasingly complex estimators and other tools. Truly, this is a case of looking for car keys underneath the streetlight because it is brighter there. (Caplan 2003)[from Ballinger 2011]
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