A measure of someone’s ignorance

Wow, there is something about John Quiggin this week that is bringing out the ignorance in lots of people. First, it was Stutchbury at The Australian. Now, it is an economist by the name of Stephen Williamson who is at Wash U. He writes:

Roughly, Quiggin is the Australian farm team in the Krugman/Thoma/DeLong league.

Now I actually have little problem with Williamson’s attempt to critique Zombie Economics. What I have a problem with is belittling its author in this derogatory matter. If Williamson’s critique was really substantive he wouldn’t have to stoop to this. And he reveals ignorance further with this statement:

What is Quiggin’s claim to fame? His early work is an odd mix of agricultural economics and decision theory, but he seems to have distinguished himself mainly in public policy.

Well I think we can safely say this is a ‘glass houses’ moment. Here is John Quiggin on Google Scholar. Here is Stephen Williamson. I guess founding a field is not distinguished enough for some people.

4 thoughts on “A measure of someone’s ignorance”

  1. No, I have problems with his review, too. Williamson says that EMH has no implications, and so cannot be wrong, which is a pretty neat way of defending your point of view. Except Quiggin spends quite a bit of time, both in his blog and in the book, arguing that EMH does have implications, and that these implications are wrong. 

    The review is just plain lazy. 


  2. It does remind me of the US wild west where the well known reputable sherrif became a magnet for every no-name to try his luck! My (rare) criticism of Quiggan goes to his political judgments where his heart rather than his head can occasionally  be ascendant!


  3. The Structure of Scientific Revolutions John Quiggin in an Australian economist. He made his name in the early 1980s in an esoteric area called decision theory. The Econometrics Society made him a fellow on the basis of this work, a distinguished award. He writes a blog, which has many devoted followers. The book is primarily about macroeconomics, however, which is not his area. Asking Quiggin about macroeconomics is like going to a podiatrist for your headache: it’s the wrong end of the body. The chapter on Dynamic Stochastic General Equilibrium modeling (DSGE modeling) is a good example of Quiggin’s lack of expertise about modern macroeconomics. He states that one of the oddities about DSGE modeling is the representative agent paradigm. This is an abstraction where the decision making of one representative consumer/worker is taken as a stand-in for the millions of people living in an actual economy. This abstraction was employed in a famous 1982 article by Kydland and Prescott. Finn I. Kydland and Edward C. Prescott justly won the Noble prize in 2004. The stand-in consumer was abandoned in 1994 in important work by the late and great economist S. Rao Aiyagari. Every graduate student in macroeconomics today knows the Aiyagari paradigm. This work is not mentioned in Quiggin. Nor is the celebrated work by Mortensen and Pissarides, done during the late 1980s and early 1990s, on modeling unemployment. Dale T. Mortensen and Christopher A. Pissarides won the 2011 Noble prize for Economics. There has been a flurry of work in macroeconomics embedding the Mortensen and Pissarides framework of unemployment into an Aiyagari/Kydland/Prescott style DSGE model. An early example is the research by David Andolfatto in 1996. Interestingly, Noble Prize winner Paul R. Krugman’s latest research with Gauti B. Eggertsson borrows from Aiyagari (they cite it) and is essentially a dynamic general equilibrium model, albeit with a very Keynesian flavor. Quiggin is really out of touch with modern economics. The trouble with Quiggin’s book is that to the non-economist his little bit of knowledge will sound authoritative. Like an undergraduate’s essay, many of the bits and pieces are indeed correct. But, also like many undergraduate essays, it shows little understanding about modern macroeconomic, just a superficial dropping of names and theories. Beloved Albert Einstein, a hero for scientists, didn’t like quantum mechanics and argued against it. Perhaps it was because of the escalation of the mathematics required to understand the quantum world. Some people say that Einstein wasn’t good at math. The mathematics in his papers is easy for a modern economist or physicist to understand–look them up on the web. Time has advanced mathematical training among scientists. Anyway, this was one battle Einstein lost. When Keynesians displaced the classical economists in the 1940s, 1950s and 1960s the latter cried out about the mathematics (calculus and statistics) the former used. Keynesians, such as the Noble prize winners John R. Hicks, Lawrence R. Klein and Paul A. Samuelson, were at the forefront of technique in their day. And now it is the displaced Keynesian crying about the new math (dynamic programming, numerical analysis, stochastic processes) used by the neoclassical economists ushered in by the Kydland and Prescott revolution. Maybe the table will be reversed tomorrow. Who knows: if you could forecast this you could be a Noble Prize winner. This is the process of science: New ideas don’t come easily and old ones are hard to displace. Quiggin sounds like an old man whining about the young Turks.  Professor Quiggin here is a question. Rather than solving macroeconomic models on high-speed computers to simulate the effects of government policies, what do you propose? (i) We input economic data streams and policies into your quick-witted brain and do what comes out. (2) We use a divining rod. (3) We make stuff up. Yeah, the alternatives don’t look so good to most of us.


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