Maths in Economics and Global Calamity
This morning I was reading some of our assigned articles for today’s International Monetary Relations class and came across this quote from Robert Skidelsky, the famed biographer of John Maynard Keynes. It struck me as essentially a great illustration of why I am at the Korbel school, and why you might want to consider being here too.
Under a heading “Towards a New Economics”, Skidelsky writes of the tension between Keynesian and Neoclassical economic theory…
“Keynes claimed his theory was more ‘general’ than classical economics because it encompassed a variety of economic situations exhibiting different states of knowledge.The question is: how central is the Keynes case? If the capitalist growth engine is subject to irreducible uncertainty then its mediocre performance and frequent breakdowns are explained.
“If, on the other hand, uncertainty can be plausibly modelled as an information problem, to be overcome by learning and by more efficient data processing, then Keynes’s case is marginalised, and the classical theory is reinstated as the central case.
The comeback of classical economics consisted in marginalising the Keynes case, and reinserting its own theory of the self-regulating market based on ‘perfect information’ as the ‘general case’.
The breakdown of the self-regulating market in 2007–8 suggests to me that Keynes’s theory is the ‘general’ one. What would an economics which takes uncertainty seriously look like?
The fundamental issue involves the role of maths in economics. The older generation of economists used maths for a strictly limited purpose: to make more precise their intuitions about the real world, not to create an axiomatic system whose virtue lay in its unrealism.
There has to be a return to an economics that allows room for explanations of economic behaviour that cannot be expressed mathematically.”
Essentially this quote not only has a lot to do with why the global economy is where it is today (in the midst of the Great Recession, brought on by the collapse of the financial system in 2008), but also with why the GFTEI program exists and why I, someone who comes from a non-quantitative/math background, hope I can make a contribution to economic development in the future. When I first got my acceptance to the Korbel school, I was worried that as a non-mathsy person (to use a technical term) I would not have anything to contribute to the field of international economics – trade, finance, etc. However what I had hoped, and what has turned out to be the case, is that you CAN understand these theories and arguments without being a math major, and you can contribute to the field without writing in mathematical equations.
In fact, as Keynes would argue, you can contribute more, because in doing so you may be willing to consider aspects of what drives the global economy (like the irrationality and herd behaviour of us humans who act within it) that can have a MAJOR impact on outcomes – the lives of you, me and the billions of other people who we share this world with. These are aspects of the human experience which the events of 2008 have made it all the more difficult for neoliberal economists to disregard, as they seek to push their free market agendas. That is not to say that they won’t continue to try…which is why those of us who can look at issues from the perspective of international political economists who bring to bear insights such as the role of power, psychology and from other social science traditions must keep doing what we’re doing.
You could even say the possibility of minimising the chance of another great global calamity depends on it!
P.S. And by the way, that unwieldy comment from Skidelsky about “older” economists (I am not sure if all neoclassical economists are really old) using maths in their economics to “create an axiomatic system whose virtue lay in its unrealism” is essentially what NPR is alluding to in this headline from its article today about the awarding of the Nobel Prize to a pair of economists who “actually solved problems in the real world”. The problem is that far too many economists have created elegant mathematical models to illustrate how X leads to Y, but failing to recognise that there’s a whole lot of GREY FUZZINESS in the middle where real life kinda intervenes and which often causes their models to fail catastrophically).