This week on Econtalk, Russ Roberts and John Papola discuss their most recent economics rap video about a fictional debate between F.A. Hayek and J.M. Keynes entitled “Fight of the Century”. You can find the video here. An earlier one also featuring Hayek and Keynes was called “Fear the Boom and the Bust”. Both of the videos are entertaining and educational. If you don’t know anything about Hayek, Keynes or macroeconomics, you can learn quite a bit just from these videos. Although, Roberts and Papola are strong proponents of Hayek, they try their best to represent Keynes fairly. I will not address the economics arguments directly but rather comment on the philosophy of Hayek that motivates his ideas.
Hayek is a hero of libertarian leaning economists such as Roberts. His main thesis is that the economy is far too complex to ever be understood by economists so any attempt at economic manipulation by the government such as the stimulus is misguided at best and dangerous at worst. He claims that it is always better to just let the free market play out. An Econtalk episode on Hayek can be found here and these ideas are summarized in his Nobel address found here. In some sense, Hayek was ahead of his time in recognizing the importance of complex systems as a field into itself. On the other hand, he takes a very defeatist attitude towards it. I have argued before (e.g. see here) that a purely reductionist approach is a futile approach to understanding complex phenomenon like biology or economics. However, that doesn’t imply that some form of systematization or quantification is impossible. For example, consider water flowing in a pipe. If the velocity of the water is low then the water will flow smoothly. However, when the velocity is fast enough the flow will become turbulent. We can even calculate when the instability transition will occur. Although it is completely futile to predict the trajectories of water molecules in a turbulent flow, there are statistical invariants that are well behaved. Hayek claims that even a statistical theory of economics is impossible because economics is comprised of heterogeneous players so there is no natural way to average. However, he makes such claims without any proof. It may be true that there are no statistical invariants in economics but that is a question that can at least be studied. Hayek doesn’t even believe that economics measures like the unemployment rate is of any use because that knowledge cannot be used in any useful way.
My approach to complex systems is based on two observations. The first is that we can only have some quantitative control of a system if it is smooth enough so that small perturbations generally lead to small changes in the system. We can handle instances of where small changes lead to big changes (e.g. bifurcation or critical points where the qualitative behavior of the system changes drastically, like a phase transition between liquid and gas) if they are not too close to each other. Hence, I only try to model something that behaves relatively nicely. (I’ve argued before (e.g. see here) that physics could be described as the science of model-able things.) The second observation is that most functions, no matter how badly behaved, can be made smooth if you integrate over it enough times. If a system is very complex, I look for integrated or averaged quantities that seem to behave better. For example, while the dynamics of the molecules in a gas are buzzing around in a haphazard unpredictable way, the temperature of the gas is well defined and can be described quantitatively. Although human metabolism is highly complex, it still obeys the conservation of energy at a global level and I can use that fact to make quantitative predictions about the response of body weight to changes in food intake. So my take on the stimulus is that it is plausible that increasing spending can increase the velocity of money flow in the economy and kick us out of a recession. While I doubt that we will ever be able to predict exactly how well a stimulus will work I think we can at least make some probabilistic predictions about the effect size.