Paul Krugman vs. Mervyn King on Keynes
from Lars Syll
Most self-described Keynesians are Part 1ers. They don’t necessarily believe that workers and consumers are perfectly rational, or deny that sudden shifts in behavior can happen, but irrationality and volatility are at the fringes of their worldview.
King argues, however, that this is all wrong; he is, basically, a Chapter 12er, asserting that economic decisions always take place under conditions of “radical uncertainty”—ignorance about the future that can’t be quantified by probabilities, so that there is no such thing as optimizing behavior. People cope with this uncertainty by settling on “narratives” that are conventionally accepted at any given moment, but can suddenly change. And he urges economists to turn away from supply-and-demand-type analysis, which he calls the economics of “stuff”—as in markets for prosaic physical goods—in favor of the economics of “stuff happens.”
That’s not an unheard-of position, but it’s a remarkable one for an ex–central banker to take, let alone one who, in a former life, was a card-carrying mainstream economist. Why does he go there?
It’s not entirely clear, even though King spends a whole chapter explaining why radical uncertainty, not quantifiable risk, is the essence of economic life. Yes, economic forecasts are often grossly wrong; yes, even smart people often have far too much confidence in their ability to assess risks. Every serious economist knows this, yet most don’t consider it sufficient reason to abandon conventional tools of analysis. At most, it’s a reason to use them in the subjunctive—to analyze economic issues as if people were making reasonable choices, while being aware that they might not. What makes King decide that this isn’t enough?
Part of the answer seems to be the sheer scale of the misjudgments leading up to the financial crisis, with nobody in the financial sector even imagining that housing prices could fall so far. What’s odd, though, is that some economists using quite conventional tools—notably Yale’s Robert Shiller, arguably the world’s leading expert on bubbles—warned well in advance that housing prices were unrealistic and would fall to historically normal levels, which was what did in fact happen.
On this issue the self-proclaimed Keynesian economist Paul Krugman is simply wrong, and former governor of the Bank of England, Mervyn King, is right.
Well, as we all know, Paul Krugman and some other more or less unorthodox mainstream economists keep on arguing that, although they have one or two critiques to come with, their mainstream economic models are still valid for analyzing modern economies.
Yours truly disagrees.
Those models — DSGE, IS-LM, AS-AD, or what have you — don’t adequately reflect the width and depth of Keynes’s insights on the workings of modern market economies.
As is well-known, IS-LM models are Krugman’s favourite ‘simple gadgets.’ But they are typically set in a current values numéraire framework that definitely downgrades the importance of expectations and uncertainty — and hence give too large a role for interests as ruling the roost when it comes to investments and liquidity preferences. In this regard they are actually as bad as all the modern microfounded Neo-Walrasian-New-Keynesian models where Keynesian genuine uncertainty and expectations aren’t really modelled. Especially the two-dimensionality of Keynesian uncertainty — both a question of probability and ‘confidence’ — has been impossible to incorporate into this framework, which basically presupposes people following the dictates of expected utility theory (high probability may mean nothing if the agent has low ‘confidence’ in it). Reducing uncertainty to risk is nothing but hand waving. According to Keynes we live in a world permeated by unmeasurable uncertainty — not quantifiable stochastic risk — which often forces us to make decisions based on anything but ‘rational expectations.’ Keynes rather thinks that we base our expectations on the ‘confidence’ or ‘weight’ we put on different events and alternatives. To Keynes expectations are a question of weighing probabilities by ‘degrees of belief,’ beliefs that often have preciously little to do with the kind of stochastic probabilistic calculations made by the rational agents as modeled by “modern” social sciences. And, whether we like it or not, often we ‘simply do not know.’ As Keynes writes in A Treatise on Probability:
The kind of fundamental assumption about the character of material laws, on which scientists appear commonly to act, seems to me to be [that] the system of the material universe must consist of bodies … such that each of them exercises its own separate, independent, and invariable effect, a change of the total state being compounded of a number of separate changes each of which is solely due to a separate portion of the preceding state … Yet there might well be quite different laws for wholes of different degrees of complexity, and laws of connection between complexes which could not be stated in terms of laws connecting individual parts … If different wholes were subject to different laws qua wholes and not simply on account of and in proportion to the differences of their parts, knowledge of a part could not lead, it would seem, even to presumptive or probable knowledge as to its association with other parts … In my judgment, the practical usefulness of those modes of inference … on which the boasted knowledge of modern science depends, can only exist … if the universe of phenomena does in fact present those peculiar characteristics of atomism and limited variety which appears more and more clearly as the ultimate result to which material science is tending.
We cannot — from a relevant and realistic point of view — just presuppose that what has worked before, will continue to do so in the future. How strange then that mainstream macroeconomists — both of the fresh water and salt water ilk — as a rule do not even touch upon these aspects of scientific methodology that seem to be so fundamental and important for anyone trying to understand how we learn and orient ourselves in an uncertain world. An educated guess on why this is a fact would be that Keynes’s concepts are not possible to squeeze into a single calculable numerical ‘probability.’ In the quest for calculable risk and quantities, one puts a blind eye to uncertainty and qualities and looks the other way.
Why is this important? Because the kind of involuntary unemployment and low investment activity that intermittently characterizes modern market economies is basically impossible to understand without weighing in the kind of uncertainties and expectations that was at the forefront of Keynes’s analysis.
King understands that. Krugman doesn’t.