Paul Krugman — mistaking the map for the territory
from Lars Syll
Paul Krugman has — together with Robin Wells — written an economics textbook that is used all over the world. As all the rest of mainstream economics textbooks, it stresses from the first pages the importance of supplying the student with a systematic way of thinking through economic problems with the help of simple models.
Modeling is all about simplification …
A model is a simplified representation of reality that is used to better understand real-life situations …
The importance of models is that they allow economists to focus on the effects of only one change at a time …
For many purposes, the most effective form of economic modeling is the construction of ‘thought experiments’: simplified, hypothetical versions of real-life situations …
And these kind of rather vacuous ‘simplicity’ and ‘understanding’ statements get repeated — almost ad nauseam — over and over again in the book.
For someone genuinely interested in economic methodology and science theory it is definitely difficult to swallow Krugman’s methodological stance, and especially his non-problematized acceptance of the need for simple models.
To Krugman modeling is a logical way to analytically isolate different variables/causes/mechanisms operating in an economic system. Simplifying a complex world makes it possible for him to ‘tell a story’ about the economy.
Is not the use of abstractions a legitimate tool of economics? No doubt — it is only that all abstractions are not equally correct. An abstraction consists of isolating a part of reality, not in making it disappear.
What is missing in Krugman’s model picture is an explanation of how and in what way his simplifications increase our understanding — and of what. If a model is good or bad is mostly not a question of simplicity, but rather if the assumptions on which it builds are valid and sound, or just something we choose, to make the model (mathematically) tractable.
Assumptions may make the model rigorous and consistent from a logical point of view, but that is of little avail if the consistency is bought at the price of not giving a truthful representation of the real economic system.
The model may not only be simple but oversimplified, making it quite unuseful for explanations and predictions.
The theories economists typically put forth about how the whole economy works are too simplistic.
Throughout his discussion of models, Krugman assumes that they ‘allow economists to focus on the effects of only one change at a time.’ This assumption is of paramount importance and really ought to be much more argued for — on both epistemological and ontological grounds — if at all being used.
Limiting model assumptions in economic science always have to be closely examined since if we are going to be able to show that the mechanisms or causes that we isolate and handle in our models are stable in the sense that they do not change when we ‘export’ them to our ‘target systems,’ we have to be able to show that they do not only hold under ceteris paribus conditions and a fortiori only are of limited value to our understanding, explanations or predictions of real economic systems.
The rather one-sided emphasis on usefulness and its concomitant instrumentalist justification cannot hide that neither Krugman, nor the legions of other mainstream economics textbooks authors, give supportive evidence for their considering it fruitful to believe in the possibility of analyzing complex and interrelated economic system ‘one part at a time.’ For although this atomistic hypothesis may have been useful in the natural sciences, it usually breaks down completely when applied to the social sciences. Dubious simplifying approximations do not take us one single iota closer to understanding or explaining open social and economic systems.
The kind of relations that Krugman and other mainstream economists establish with their ‘thought experimental’ modeling strategy are only relations about entities in models that presuppose causal mechanisms being atomistic and additive. When causal mechanisms operate in real world social target systems they only do it in ever-changing and unstable combinations where the whole is more than a mechanical sum of parts. If economic regularities obtain they do it (as a rule) only because we engineered them for that purpose. Outside man-made ‘nomological machines’ they are rare, or even non-existant. Unfortunately that also makes most of the mainstream modeling achievements rather useless.
All empirical sciences use simplifying or ‘unrealistic’ assumptions in their modeling activities. That is not the issue – as long as the assumptions made are not unrealistic in the wrong way or for the wrong reasons.
Theories are difficult to directly confront with reality. Economists therefore build models of their theories. Those models are representations that are directly examined and manipulated to indirectly say something about the target systems. But models do not only face theory. They also have to look to the world. Being able to model a ‘credible world’ — Krugman’s ‘thought experiment’– a world that somehow could be considered real or similar to the real world, is not the same as investigating the real world. Even though all theories are false, since they simplify, they may still possibly serve our pursuit of truth. But then they cannot be unrealistic or false in any way. The falsehood or unrealisticness has to be qualified.
Some of the standard assumptions made in mainstream economic theory – on rationality, information handling and types of uncertainty – are not possible to make more realistic by ‘de-idealization’ or ‘successive approximations’ without altering the theory and its models fundamentally. And still there is not a single mentioning of this limitation in Krugman’s textbook!
From a methodological perspective, Krugman’s economic textbook — as are those of Mankiw et consortes — is a rather unimpressive attempt at legitimizing using fictitious idealizations for reasons more to do with model tractability than with a genuine interest of understanding and explaining features of real economies.
Krugman’s textbook and its simplicity preaching shows that mainstream economics has become increasingly irrelevant to the understanding of the real world. The main reason for this irrelevance is the failure of mainstream economists to match their deductive-axiomatic methods with their subject.
It is — sad to say — a fact that within mainstream economics internal validity is everything and external validity nothing. Why anyone should be interested in that kind of theories and models — as long as mainstream economists do not come up with any export licenses for their theories and models to the real world in which we live — is beyond my imagination. Sure, the simplicity that axiomatics and analytical arguments bring to economics is attractive to most economists, but simplicity obviously has its perils. Although simplicity is great when solving models, it’s quite another thing to assume that reality conforms to that tractability prerequisite.
Krugman’s and other mainstream economists’ textbooks are sad readings. Both theoretically and methodologically they are exponents of an ideology that seems to say that as long as theories and hypotheses are possible to transform into simple mathematical models, everything is just fine. As yours truly has tried to argue, there is actually no reason — other than pure hope — for believing this. The lack of methodological reflection in these books not only makes things wrong, but even worse, makes economics absolutely irrelevant when it comes to explaining and understanding real economies.