by Central fallacies of modern economics To criticise/oppose the current mathematical modelling emphasis is to adopt an antiscience stance. It is not. Mathematics is not essential (or inessential) to science; science involves using tools that are appropriate to the given task. A science of economics is perfectly feasible, and the current emphasis on mathematical modelling in economics serves, given the nature of social reality, mostly to prevent that potential from being realised. Thought-to-be false assumptions and questionable modelling methods are justified and so useable if/where they generate agreeable conclusions, or anyway conclusions held to be true. This is incorrect, though seemingly widely believed even, or perhaps especially, amongst heterodox
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Central fallacies of modern economics
To criticise/oppose the current mathematical modelling emphasis is to adopt an antiscience stance.
It is not. Mathematics is not essential (or inessential) to science; science involves using tools that are appropriate to the given task. A science of economics is perfectly feasible, and the current emphasis on mathematical modelling in economics serves, given the nature of social reality, mostly to prevent that potential from being realised.
Thought-to-be false assumptions and questionable modelling methods are justified and so useable if/where they generate agreeable conclusions, or anyway conclusions held to be true.
This is incorrect, though seemingly widely believed even, or perhaps especially, amongst heterodox economists critical of the mainstream. That is, heterodox economists frequently suppose that although their modelling assumptions are (necessarily) false, their models are better (than those of their opponents) because the conclusions generated are held to be true. It may be true that ‘all polar bears are white’. But if this apparent truth is deductively generated from the assumptions that ‘all polar bears eat snow’ and ‘all snow-eaters are white’, we have added nothing to our understanding of polar bears, snow or whiteness; and nor have we provided explanatory support for the proposition that ‘all polar bears are white’. All deductive exercises that are so based on known absurd fictions, and this inevitably includes almost all mathematical modelling exercises in modern economics, are just as pointless. Certainly they add little to our understanding of social reality.
The overarching flaw with the economic approach using methodological individualism and rational choice theory is basically that they reduce social explanations to purportedly individual characteristics. But many of the characteristics and actions of the individual originate in and are made possible only through society and its relations. Society is not a Wittgensteinian ‘Tractatus-world’ characterized by atomistic states of affairs. Society is not reducible to individuals, since the social characteristics, forces, and actions of the individual are determined by pre-existing social structures and positions. Even though society is not a volitional individual, and the individual is not an entity given outside of society, the individual (actor) and the society (structure) have to be kept analytically distinct. They are tied together through the individual’s reproduction and transformation of already given social structures.
Since at least the marginal revolution in economics in the 1870s it has been an essential feature of economics to ‘analytically’ treat individuals as essentially independent and separate entities of action and decision. But, really, in such a complex, organic and evolutionary system as an economy, that kind of independence is a deeply unrealistic assumption to make. Simply assuming that there is strict independence between the variables we try to analyze doesn’t help us the least if that hypothesis turns out to be unwarranted.
To be able to apply the ‘analytical’ approach, economists have to basically assume that the universe consists of ‘atoms’ that exercise their own separate and invariable effects in such a way that the whole consists of nothing but an addition of these separate atoms and their changes. These simplistic assumptions of isolation, atomicity, and additivity are, however, at odds with reality. In real-world settings, we know that the ever-changing contexts make it futile to search for knowledge by making such reductionist assumptions. Real-world individuals are not reducible to contentless atoms and so not susceptible to atomistic analysis. The world is not reducible to a set of atomistic ‘individuals’ and ‘states.’ How variable X works and influences real-world economies in situation A cannot simply be assumed to be understood or explained by looking at how X works in situation B. Knowledge of X probably does not tell us much if we do not take into consideration how it depends on Y and Z. It can never be legitimate just to assume that the world is ‘atomistic.’ Assuming real-world additivity cannot be the right thing to do if the things we have around us rather than being ‘atoms’ are ‘organic’ entities.
If we want to develop new and better economics we have to give up on the single-minded insistence on using a deductivist straitjacket methodology and the ‘analytical’ method. To focus scientific endeavours on proving things in models is a gross misapprehension of the purpose of economic theory. Deductivist models and ‘analytical’ methods disconnected from reality are not relevant to predict, explain or understand real-world economies
To have ‘consistent’ models and ‘valid’ evidence is not enough. What economics needs are real-world relevant models and sound evidence. Aiming only for ‘consistency’ and ‘validity’ is setting the economics aspirations level too low for developing a realist and relevant science.
Economics is not mathematics or logic. It’s about society. The real world.
Models may help us think through problems. But we should never forget that the formalism we use in our models is not self-evidently transportable to a largely unknown and uncertain reality. The tragedy with mainstream economic theory is that it thinks that the logic and mathematics used are sufficient for dealing with our real-world problems. They are not! Model deductions based on questionable assumptions can never be anything but pure exercises in hypothetical reasoning.
The world in which we live is inherently uncertain and quantifiable probabilities are the exception rather than the rule. To every statement about it is attached a ‘weight of argument’ that makes it impossible to reduce our beliefs and expectations to a one-dimensional stochastic probability distribution. If “God does not play dice” as Einstein maintained, I would add “nor do people.” The world as we know it has limited scope for certainty and perfect knowledge. Its intrinsic and almost unlimited complexity and the interrelatedness of its organic parts prevent the possibility of treating it as constituted by ‘legal atoms’ with discretely distinct, separable and stable causal relations. Our knowledge accordingly has to be of a rather fallible kind.
If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? Even if there always has to be a trade-off between theory-internal validity and external validity, we have to ask ourselves if our models are relevant.
‘Human logic’ has to supplant the classical — formal — logic of deductivism if we want to have anything of interest to say of the real world we inhabit. Logic is a marvellous tool in mathematics and axiomatic-deductivist systems, but a poor guide for action in real-world systems, in which concepts and entities are without clear boundaries and continually interact and overlap. In this world, I would say we are better served with a methodology that takes into account that the more we know, the more we know we do not know.
Mathematics and logic cannot establish the truth value of facts. Never has. Never will.