Radical uncertainty — a question of economic methodology

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Lars Pålsson Syll
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Radical uncertainty — a question of economic methodology

Between 1920 and 1950, a debate took place which defined the future of economics in the second half of the 20th century. On one side were John Maynard Keynes and Frank Knight; on the other, Frank Ramsey and Jimmie Savage.

Knight and Keynes believed in the ubiquity of “radical uncertainty”. Not only did we not know what was going to happen, we had a very limited ability to even describe the things that might happen. They distinguished risk, which could be described with the aid of probabilities, from real uncertainty—which could not. In Knight’s world, such uncertainties gave rise to the profit opportunities which were the dynamic of a capitalist economy. Keynes saw these uncertainties as at the root of the inevitable instability in such economies.

Their opponents insisted instead that all uncertainties could be described probabilistically. And their opponents won, not least because their probabilistic world was convenient: it could be described axiomatically and mathematically.

It is difficult to exaggerate the practical consequence of the outcome of that technical argument. To acknowledge the role of radical uncertainty is to knock away the foundations of finance theory and much modern macroeconomics. But the reigning consensus is beset with glaring weaknesses. Keynes and Knight were right, and their opponents wrong. And recognition of that is a necessary preliminary to the rebuilding of a more relevant economic theory.

John Kay

Many economists have over time tried to diagnose what’s the problem behind the ‘intellectual poverty’ that characterizes modern mainstream economics. Kay points to the questionable reduction of uncertainty into probabilistic risk. Rationality postulates, rational expectations, market fundamentalism, general equilibrium, atomism, and over-mathematisation, are some other things one have been pointing at. But although these assumptions/axioms/practices are deeply problematic, they are mainly reflections of a deeper and more fundamental problem.

The main problem with mainstream economics is its methodology.

The fixation on constructing models showing the certainty of logical entailment has been detrimental to the development of a relevant and realist economics. Insisting on formalistic (mathematical) modelling forces the economist to give upon on realism and substitute axiomatics for real-world relevance. The price for rigour and precision is far too high for anyone who is ultimately interested in using economics to pose and (hopefully) answer real-world questions and problems.

This deductivist orientation is the main reason behind the difficulty that mainstream economics has in terms of understanding, explaining and predicting what takes place in our societies. But it has also given mainstream economics much of its discursive power – at least as long as no one starts asking tough questions on the veracity of – and justification for – the assumptions on which the deductivist foundation is erected. Asking these questions is an important ingredient in a sustained critical effort at showing how nonsensical is the embellishing of a smorgasbord of models founded on wanting (often hidden) methodological foundations.

The mathematical-deductivist straitjacket used in mainstream economics presupposes atomistic closed-systems – i.e., something that we find very little of in the real world, a world significantly at odds with an (implicitly) assumed logic world where deductive entailment rules the roost. Ultimately then, the failings of modern mainstream economics have its root in a deficient ontology. The kind of formal-analytical and axiomatic-deductive mathematical modelling that makes up the core of mainstream economics is hard to make compatible with a real-world ontology. It is also the reason why so many critics find mainstream economic analysis patently and utterly unrealistic and irrelevant.

Although there has been a clearly discernible increase and focus on “empirical” economics in recent decades, the results in these research fields have not fundamentally challenged the main deductivist direction of mainstream economics. They are still mainly framed and interpreted within the core “axiomatic” assumptions of individualism, instrumentalism and equilibrium that make up even the “new” mainstream economics. Although, perhaps, a sign of an increasing – but highly path-dependent – theoretical pluralism, mainstream economics is still, from a methodological point of view, mainly a deductive project erected on a foundation of empty formalism.

If we want theories and models to confront reality there are obvious limits to what can be said “rigorously” in economics. For although it is generally a good aspiration to search for scientific claims that are both rigorous and precise, we have to accept that the chosen level of precision and rigour must be relative to the subject matter studied. An economics that is relevant to the world in which we live can never achieve the same degree of rigour and precision as in logic, mathematics or the natural sciences. Collapsing the gap between model and reality in that way will never give anything else than empty formalist economics.

In mainstream economics, with its addiction to the deductivist approach of formal- mathematical modelling, model consistency trumps coherence with the real world. That is surely getting the priorities wrong. Creating models for their own sake is not an acceptable scientific aspiration – impressive-looking formal-deductive models should never be mistaken for truth.t is still 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 is beyond my imagination. 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, they really should not be surprised if people say that this is not science, but autism!

When applying deductivist thinking to economics, economists usually set up “as if” models based on a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is of course that if the axiomatic premises are true, the conclusions necessarily follow. The snag is that if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often don’t. When addressing real economies, the idealizations necessary for the deductivist machinery to work, simply don’t hold.

So how should we evaluate the search for ever greater precision and the concomitant arsenal of mathematical and formalist models? To a large extent, the answer hinges on what we want our models to perform and how we basically understand the world.

For Keynes, 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, Keynes 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.

To search for precision and rigour in such a world is self-defeating, at least if precision and rigour are supposed to assure external validity. The only way to defend such an endeavour is to take a blind eye to ontology and restrict oneself to prove things in closed model-worlds. Why we should care about these and not ask questions of relevance is hard to see. We have to at least justify our disregard for the gap between the nature of the real world and our theories and models of it.

Keynes once wrote that economics “is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world.” Now, 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.

Models preferably ought to somehow reflect/express/correspond to reality. I’m not saying that the answers are self-evident, but at least you have to do some philosophical under-labouring to rest your case. Too often that is wanting in modern economics, just as it was when Keynes in the 1930s complained about Tinbergen’s and other econometricians lack of justifications of the chosen models and methods.

“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 don’t know”.

The models and methods we choose to work with have to be in conjunction with the economy as it is situated and structured. Epistemology has to be founded on ontology. Deductivist closed-system theories, as all the varieties of the Walrasian general equilibrium kind, could perhaps adequately represent an economy showing closed-system characteristics. But since the economy clearly has more in common with an open-system ontology we ought to look out for other theories – theories who are rigorous and precise in the meaning that they can be deployed for enabling us to detect important causal mechanisms, capacities and tendencies pertaining to deep layers of the real world.

Rigour, coherence and consistency have to be defined relative to the entities for which they are supposed to apply. Too often they have been restricted to questions internal to the theory or model. But clearly, the nodal point has to concern external questions, such as how our theories and models relate to real-world structures and relations. Applicability rather than internal validity ought to be the arbiter of taste.

So — if we want to develop a new and better economics we have to give up on the deductivist straitjacket methodology. To focus scientific endeavours on proving things in models is a gross misapprehension of what an economic theory ought to be about. Deductivist models and methods disconnected from reality are not relevant to predict, explain or understand real-world economies.

If economics is going to be useful, it has to change its methodology. Economists have to get out of their deductivist theoretical ivory towers and start asking questions about the real world. A relevant economics science presupposes adopting methods suitable to the object it is supposed to predict, explain or understand.