Lars P. Syll — a question of economic methodology

Radical uncertainty is feature of a complex adaptive system a chief characteristic of which is emergence. Emergence is at the heart of evolution theory. Emergence in this context means that there is no way to predict what will emerge from a complex adaptive system based on investigation of the past and present state of the system. This implies that surprise is a characteristic of such systems.

This also implies that complex adaptive systems are like open systems rather than closed, receiving input exogenously, although in reality the additional input arises endogenously through the system dynamics, e.g., through reflexivity that engenders feedback and learning, but it a way that cannot be foreseen based on the present and past system states and operations.

Treating social systems as if they conformed to the structure and dynamics described theoretical in natural science, e.g., based on endogeneity, involves oversimplification. There is a strong tendency among rationalists that prefer formal solutions to adopt methodological assumptions based on mathematical tractability and convenience instead of accepting the empirical limitations of complex adaptive systems like human societies.

This has resulted in what Michael Hudson has dubbed "junk economics." Elegant but wrong.

It's long past time to admit that Keynes and Knight were correct and that Ramsey and Savage were wrong.

Lars P. Syll’s Blog
Radical uncertainty — a question of economic methodology
Lars P. Syll | Professor, Malmo University

Lars P. Syll — The limits of probabilistic reasoning

This is an important issue and some background is needed.

This is a fundamental issue in epistemology. As such it involves not only mathematics and science but also philosophy and logic. It is not an exaggeration to assert that this debate has been going on for millennia around the world and it remains undecided, which implies the need for further exploration. To claim certainty under such circumstances is premature.

Furthermore, the certainty of models comes from the logic and math. This certainty is that of tautology, or logical necessity, and contradiction, or logical impossibility. This is endogenous to the modeling process.

The interpretation of the model as a representation of reality is a substantial matter that goes beyond the procedure of the modeling and stands in need of connecting the model and reality in a way that is exogenous to the model. Process does not include substance as a virtue of the model. The model must be connected with what it represents internally, of course, and philosophy of logic and philosophy of science explore how this may take place. This is still controversial.

This controversy was raging at Cambridge and Oxford when Keynes was there. He would have been aware of the issues involved and the horizon of knowledge at the time. He was incorporating his view this in his Treatise on Probability.

In addition, at least since Aristotle, science has been regard as the search for causes and the aim is to provide a causal account that accords with observation. As Hume pointed out, the concept of causality is a very slippery one indeed. This is also a controversial subject and presently the debate in our area of the world is largely between realists and instrumentalists.

For example, accounting rules establish identities that all who understand the rules and their application accept. Where disagreement arises is often in attributing causality to the identity to account for it in actual terms and to use it for forecasting. This is to move from accounting to theory and scientific theories must be "testable" to distinguish them from speculation. The meaning and criteria of "testable" are also controversial.

Disagreement in debate often comes down to such matters, which are presumptions acting as hidden assumptions, since the underlying frame is not articulated and when parties disagree over the framing, there is no path to reaching a decisive outcome for lack of agreement over fundamental criteria.

Such issues regarding economics encompass philosophical logic (including foundations of mathematics), ontology, epistemology, value theory, action theory, philosophy of science and philosophy of social science. This is before getting into sociology and economic sociology, anthropology and economic anthropology, and history and economic history. Oh, I almost forget system theory and information theory.

In short, most conventional approaches are naïve unless they take foundations into account.

Lars P. Syll’s Blog
The limits of probabilistic reasoning
Lars P. Syll | Professor, Malmo University

See also from Lars today

Simplification is a virtue in modeling. Oversimplification is a vice.

Equilibrium — an assumption making many theories inaccurate

Lord Keynes — The Difference between a priori and a posteriori Probability

Key epistemological distinction.

Social Democracy For The 21St Century: A Post Keynesian Perspective
The Difference between a priori and a posteriori Probability
Lord Keynes

Lord Keynes — Probability Theory 101

I have updated below my posts on probability theory, probability theory in economics and decision making theory and Keynes’ contributions to probability theory.

Social Democracy for the 21st Century: A Post Keynesian Perspective

Probability Theory 101
Lord Keynes

Lord Keynes — My Posts on Uncertainty

 Below are links to my various posts on fundamental uncertainty, often with discussion of probability theory.

Social Democracy For The 21St Century: A Post Keynesian Perspective
My Posts on Uncertainty
Lord Keynes

See also, Skidelsky on Uncertainty and Knowledge

Philip Pilkington — Keynes and the “Fallacy of Aggregation” in Probability Theory

If Keynes’ fallacy of aggregation shows us nothing else, it should at least show us that when it comes to applied probability theory (i.e. econometrics) it is not so much the tools that are important as it is the person doing the work. And if the tools begin to become a fetish in and of themselves I see no good reason not to get rid of them to a very large extent.

Fixing the Economists
Keynes and the “Fallacy of Aggregation” in Probability TheoryPhilip Pilkington

Lars P. Syll — The dilemma of probability theory (wonkish)

This importantly also means that if you cannot show that data satisfies all the conditions of the probabilistic nomological machine, then the statistical inferences used – and a fortiori neoclassical economics – lack sound foundations!

The dilemma of probability theory (wonkish)
Lars P. Syll | Professor, Malmo University

Lord Keynes — M. E. Brady’s Critique of Post Keynesianism

While charge (1) is probably true, I think it is clear that charge (2) is false: there are Post Keynesians who do recognise degrees of uncertainty, such as, for example, Dow (1994 and 1995), Jespersen (2009: 8), Lars Syll, and (if he self-identifies as a Post Keynesian) Crocco (2002).

But I would like to see someone respond to charge (3).

Wonkish, but I have been wondering about this myself.

Social Democracy For The 21St Century: A Post Keynesian Perspective
M. E. Brady’s Critique of Post Keynesianism
Lord Keynes

See also Lord Keynes, Brady and Arthmar on “Keynes, Boole and the Interval Approach to Probability”

Lord Keynes — Bibliography on Keynes’s Theory of Probability Updated

Title self-explanatory.

Social Democracy For The 21St Century: A Post Keynesian Perspective

Bibliography on Keynes’s Theory of Probability Updated

Lord Keynes

Lars P. Syll — Economics and probability

This importantly also means that if you cannot show that data satisfies all the conditions of the probabilistic nomological machine, then the statistical inferences used – and a fortiori neoclassical economics – lack sound foundations!

Economics and probability
Lars P. Syll | Professor of Social Studies and Associate Professor of Economics, Malmo University

How the magician does the trick.

Lars P. Syll — Kenneth Arrow on knowledge that only comes trailing clouds of vagueness

Sums it up.

Lars P. Syll
Kenneth Arrow on knowledge that only comes trailing clouds of vagueness

The tipoff in neoclassical economics is the use of "natural." Students o philosophers (like me) recognize "natural" as a normative term that used to be used a synonymous with "divine" prior to the scientific revolution, and thereafter "natural' retained its normative authoritative connotation although no longer justified as divine. The normative authoritative connotation is now justified in terms of "laws of nature," with nature playing the role of the divine.

This is evident in 18th century Deism, where the deity is only invoked to start the "clock," which then runs in a deterministic and ergodic fashion, making "natural science" authoritative in the way that "divine" was authoritative  The difference is that scientists became the divines standing in for clerics and theologians.

The 19th century dropped the façade of deity after Feuerbach made the case that deity is an anthropomorphic projection of an imaginary ideal and Nietzsche proclaimed, "God is dead." But "natural" retained the authoritative connotation of "divine" without the divine. Scientists now did the divining based on theory and experiment rather than interpreting scripture as divine revelation.

Neoclassical economic (marginalism) develop in emulation of 19th century mechanics. Adam Smith's invisible hand is reinterpreted as a substitute for the invisible hand of God in the great chain of being that science replaced. Economists "discovered" the "laws of economics," like that of supply and demand in price determination, and proclaimed these "laws" to be "natural" and inviolable. Economics would be ergodic, like natural science, in spite of the fact that no other social science pretended to that level of certainty. In response, economics allied with natural science rather than social science and did not bother to look at its sister sciences but only to its "mother," physics.

The economics profession has not been able to shake this heritage for fear of appearing "unscientific." Therefore the demand for quantitative measurement and math modeling. It's just a hangover of previous superstition based on the great chain of being. Now the great chain is that of unified science, with physics at the base and the rest of the sciences proceeding from this level in rising orders of complexity. The problem arises when the implications of complexity are overlooked or denied.

If economics were the epistemic giant that many in the profession claim it to be, then CEO's would be economists. The reality is that most non-financial firms don't even have economics departments, let alone chief economists.

Where the mistake lies in in thinking that what is normatively authoritative in a model is therefore authoritative in what the model putatively  represents when there is no way of knowing this. Science is always tentative, in that "laws" are hypotheses that can be disconfirmed by evidence. As Kuhn has observed (somewhere in The Structure of Scientific Revolution), disconfirmation of hypotheses are not sufficient to overturn the theory serving as the paradigm for normal science until ad hoc adjustments make it evident that another theory is needed.

In economics, most of the profession have not gotten this message yet and are still busy adding epicycles to account for anomalies like the recent catastrophe that their models missed. And they refuse to look at other ways of seeing because these are not expressed quantitatively in mathematical models. They haven't realized yet that the methodology is the problem. The data is not compatible with the simple models being employed for convenience and tractability because of the uncertainty in social science arising from complexity. Doh.