This whole article is based on flawed assumptions, which Sam comes closest to explicitly identifying.
The article assumes that the outcome of actions can be predicted.
Complexity theory tells us that there are many different sorts of systems, all of which are predictable only in a probabilistic sense.
Some systems are sufficiently simple that the probabilities deliver a close approximation to hard predictability. Engineers love such systems, the economy as a whole is not such a system, though it does contain many component sub-systems that have this set of characteristics.
Some systems are complicated, with less distinct boundary conditions and more obviously probability based outcomes. Much of human activity falls into this category, and hence much of economics.
Some systems are complex, dispositional, and interactive. Such systems can respond in any manner, but some responses are much more probable than others. One must probe such systems, sense how they actually respond, then amplify desired trends and dampen down undesired ones. Much of economics falls into this class of complexity. It is simply not capable in either logic or mathematics of being predicted with consistency. One interacts with such systems, and is changed by the interaction, to a similar degree to the changes one wroughts on the system. Boundary conditions change with every action.
And some systems are chaotic. Some sorts of chaos are causal, but unpredictable (like the Mandelbrot set), and other forms of chaos are completely random (not amenable to prediction at any level). Some aspects of economic systems are chaotic.
So starting with an assumption that anyone can predict how the economy will respond simply displays an ignorance of the degrees of complexity present.
And Goodhart’s Law is important:
“Any observed statistical regularity will tend to collapse once pressure is put upon it for control purposes.”
Having said that, there are other aspects at play as well, other paradigms available.
A market based (exchange based) set of valuation measures (with all the many layers of derivative measures and tools) is only one possible paradigm.
Markets have been very useful historically, in a context where the vast majority of goods and services were scarce, and where most people could be genuinely employed in tasks with social benefit.
We are now entering an age where computers and automation can deliver any good or service (or at least a replica that is indistinguishable by human senses). In such a realm there is no need to employ people to do anything, as there is no need to exchange anything.
That requires a complete re-examination of the concepts of the values we claim to hold most dear – life and liberty.
What might liberty mean in an age where any discovery, any information or manufacturing technique perfected, can (in a matter of seconds) be replicated to every personalised production system on the planet and be available to every individual who might have use of it?
We have the technical ability to produce such systems.
The market value (exchange value) of such a system must be zero, as by its universal nature, it makes all goods and services as scarce and as valuable as oxygen in the air – of no market value due to universal abundance.
For the most part, we are trapped within a paradigm that has collapsed a method of accounting (money) with the things represented (goods and services), and most minds can no longer keep them separate.
The questions facing our society are far larger than those any first year student of complexity could instantly answer – ie why no one can predict how an economy will behave.
The really deep question is, at the deepest (and or highest – depending on ones conceptual schema) levels of awareness and incentive structures, what are the values that deliver the greatest probability of life, and the greatest degrees of individual freedom?
I am very clear, beyond any shadow of reasonable doubt, that market based values of exchange are rapidly approaching the point where they deliver greater threat to life and liberty than they deliver in opportunities. And the curve appears to be a tight exponential, when it crosses the axis it is going to go deeply negative very quickly. We have time to develop a replacement, but not a lot of time.