Topic: Market Planning (Read 1290 times)

I agree that this is a brand new field, as I call it "CryptoCoinomics", as in the Economics of Crypto Currencies.

As far as planning for it, that's really a difficult area. How to you plan or predict on macro-economic scale? I would think there will be a ton of math involved to make it workable.

Good to see someone is thinking ahead

Free will makes it impossible to "plan".

You're going to rewrite economics and finance?

Maybe start with the basics of how a price unstable currency would destroy an economy.  BTC should have many examples of businesses that stopped accepting BTC because of rampant inflation now in the second year.

They are far too simple, most have been around for 40 years if not longer. Given the computing power that we have now they could do exponentially better. However before we start coding, it is necessary to build a theoretical framework.

At first, I thought you were talking about planned economy for a country, then realised you were talking about decision making systems by  modeling a matrix of different outcome. I believe large corporations do that NOW. Investment banks/rating agencies do exactly that to estimate company earnings under normal conditions and changes in market environment.

I read your article, I couldn't catch your argument.

You're going to rewrite economics and finance?

Central economic planning, despite its practical and theoretical flaws, received a great deal of scientific and technical attention as a discipline in the 20th Century. A great deal of technical talent was devoted to developing the tools and intellectual apparatus of this discipline. Many resources went into the creation of 4-year, 6-year and even longer term economic plans with or without the aid of computers and mathematical models. In a very real sense central economic planning remains alive and well at the world’s central banks and in their attempts to manage a number of economic factors from prices to employment through the practical tools of monetary policy and theoretical models based on the Keynesian-monetarist consensus. Variations on the Phillip’s curve, NAIRU and multiple equilibrium models remain in use, despite their utter failure as empirical or predictive guides in a complex system.
 
Ludwig von Mises in his 1921 book “Socialism: An Economic and Sociological Analysis” was the first to logically demolish the idea of central planning and formulate the economic calculation problem as its central flaw. His student F.A. Hayek would later delve into the reasons why complex systems and spontaneous or emergent orders are so resistant to the conceited efforts of central planners.
 
However the failure of central planning and the complexity of prediction in market systems is by no means a reason to abandon “planning” and the strategic formulation of long term objectives and the means to achieve them. Strategic planning of smaller scope that is related not to entire economies but to families, companies or even personal goals is a reality that we see all around us. The use of models currently used can range from the simplest Discounted Cash Flow spreadsheet to smart company data bases that put central planner’s Project Cybersyn, or the fictional Multivac to shame. As Hayek brilliantly put it “the more the state plans, the more difficult planning becomes for the individual”. Conversely the smaller the scope of the top-down central plan, the farther ahead individuals and groups can set their objectives and can plan ahead to reach them.
 
There is a need for a theoretical framework that will allow us to develop the discipline of long term free market planning*. Current models are antiquated and distorted by the influence of econometric simplification (masquerading as complexity) born of physics-envy that so many economists suffer under. Market planning models should look to sciences dealing with complex emergent orders: biology and meteorology. A market planning model should have the flexibility, tolerance to change and space for trial and error of a gardening project or a selective breeding program. Such a plan must be able to react to changing inputs (mainly prices) by branching off or abandoning complete modules, slowing and speeding up certain branches of the plan as circumstances change. It must have feedback loops in its decision trees and trigger levels for expansion, retrenchment or even the abandonment of the entire plan when tolerance thresholds are exceeded.
 
I do not hope to do more here than merely outline what I believe is a very exciting field that will  require an immense amount of work to become an useful tool for individuals, companies, families... and bring the science of economics back to its rightful place as an everyday tool rather than an academic plaything. If in the 21st Century we see only a fraction of the technical effort devoted in the 20th to central planning, to this new discipline, we can expect incredible results. Market planning software could become as ubiquitous as accounting programs currently are. Market planning algorithms will also be very useful in the creation of DAOs (decentralised autonomous organizations).


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