Flashlights, Power Grids, Institutions of Calculation, Pride and Human Frailty

The difference between the schools of quantitative and behavioral of economics consists largely in which errors they choose to accept in furthering the utility of their craft.

Each of these schools masters a set of conceptual levers with which they seek to solve problems. Or more realistically, the people in the school learn levers, and define their schools by the limits of those levers. They explore their field with levers. They do not necessarily even understand, or agree upon the problem they are solving with those levers. Often, they redefine the problem by the levers at their disposal – a form of unintentional circular reasoning that is rarely evident except in retrospect.

A lever is something that they can use to run a test. Testing is the sensory tool of science. But more clearly, methods and their tests are extensions of human perception. Think of them as an insects antennae. They sense whatever they are designed to sense. But it is up to humans to synthesize that new sensory data into a cogent whole. The problem occurs when our specialists become so enamored of their sensors that they bias their perception of the whole, as something designed to be explored by the sensors at their disposal.

Like any school of thought, the limits of that school are determined by the methodological scope of it’s levers, what effects they ignore, or what priorities the school’s practitioners give to which effects either considered or ignored. Most often, practitioners become enthralled with the levers they best understand. These ignored effects, and preferred levers, constitute errors. THey must be errors, if they eliminate or ignore information — information that may be either influential to the test, or influential to secondary causes.

My favorite response by economists is “… but we don’t consider that economics, so we dont consider this a problem for us to solve.” When in fact, economics is simply the school of measurement of the social sciences, when we choose to make material improvements in life — due to the increasing division of labor and resulting decrease in prices – our method of determining political policy. Economists then ignore the secondary causes of their research: they seek to justify a tool, rather than follow a chain of causation.

In the quantitative (abstract) and experiential (experiential and logical) schools of economics, participants either err on the side of understanding human behavior in favor of models that support levers of government intervention, or they err on the side of understanding that there are consequences to policy in the absence of knowledge about secondary causes. The difference in priority between the quantitative and the behavioral, is simply the priority that each gives to it’s methods. They seek to solve the problem from different ends of the human spectrum.

For example, the behaviorists did not understand the stickiness of prices and contracts over time, nor the importance of having sufficient money in the system, nor the problem with their concept of freedom, its relation to property, property to calculation and incentive, or the epistemology that property permits humans to employ.

The quantiatives did not understand number of very important things, primarily the nature of entrepreneurship, the limits of the DSEM (dynamic stochastic equilibrium model) the nature of what numbers can represent as categories given that factors of production, and even all objects in human experience, have different utility at different times. Nor did they understand how important habitual knowledge, (traditions and habits) are in society, and how quiclky humans forget them when they are not of daily use due to social programs or credit money, inflation, or taxation.

Nor did any of them understand that the problem we faced was the nature and dependence of society on human calculation itself, and that accounting practices, government by and laws, as well as the democratic system of government, are effectively laundering useful causality from the pricing system, as well as distorting it through the use of excess credit money.

This axis of differences between abstract quantitative and experiential logical is intersected by those people that err on the side of institutional conservatism as a protection against fashion or err on the side of institutional change as a means of altering society by way of its institutions of cooperation and conflict resolution. However, both ends of teh spectrum ignore either the opportunity for change in preference for risk against institutions, or ignore the impact on institutions in favor of experimental change.

And these differences are not minor or meaningless. It is the difference in the philosophy of giving people tools by which to better themselves and others, by fulfilling wants, and rewarding those who do so, and the opposite camp, which desires to change the status of humans at the discretion of the political managers who can achieve the power to pull the levers of their choice, and create class conflict over the spoils of productivity gain.

The debate rages. However, it appears, at least after cautious study of the history of ideas, that experiments that extend our institutions of calculation are those that are material investments in humanity. And those that are more fashionable, are minor adjustments to class, power, and material randomness as we fitfully pursue life.

Our problem is not economics. It’s calculation. Our political system is destroying our ability to calculate – because it’s members do not understand the underlying problem of human calculation, nor the need to modify government to facilitate it.

That change, that one change, is the single most important modification we need to make to our institutions.

Redistribution becomes calculable under that model. Class warfare becomes unnecessary. And to support Durkhiem, it prevents the state from suppressing freedom and individuality, because it no longer needs to, nor does it need to be a costly behemoth sitting on top of our society, nor can it, because it’s worth would be measurable.

That is the methodology that we need: measurement of causality.

Prediction is simply a silly chimera to compensate for the lack of information because we launder causality from our political efforts, and to justify the pulling of levers of government through taxes and laws because we lack that measurement and the information it contains.

And if my argument appears to favor both sides, yielding confusion rather than clarity, it is because we must continue to compensate for the practical reality of human frailty and foible, while creating institutions that allow us our political expression as a vent for our frustrations, while building a set of institutions that make our society increasingly calculable, comparable, forecastable, perceivable, and thusly one of cooperation in a division of knowledge and labor.

But we must not, ever, think that politics is more than a vent for the resolution of conflict between groups. Our society is it’s institutions of calculation. Our fitful political rhetoric an amusement and distraction that rails against our lack of control over them, while at the same time our prosperity entirely dependent upon them.

And we must constantly monitor our schools of thought, as well as our own fantasies, so that we are not so enthralled in our pride, that we forget that we are inventing our future, not discovering it, and that each of these methods, schools of though, political systems, is a flashlight in the dark, and our institutions of calculation the power grid that keeps them lit.

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