## The probabilistic delusion in economics

2 August, 2014 at 09:19 | Posted in Statistics & Econometrics | 1 CommentModern neoclassical economics relies to a large degree on the notion of probability and the assumption that economic data have to be conceived as random events that are analyzable within a probabilistic framework.

But is it really warranted to model the economic system as a system where randomness can only be analyzed and understood when based on an *a priori* notion of probability?

When attempting to convince us of the necessity of founding empirical economic analysis on probabilistic models, neoclassical economics actually forces us to (implicitly) interpret events as random variables generated by an underlying probability density function.

This is at odds with reality. Randomness obviously is a fact of the real world. Probability, on the other hand, attaches (if at all) to the world via intentionally constructed theoretical models, and *a fortiori* is only a fact of a probability generating nomological machine or a well constructed experimental arrangement or “chance set-up”.

Just as there is no such thing as a “free lunch”, there is no such thing as a “free probability.” To be able at all to talk about probabilities, you have to specify a model. If there is no chance set-up or model that generates the probabilistic outcomes or events — in statistics one refers to any process where you observe or measure as an experiment (rolling a die) and the results obtained as the *outcomes* or *events* (number of points rolled with the die, being e. g. 3 or 5) of the experiment — there strictly seen is no event at all.

Probability is a relational element. It always must come with a specification of the model from which it is calculated. And then to be of any empirical scientific value it has to be *shown* to coincide with (or at least converge to) real data generating processes or structures — something seldom or never done!

And this is the basic problem with economic data. If you have a fair roulette-wheel, you can arguably specify probabilities and probability density distributions. But how do you conceive of the analogous nomological machines for prices, gross domestic product, income distribution etc? Only by a leap of faith. And that does not suffice. You have to come up with some really good arguments if you want to persuade people into believing in the existence of socio-economic structures that generate data with characteristics conceivable as stochastic events portrayed by probabilistic density distributions!

From a realistic point of view we really have to admit that the socio-economic states of nature that we talk of in most social sciences — and certainly in economics — are not amenable to analyze as probabilities, simply because in the real world open systems that social sciences — including economics — analyze, there are no probabilities to be had!

The processes that generate socio-economic data in the real world cannot just be assumed to always be adequately captured by a probability measure. And, so, it cannot really be maintained that it even should be mandatory to treat observations and data — whether cross-section, time series or panel data — as events generated by some probability model. The important activities of most economic agents do not usually include throwing dice or spinning roulette-wheels. Data generating processes — at least outside of nomological machines like dice and roulette-wheels — are not self-evidently best modeled with probability measures.

If we agree on this, we also have to admit that much of modern neoclassical economics is based on unjustifiable probabilistic assumptions. I would even go further and argue that there really is no justifiable rationale at all for this belief that all economically relevant data can be adequately captured by a probability measure. In most real world contexts one has to *argue* and *justify* one’s case. And that is obviously something seldom or never done by practitioners of mainstream neoclassical economics.

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

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In my view the problem is not that probabillity-notions could not be applied to economics as a matter of principle. The problem that to many overlook is that the probability distributions themselves are dynamical objects that are generated endogenously. The problem is not that mainstream economics has to much probabillity theory in it, the problem is that most economists, mainstream or not, have very little intuition for what “dynamics” and “time-dependence” truly mean.

Comment by xconomics— 8 August, 2014 #