The Explanatory Power of Neoclassical Economics
Techdirt’s Mike Masnick recently posted an article about a group of economists who claim to be going up against the dominant economic school of thought. The post notes that when one looks closely, these economists, like many before them, aren’t really critiquing the theory of the heart of modern economics, the rational agent, but rather they’re noting that people make judgments in context. In Mike’s words, “the rational person… is based on data, not dollars.”
What Mike’s post misses, however, is that neoclassical economics doesn’t very well account for the very “data” that they’re talking about. While there are some tricks to negate unquantifiable effects like peer pressure or social etiquette, those techniques are limited to particular data sets in particular circumstances. As a whole, neoclassical economics primarily deals with easily quantifiable variables like prices and pounds.
The entirety of the unmeasurable factors like pressure or etiquette is supposed to be captured by the utility function, the single line that denotes the sum of an agent’s preferences and tastes. This isn’t a problem in terms of internal consistency, but it is a problem in terms of practicality. As we grow to better understand how the numeric components of economics fit together, the fact that this component is made up exogenously (not explained within the economic model) will continue to eat into the explanatory power of the neoclassical models, leading to overconfidence bias in results with questionable accuracy.
The discipline is evolving in an attempt to take care of these holes via the invention of bounded rationality, the creation of behavioral economics, and exploratory works into new neurological studies. However, these new explorations mean great change is on the horizon for the dismal science. From what I understand, one of the great shifts that will be occuring is that instead of arriving at a clean answer where two lines cross, or correctly interpreting a statistically calulated coefficient, economics will have to shift towards settling for fuzzy answers and ranges of reasonable probability. I don’t think this is necessarily good or bad… probably more the former than the latter though. I agree with a textbook I have, which stated “I would rather know something imperfectly than not know it with great precision.”
However, even as the discipline grows, I doubt I’ll personally ever be convinced of it’s explanatory power for two reasons. First, the rational agent was invented as an interpretation of the math economists created instead of the other way around. This wouldn’t be a problem if economists rigorously checked the models they create, but I suspect that escalation of commitment bias comes into play, leading economists to choose data sets that fit the models they’ve already worked hard on instead of altering them again and again. Second, economics is the only science I know of where the study of it changes the discipline itself. If people study economics and use it to achieve they’re economic goals, then that has become another variable to be added to the economic equation, which leads to more study, and the cycle starts over again.
Now nothing I’ve said covers some of my other issues with the discipline, like its oversimplification of price relationships, nor does it cover why I’ve stuck with economics as a major. Perhaps I’ll expand on those later, but for now, I’ll simply set up the premise that though there is theoretically room for infinite explanatory power in economics, I’m skeptical of it in that regard.
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