11th
Economics in its right place.
[Warning: This post is one, among many I’ve drafted in past years, attempting to delineate my views on the economics field and its proper aims. Reading this post may be damaging to your research ambitions and/or baseline serotonin levels.]
The economics discipline is marketed as teaching its pupils how to see the assumptions underlying a statement or argument – given some conclusion, the well-taught student should be able to locate, in short order: (1) the empirical claims that are implicitly relied upon, and (2) the value judgments and weighing-of-goals that are applied in the case of a prescriptive/normative conclusion. Economics shares the struggle with epistemological issues encountered by all social scientists – the fundamental unknowability of the social world; the phenomenology of observation; the feedback mechanism from our construction of the social world into the operating dynamics of said social world. But it attempts to parse out the causal chains in those things which we can measure – if imperfectly, then hopefully consistently.
In this way, economics is an engineering subdiscipline: one dedicated to understanding the mechanics of simulations and models of reality, rather than some fundamental, and fundamentally consistent, reality itself. And there is great use in this aim. As decisionmakers and agents of society are forced to act with imperfect and incomplete models of the social world in mind, deepening our understanding of how these models work is important work.
The economist, therefore, contributes most to the field by one of three pursuits of labor: (A) narrowing the gap between known-reality and reality by the improvement of measures (the expansion of the scope of the category “the measurable world”, which is the object of social scientists); (B) maintaining the internal consistency (logical rigor) of our understanding of (i) causal relationships (models), and (ii) possible internal dynamics (this being the chief aim of Theory/mathematical economics)*; and, (C) improving our models by composing new ones – better fit to the data in A, or more specified in their elimination of possible coexisting logics per B.
This – to my mind, and perhaps to that of Thom Yorke – is economics in its right place.
* On the latter count, let me rant for a moment: I find myself increasingly arguing with those enamored of Theory. The reasons are simple: first, they take a mathematical modeling of agents (firms, individuals, economies) to be empirically descriptive prima facie, when in fact they are simply studies in feasibility; a formal model only proves that given certain conditions, some outcomes are logically (mathematically) consistent – which is to say, possible – and others are logically inconsistent – which is to say, impossible; second, being failed mathematicians/physicists, they feel a certain superiority over us mere technocrats who limit our scope and are constantly aware of the costs of attempting to expand beyond our domain of the measurable-world; another way of putting this is that they are happier being wrong, and concomitantly damaging to the world, but published; in physics and mathematics, such idiocy is tolerated because the human cost of High Theory on the everyman is low; in economics, it should not be, and the moral philosophers among us have failed in our lack of righteous indignation; to paraphrase a masterful script, Boondock Saints, it is not the evil of bad men we are to fear most, but rather the indifference of good men.
