by What can economists know? The early concerns voiced by such critics as Keynes and Hayek, while they may indeed have been exaggerated, were not misplaced. I believe that much of the difficulty economists have encountered over the past fifty years can be traced to the fact that the economic environment we seek to model are sometimes too messy to be fitted into the mold of a well-behaved, complete model of the standard kind. It is not generally the case that some sharp dividing line separates a set of important systematic influences that we can measure, proxy, or control for, from the many small unsystematic influences that we can bundle into a ‘noise’ term. So when we set out to test economic theories in the framework of the standard paradigm, we face quite serious and deep-seated difficulties. The problem of model selection may be such that the embedded test ends up being inconclusive, or unpersuasive. Although advances have been made using a modern empiricist approach in modern economics, there are still some unsolved ‘problematics’ with its epistemological and ontological presuppositions. There is, e. g., an implicit assumption that the data generating process (DGP) fundamentally has an invariant property and that models that are structurally unstable just have not been able to get hold of that invariance.
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What can economists know?
The early concerns voiced by such critics as Keynes and Hayek, while they may indeed have been exaggerated, were not misplaced.
I believe that much of the difficulty economists have encountered over the past fifty years can be traced to the fact that the economic environment we seek to model are sometimes too messy to be fitted into the mold of a well-behaved, complete model of the standard kind. It is not generally the case that some sharp dividing line separates a set of important systematic influences that we can measure, proxy, or control for, from the many small unsystematic influences that we can bundle into a ‘noise’ term. So when we set out to test economic theories in the framework of the standard paradigm, we face quite serious and deep-seated difficulties. The problem of model selection may be such that the embedded test ends up being inconclusive, or unpersuasive.
Although advances have been made using a modern empiricist approach in modern economics, there are still some unsolved ‘problematics’ with its epistemological and ontological presuppositions. There is, e. g., an implicit assumption that the data generating process (DGP) fundamentally has an invariant property and that models that are structurally unstable just have not been able to get hold of that invariance. But one cannot just presuppose or take for granted that kind of invariance. It has to be argued and justified. Grounds have to be given for viewing reality as satisfying conditions of model-closure. It is as if the lack of closure that shows up in the form of structurally unstable models somehow could be solved by searching for more autonomous and invariable ‘atomic uniformity.’ But if reality is ‘congruent’ to this analytical prerequisite has to be argued for, and not simply taken for granted.
Even granted that closures come in degrees, we should not compromise on ontology. Some methods simply introduce improper closures, closures that make the disjuncture between models and real world target systems inappropriately large. Garbage in, garbage out.
Underlying the search for these immutable ‘fundamentals’ lays the implicit view of the world as consisting of material entities with their own separate and invariable effects. These entities are thought of as being able to be treated as separate and addible causes, thereby making it possible to infer complex interaction from knowledge of individual constituents with limited independent variety. But if this is a justified analytical procedure cannot be answered without confronting it with the nature of the objects the models are supposed to describe, explain or predict.