Can anyone tell me if the sort of the sort of simultaneous equation/structural equation modeling of economic relationships that that was championed and to some extent developed out of the Cowles Commission (later Foundation) is technically the same under the hood as the "structural equation models" (SEM) framework common in, for example, psychology & political science? I note that Wikipedia states that SEM models are "not to be confused with" econometric simultaneous equation models, but does not actually spell out the difference.
The short descriptions of what they do seem similar -- so similar that I can imagine building an causal economic model using SEM software. But the SEM framework pays a lot of attention to various various concerns that don't seem relevant to or are not commonly used by econometric modelers. For instance, unobservable variables play a key role in SEM modelling, with substantial apparatus devoted to confirmatory factor analysis and measurement models associated with them. Economics usually bases its models primarily on quantities and prices that are, at least in principle, observable, while unobservable quantities (level of efficiency? total social welfare?) are usually assumed to be firmly grounded in economic theory, with changes, if not absolute levels, indirectly observable in levels and flows of economic goods. I think most economists would regard efficiency and welfare as more concrete than SEM's latent variables (e.g. introversion, legitimacy).
I've had more exposure to economics than psychology. but despite this I don't feel like I can list distinctive concerns or capacities of the economic approach to structural equation modeling that are not present in SEM. I have a somewhat inchoate impression that SEM is more concerned with validating model constructs and establishing the flow of causation, while economic structural modeling is more concerned with establishing that the equations which fit together into an economy are estimated consistently with one another, and that the equations and data together provide a uniquely determined ("identified") solution.
But I don't know if these differences in emphasis imply that these are different techniques, or if people are actually wielding largely identical tools to solve their respective problems. For instance, I know that path analysis, common in SEM models, is infrequent in econometric work, but I don't know if that is because the usual econometric implementations of structural models is incompatible with a path analysis approach.