Hehe. Tbf, lots of economists started as engineers – but then came into the discipline, did a whole bunch of analysis, and helped build shiz up … rather than sniping from the sidelines and ignoring current lit. That’s the difference that matters right there.

Sounds good, especially since it reinforces my priors 😉

More seriously though I will have a look.

Keane argued that it is not possible to learn anything of interest from data without theoretical assumptions. All statistical inference relies on some untestable assumptions

Abstract

In this paper I attempt to lay out the sources of conflict between the so-called “structural” and “experimentalist” camps in econometrics.

Critics of the structural approach often assert that it produces results that rely on too many assumptions to be credible, and that the experimentalist approach provides an alternative that relies on fewer assumptions.

Here, I argue that this is a false dichotomy. All econometric work relies heavily on a priori assumptions.

The main difference between structural and experimental (or “atheoretic”) approaches is not in the number of assumptions but the extent to which they are made explicit.

Also look at Keane, Michael P. 2010. “A Structural Perspective on the Experimentalist School.” Journal of Economic Perspectives, 24(2): 47–58 where he argues that we cannot begin a systematic assembly of facts and empirical regularities without a pre-existing theoretical framework that gives the facts meaning and tells us which facts we should establish.

Koopman’s famous 1947 essay ‘measurement without theory’ argued that without theory, you do not know what to “look for” and what phenomena to observe and what measures to define and compute.