Bryan Caplan writes:
Almost all economic models assume that human beings are Bayesians... It is striking, then, to realize that academic economists are not Bayesians. And they're proud of it!
This is clearest for theorists. Their epistemology is simple: Either something has been (a) proven with certainty, or (b) no one knows - and no intellectually respectable person will say more...
Empirical economists' deviation from Bayesianism is more subtle. Their epistemology is rooted in classical statistics. The respectable researcher comes to the data an agnostic, and leaves believing "whatever the data say." When there's no data that meets their standards, they mimic the theorists' snobby agnosticism. If you mention "common sense," they'll scoff. If you remind them that even classical statistics assumes that you can trust the data - and the scholars who study it - they harumph.
Robin Hanson offers an explanation:
I’ve argued that the main social function of academia is to let students, patrons, readers, etc. affiliate with credentialed-as-impressive minds. If so, academic beliefs are secondary – the important thing is to clearly show respect to those who make impressive displays like theorems or difficult data analysis. And the obvious way for academics to use their beliefs to show respect for impressive folks is to have academic beliefs track the most impressive recent academic work.
...beliefs must stay fixed until an impressive enough theorem or data analysis comes along that beliefs should change out of respect for that new display. It also won’t do to keep beliefs pretty much the same when each new study hardly adds much evidence – that wouldn’t offer enough respect to the new display.
I wonder, what does this look like in the cross section? In other words, relative to other academic disciplines, which have the strongest tendency to celebrate difficult work but ignore sound-yet-unimpressive work? My hunch is that economics, along with most other social sciences, would be the worst offenders, while the fields closer to engineering will be on the other end of the spectrum. Engineers should be more concerned with truth since whatever they build has to, you know, work. What say you? More importantly, anyone have any evidence?