I find Don Boudreaux's tendency of late to say things that I consider both accurate and important very unnerving...

What's he playing at!

Just kidding.

Most of this has been around the role of theory and empirics and how the two work together. This is excellent:

"First, I do take empirical work – including, by the way, non-quantitative history – very seriously. I emphatically do not believe that reality can be divined merely from armchair, a priori theorizing. (I’m sure that the same holds true for Russ, but I’ll speak here formally only for myself.) But to take empirical work seriously is not at all the same practice as naively swallowing asserted ‘facts’ and quantitative relationships whole and uncritically. Quite the opposite is true. To take empirical work seriously requires thinking seriously about methodology and epistemology – a practice that leads to mature evaluation of empirical claims. In turn, a mature evaluation of empirical claims often leads to a rejection of many such claims (for a variety of possible reasons). Such rejections of empirical claims reflect not a rejection of the importance of empirical information but, rather, a recognition of the inescapability of evaluating any and all empirical claims through theoretical lenses.

Second, the nature of economics and other social sciences means that the proper role of abstract theory in these sciences is greater even than it is in the ‘natural’ sciences. Not only is ceteris almost never paribus in social and economic reality, but many of the ‘predicted’ effects of postulated causes are often too fine and too small to detect with any practically useable tools of observation and measurement – even when ceteris is paribus."

Applications of these principles, of course, are likely to introduce some differences of opinion - but that's OK.

*****

On the slipperiness of dealing with empirics, Jonathan Catalan also has a good post up on our brain's tendency to search for causality whenever we look at statistics. Of course it's not alway there (sometimes it is).

This is not a problem unique to empirics, of course.

It is just as true of theory, where causality depends critically on what's referred to as "model closure" - or basically our assumptions about the direction in which causality runs.

Take Hayek's business cycle theory. He lays out a fine argument for why we'd expect the length of the capital structure to be pro-cyclical. But he makes an assumption about causality that has lead all Austrians to thinking in terms of the capital structure being too long in the boom and about right in the bust. A different model closure - a different set of causal assumptions applied to the exact same Hayekian capital theory - can get you to having the length of the capital structure about right during the boom and too short in the bust.

But how many people go around thinking that Hayekian capital theory implies the other story? Just about everyone. It doesn't. We make assumptions about causality in empirical and theoretical work. We have to, of course. We just need to be aware of it and make sure they're good assumptions.