The paper, which was published in the Review of Austrian Economics no less, finds that Austrian Business Cycle Theory (ABCT ) is not particularly relevant from an empirical standpoint. In short: The unique predictions made by ABCT, concerning the relative price and output changes of goods in different stages of production, are not borne out by the data. It is therefore very difficult to argue that such dynamics are driving the business cycle of the macroeconomy.
I've read through the paper and think that it is a very thorough and technically sound piece of analysis. More importantly, it fills a gap in the literature by using good data to ask the right questions. The conclusion closely matches my own view on ABCT, which is that it constitutes an internally consistent framework for the most part, yet has limited relevance as an overarching macro theory. (That said, L&W also acknowledge that Austrians emphasise a number of concepts, from the coordinating role of market prices and the inter-temporal allocation of resources, that are very valuable to broader economics. Mainstream macro is certainly richer for incorporating these insights.)
Arguing with Austrian-types is something of a side hobby for yours truly and I sent a copy of the paper to Chris Becker, my friend since school days and staunch proponent of all things ABCT. He has written a thoughtful blog post on what he sees are the "flaws and shortcomings" of the study. However, I am not persuaded by his arguments.
Chris starts out by calling into question the various data and metrics used by L&W. For instance, he says that PPI is "only a proxy" for actual economic activity and market prices as "no statistical measure is 100% accurate". Wait a minute, that is simply a tautology. Statistics are by definition imperfect representations of the true state of nature based on probabilistic laws and frequency distributions. To claim that this invalidates their use in scientific research is to a) betray a misunderstanding of how statistics actually works and b) discard a great majority of scientific discoveries and technological advancements since before even the Enlightenment. All that really matters in this case is that these indexes constitute accurate representations of the underlying variables and populations that they refer to. I see no reason to think that they are biased in a manner that systematically renders them uninformative (or misleading) -- particularly if the proposed dynamics were truly the main drivers of large swings in economic activity. I should also say that Chris' objections here would strike me as more convincing if I didn't see Austrians constantly referring to PPI, money supply data, etc. in support of their own arguments.
Next, Chris walks through the various monetary policy variables used in the study and what he perceives as their shortcomings. For the record, L&W use the Federal Funds Rate (FRR) as their main monetary policy variable, while a number of other metrics (M0, M1, M2, etc ) are utilized for robustness checks. In each case, these various monetary policy variables return the same broad set of results that ultimately fail to find vindication for ABCT. (That's the point of running robustness checks after all; they should produce results that are consistent with each other.) Chris does seem to agree with L&W in regarding the FFR as the most appropriate variable to proxy for changes in monetary policy. He even writes: "It is instructive that distortions of the FFR provide the most significant response in favour of ABCT, as it is the divergence between this interest rate and the natural rate of interest that sets in motion the business cycle, according to the Mises-Hayek theory." Except it isn't really instructive at all, because even if some of the coefficients have the same sign as predicted by the theory, they are almost uniformly insignificant from an economic and statistical perspective! L&W are very clear about this and make the point several times throughout their paper. For example (and with emphasis added):
It is critical to note that the results lack statistical significance. In each IRF [Impulse Response Function], the 80 % confidence interval bands suggest that none of the four IRFs demonstrate impact or dynamic responses which differ significantly from zero for more than a few months. This point is particularly relevant when ABCT would otherwise rely on the large shifts in capital to drive business cycle dynamics.
Once again, we are trying to discern whether ABCT is a plausible candidate for explaining the business cycle at large. According to this evidence, that doesn't appear to be the case.
Chris continues his discussion on monetary policy variables by describing ways in which they may or may not be directly relevant to ABCT, and how the theory can ostensibly accommodate findings that run counter to predictions made by the standard ABCT model. I won't go into too deeply into these issues except to say that I think he runs dangerously close to describing ABCT in pseudoscientific terms. As Popper correctly pointed out many years ago, a theory which claims its strength is to account for any possible outcome is no real scientific theory at all. On the flipside, to say that there are other factors that mitigate how the dynamics of ABCT play out in the economy, is tantamount to admitting that it has limited relevance for explaining observed economic phenomena! (Further, given that the dataset runs from 1972 to 2011 and the empirical analysis tracks variables over a 60-month period following a policy shock, I personally don't think that appealing to "credit injection points" and "historical contingencies" holds much water.)
The post ends with a helpful (ahem) reading list. I have taken the liberty of noting down the respective page numbers for each of the books that Chris recommends: "To really understand ABCT, one should read Ludwig von Mises’ “Human Action” [924 pages] , Friedrich von Hayek’s “Prices and Production” [594 pages], Murray Rothbard’s “Man, Economy, and State” [1,441 pages], and Jesus Huerta de Soto’s “Money, Bank Credit, and Economic Cycles.” [777 pages]". Now, I know that people like to make fun of some Austrians for inevitably referring them to incredibly lengthy treatises during internet debates (often in lieu of making actual arguments). I don't usually think of my friend as falling into that category, but come on... 3,736 pages! If that's what it takes to truly understand ABCT, then I sincerely doubt that anyone has a coherent grip on it.
Allow me to conclude by making two general observations:
1) I may be wrong, but I can't quite escape the feeling that econometrics is seen by many as the preserve of academics and government. That couldn't be further from the truth. Econometrics and statistical analysis has been fundamental to virtually every private company and industry that I have ever worked in, with or am aware of... from the energy sector to finance to consulting to media. If empirical methods were truly misleading, then surely the evolutionary dynamics of the market would have brought about their demise long ago?
2) As with any scientific field or theory, no single study -- no matter how well done -- is enough to invalidate an entire research programme. Similarly, I am hardly claiming that econometrics and empirical studies are infallible. (In addition to discussing the vexing problems of identification many times on this blog, I have also argued that theory and data are mutually reinforcing so that one acts as a check on the other.) However, I do wonder what evidence would be sufficient for Austrians to reconsider their theories. I detect a remarkable tendency to dismiss any empirical evidence that runs counter to ABCT and its related concepts. It should be said that all major schools of economic thought have had to face up to the challenges presented by the data... And are better for it. Keynesians made significant adjustments to their theories in the face of 1970's stagflation, as well as the intellectual challenges of the Lucas Critique and microfoundations movement. For their part, recent events have forced Monetarists to confront the limitations of Friedman's quantity of money supply rule and the potential ineffectiveness of monetary policy at the zero lower bound. Theory cannot advance if it is impervious to data.
PS - An ungated version of the L&W paper can be downloaded here.
PPS - Those interested in this subject should also read Daniel's excellent overview of Hayek's version of ABCT, which I believe is forthcoming in Critical Review.