First, on the challenge of trying to distinguish between business processes that are fundamentally short-term in nature versus those of the longer-term:
My dad’s business, for instance, does multiple short-term contracting projects within long-term property development projects. In the normal production structure distribution his irrigation installations would be classified near the consumer level as it sits very close to final consumption, but he prices projects at the outset of long-term investment projects when the developer begins to plan and commence his project. My dad’s business therefore adjusts prices early in the business cycle at the same time that projects more remote of the consumer do, and will continue to price for projects throughout the period of the long-term project.Unlike Chris' initial post, where he was bemoaning the use of statistical indices, I regard this as a more interesting observation. Yes, it is true that firms with short-term production horizons will in some sense be dependent on the activity of (other) firms with longer-term production horizons. However, I still don't regard this as a decisive barrier to an empirical investigation into ABCT.[*] First note, however, that Chris' objection could be seen as theoretical critique of ABCT as much as an empirical one. For if his remarks hold true, then it is extremely difficult even in principle to distinguish the way in which, say, products closer to the end consumer are made less attractive by a fall in interest rates. The mechanics of the classic (naive?) Hayekian triangle begin to unravel, since the underlying distortions -- the switch into capital goods at the expense of consumption goods during an initial period of credit expansion -- may not even occur in a qualitative sense. Indeed, if processes all along the chain of production benefit from credit expansion then we are closer to a theory of economic growth than of business cycles.
Nevertheless, what really matters in this case is the change in relative prices. If you buy the insights provided by ABCT, then it seems extremely implausible that conditions inherently favourable to long-term production processes could benefit short-term processes to a near (or even greater) extent, merely through the creation of auxiliary demand. This is particularly true if the economy is operating at anywhere near full capacity, as is typically emphasised as the starting point for their analysis by Hayek and Mises... i.e. Any increase in capital goods production must increasingly come at the expense of consumer goods.[**] The focus of Lester and Wolff (2013) was the changing nature of such relative prices. It therefore seems a perfectly valid approach from my perspective and, moreover, the failure of the data to conform to the theory's broad predictions, or show signs of economic/statistical significance, is indeed cause for scepticism of ABCT's relevance. A final point on this matter is that L&W trace the evolution of these relative prices over time, which further accounts for the dynamic shifts between sequential processes in the economy.
Chris also made a few other remarks that I thought were worthy of comment, so here are some brief(ish) observations on other parts of his post:
Of course we have only have had around 5/6 business cycles since 1972 that to my mind can’t produce any statistically significant results either.
Okay, and how many monetary policy interventions have we had in that time? Again, I would think that this reflects rather poorly on a theory that places central bank interventions at the (inevitable) heart of all swings in the business cycle.
ABCT does not claim to be a theory that can explain all observed economic phenomena,which is what Grant thinks it claims to do.
Strawman. I have been very clear -- directly following the paper by L&W -- that this was entirely a question of how relevant ABCT is for explaining observed business cycles in the macroeconomy. Nothing more, nothing less. (Although, one wonders about the usefulness of a theory on business cycles if it seemingly fails to achieve that primary goal.)
On the subject of cycles, here is a beautiful example of circularity:
On theory versus data:
Chris ends his post in decidedly Churchillian mode:
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[*] As a technical point, there is also some confusion about data classification in the above paragraph. The PPI stage-of-process data is classified by commodities, not firms. Chris' dad's business -- hi Len! -- could therefore have goods classified in various stage-of-process categories, depending on where and who the end consumer was.
[**] This is analogous to an argument made by Tyler Cowen on the co-movement of investment and consumption over the business cycle. See pp. 8-9 of Daniel Kuehn's paper on the Hayekian version of ABCT, which I also mentioned in my previous post.
On the subject of cycles, here is a beautiful example of circularity:
Let me emphasize that the relevance of the Austrian theory can only increase the more one engages and learns about[...] Austrian theory.I love this sentence and have re-worked the title of my post in its honour.
On theory versus data:
So to Grant’s point, it is more than just a tendency of Austrians to dismiss empirical ‘evidence’ that runs counter to ABCT and related concepts, because their theories are not built on empirical data but on rigorous logical deduction.Firstly, I challenge anyone to show me that ABCT follows solely and directly from the action axiom alone. The list of subsidiary axioms and assumptions becomes enormous once we reach the full scope of the theory. This idea of an immaculately conceived business cycle theory, of pure logical cogency and free of any auxiliary pillars is, to be frank, so fanciful that not even the most zealous praxeologist could believe it. More importantly, the "choice" between theory and empirics is a false dichotomy. The above paragraph betrays a misunderstanding of how theory in mainstream economics (or elsewhere) is developed and exactly why it is mutually reinforcing to empirical observation. All economic theory is essentially deductive in nature. You start with some primary axioms or propositions and work through to the implications and consequences. Yet, how do we arbitrate between competing theories or measure their importance? Well, the same way that we do for any scientific field; we test them using data from the real world. Rejection of empirical scrutiny, validation and testing means that we are no longer debating economics or any kind of science for that matter. We are now in the realm of religion.
Chris ends his post in decidedly Churchillian mode:
But Grant should know, in our professions as economists and in the practice of economic forecasting, we are continuously, nay, every week, refining and enhancing our forecasting methods and theories based on what’s available and recent experience. Economic theory and economic forecasting are, of course, very different things.Typing up that final paragraph must have been difficult whilst holding a bowler hat over his breast and staring defiantly into the distance. Just kidding, bud. I agree with the sentiments here. I ask only that theory shape our forecasting efforts and that we avail ourselves of the opportunity to reconsider these theories when the facts do not match the predictions.
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[*] As a technical point, there is also some confusion about data classification in the above paragraph. The PPI stage-of-process data is classified by commodities, not firms. Chris' dad's business -- hi Len! -- could therefore have goods classified in various stage-of-process categories, depending on where and who the end consumer was.
[**] This is analogous to an argument made by Tyler Cowen on the co-movement of investment and consumption over the business cycle. See pp. 8-9 of Daniel Kuehn's paper on the Hayekian version of ABCT, which I also mentioned in my previous post.
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