16th April 2011
Hayek and Mises vindicated: Macro-economist admits to pretence of knowledge
I chanced upon Ricardo J. Caballero's article in The Journal of Economic Perspectives (Fall 2010), entitled, "Macroeconomics after the Crisis: Time to Deal with the Pretense-of-Knowledge Syndrome". This paper is available at the SSRN website (here) and I'd strongly encourage you to read it.
I have had a bitter-sweet relationship with economics, with macro-economics being the bitter part. What puts me off macroeconomics is its delusional approach to society. Plug in some equations, imagine a few assumptions, and then cook up a monstrous 20 page series of mathematics to come out with something that pretends to tell us something about society. What put me off truly from this discipline was to hear praise about a pathetic Indian anti-poverty program based on imaginary set of mathematical calculations.
The subject of macro-economics is so divorced from reality that it tests one's patience. One doesn't know what is sensible and what is nonsense masquerading as sense.
The discipline of macroeconomics perhaps has its roots in the IS-LM models that came about after Keynes, based on simplistic and grandiose assumptions about the entire economy. Even later, rational expectations models, turned out to be quite a damp squib because of the dramatic imagination involved.
Before Keynes, economists perhaps never aspired to predict the macro-economy as a whole (except for the study of business cycles). They tried to measure it, understand its dynamics, but never to predict its future course.
Since Keynes a lot changed. Every macro-economist worth his salt spends an inordinate amount of effort in trying to predict the economy based on a few key variables and equations. And it is these people who parade about, offering predictions about the future on TV that the world sees. People therefore think of economists as predictors of the economy, than analysts of human freedom.
I would prefer that they restrict themselves to the study of freedom. More insights about "macroeconomic policy" are found in Hayek than in any standard advanced textbook on macro-economics. Surely Mises's warning against mathematical economics (discussed in my blog post here) has been vindicated.
Anyway, here are few extracts from the Caballero paper:
The recent financial crisis has damaged the reputation of macroeconomics, largely for its inability to predict the impending financial and economic crisis. Of course, it is well-known that certain elements can increase the fragility of a financial system, such as high levels of leverage or mismatches between short-term liabilities and long-term assets, and that these issues may justify policy intervention. But knowing these mechanisms is quite different from arguing that a severe crisis can be predicted.
What does concern me of my discipline, however, is that its current core—by which I mainly mean the so-called dynamic stochastic general equilibrium approach—has become so mesmerized with its own internal logic that it has begun to confuse the precision it has achieved about its own world with the precision that it has about the real one. This is dangerous for both methodological and policy reasons. On the methodology front, macroeconomic research has been in “fine-tuning” mode within the local-maximum of the dynamic stochastic general equilibrium world, when we should be in “broad-exploration” mode. We are too far from absolute truth to be so specialized and to make the kind of confident quantitative claims that often emerge from the core. On the policy front, this confused precision creates the illusion that a minor adjustment in the standard policy framework will prevent future crises, and by doing so it leaves us overly exposed to the new and unexpected.
The dynamic stochastic general equilibrium strategy is so attractive, and even plain addictive, because it allows one to generate impulse responses that can be fully described in terms of seemingly scientific statements. The model is an irresistible snake-charmer. In contrast, the periphery is not nearly as ambitious, and it provides mostly qualitative insights.
Moreover, this tension is not new to macroeconomics or even to economics more broadly. In his Nobel-prize acceptance lecture, Hayek writes:
“Of course, compared with the precise predictions we have learnt to expect in the physical sciences, this sort of mere pattern predictions is a second best with which one does not like to have to be content. Yet the danger of which I want to warn is precisely the belief that in order to have a claim to be accepted as scientific it is necessary to achieve more. This way lies charlatanism and worse. To act on the belief that we possess the knowledge and the power which enable us to shape the process of society entirely to our liking, knowledge which in fact we do not possess, is likely to make us do much harm” (von Hayek, 1974).
One reading of Hayek's comment is as a reminder of the dangers of presuming a precision and degree of knowledge we do not have.
There is no doubt that the formalization of macroeconomics over recent decades has increased its potential. We just need to be careful to not let this formalization gain its own life and distract us from the ultimate goal, which is to understand the mechanisms that drive the real economy. The idea is to place at the center of the analysis the fact that the complexity of macroeconomic interactions limits the knowledge we can ever attain.
I am almost certain that if the goal of macroeconomics is to provide formal frameworks to address real economic problems rather than purely literature-driven ones, we better start trying something new rather soon. The alternative of segmenting, with academic macroeconomics playing its internal games and leaving the real world problems mostly to informal commentators and “policy” discussions, is not very attractive either, for the latter often suffer from an even deeper pretense-of-knowledge syndrome than do academic macroeconomists.
Core and Periphery
The ultimate goal of macroeconomics is to explain and model the (simultaneous) aggregate outcomes that arise from the decisions made by multiple and heterogeneous economic agents interacting through complex relationships and markets. Neither the core nor the periphery is able to address this incredibly ambitious goal very satisfactorily. The periphery has focused on the details of the subproblems and mechanisms but has downplayed distant and complex general equilibrium interactions. The core has focused on (extremely stylized) versions of the general equilibrium interactions and has downplayed the subproblems.
The natural next step for the core, many would argue, is to add gradually the insights of the periphery into its dynamic stochastic general equilibrium structure. I am much less optimistic about this strategy, as I think it is plagued by internal inconsistencies and pretense-of-knowledge problems.
I believe that up to now the insight-building mode (both past and present) of the periphery of macroeconomics has proven to be more useful than the macro-machine-building mode of the core to help our understanding of significant macroeconomic events. I believe it would be good for macroeconomics to (re)orient a larger share of its human capital in this direction, not just for the study of crises but also for its broader concerns. It is only natural for macroeconomists to want more, but it is the rushed process to fulfill this ambition that I believe has led the core right into Hayek’s pretense-of-knowledge syndrome.
If we were to simply use these stylized structures as just one more tool to understand a piece of the complex problem, and to explore some potentially perverse general equilibrium effect which could affect the insights isolated in the periphery, then I would be fine with it. My problems start when these structures are given life on their own, and researchers choose to "take the model seriously" (a statement that signals the time to leave a seminar, for it is always followed by a sequence of naive and surreal claims).
My point is that by some strange herding process the core of macroeconomics seems to transform things that may have been useful modeling short-cuts into a part of a new and artificial “reality,” and now suddenly everyone uses the same language, which in the next iteration gets confused with, and eventually replaces, reality. Along the way, this process of make-believe substitution raises our presumption of knowledge about the workings of a complex economy, and increases the risks of a “pretense of knowledge” about which Hayek warned us.
After much trial and error, these core models have managed to generate reasonable numbers for quantities during plain-vanilla, second-order business cycle fluctuations. However, the structural interpretation attributed to these results is often naïve at best, and more often is worse than that.
A theory is no longer testable when rejection is used not to discard the theory, but to select the data moments under which the core model is to be judged. This practice means that well-known major failures just become “puzzles,” which are soon presumed to be orthogonal to the output from the quantitative model that is to be taken “seriously.”
By now, there are a whole set of conventions and magic parameter values resulting in an artificial world that can be analyzed with the rigor of micro-theory but that speaks of no particular real-world issue with any reliability.
However, I think this incremental strategy may well have overshot its peak and may lead us to a minimum rather than a maximum in terms of capturing realistic macroeconomic phenomena. We are digging ourselves, one step at a time, deeper and deeper into a Fantasyland, with economic agents who can solve richer and richer stochastic general equilibrium problems containing all sorts of frictions.
Given the enormous complexity of the task at hand, we can spend an unacceptably long time wandering in surrealistic worlds before gaining any traction into reality.
We ultimately need to revisit the ambitious goal of the core, of having a framework for understanding the whole, from shocks to transmission channels, all of them interacting with each other. The issue is how to do this without over-trivializing the workings of the economy (in the fundamental sense of overestimating the power of our approximations) to a degree that makes the framework useless as a tool for understanding significant events and dangerous for policy guidance.
Facing and Embracing Economic Complexity
One of the weaknesses of the core stems from going too directly from statements about individuals to statements about the aggregate. The nodes of economic models are special, for they contain agents with frontal lobes who can both strategize and panic, and it is these features that introduce much of the unpredictability in the linkages I mentioned earlier.
Haldane (2009) compares the recent financial crisis to the Severe Acute Respiratory System (SARS) outbreak earlier in the decade. Morbidity and mortality rates from SARS were, “by epidemiological standards, modest.” Yet SARS triggered a worldwide panic, reducing growth rates across Asia by 1–4 percentage points. Parents kept their children home from school in Toronto, and Chinese restaurants in the United States were the targets of boycotts. Faced with Knightian uncertainty, people conflated the possibility of catastrophe with catastrophe itself.
Some Policy Implications of a Confusing Environment
[Sanjeev's note: In this section, Caballero deteriorates into a confused Keynesian, and starts prescribing statist interventions of all sort. Let me warn you in advance about this section!!]
We need to rework the mechanism the core currently. The problem is that we do not know the mechanism, not just that we don’t know its strength.
For now, we shouldn't pretend that we know more than this, although this is no reason to give up hope. We have made enormous progress over the last few decades in the formalization of macroeconomics. We just got a little carried away with the beautiful structures that emerged from this process.
[These guys don't give up even after the theory has failed. Sanjeev]
The Pretense of Knowledge
The root cause of the poor state of affairs in the field of macroeconomics lies in a fundamental tension in academic macroeconomics between the enormous complexity of its subject and the micro-theory-like precision to which we aspire. The modern core of macroeconomics swung the pendulum to the other extreme, and has specialized in quantitative mathematical formalizations of a precise but largely irrelevant world.
From a policy perspective, the specifics of a crisis are only known once the crisis starts. For this reason, my sense is that, contrary to the hope of policymakers and regulators, there is limited scope for policy that can in advance eliminate the risk or costs of financial crisis, beyond some common-sense measures (like capital requirements for financial institutions) and very general public–private insurance arrangements (like deposit insurance).
The challenges are big, but macroeconomists can no longer continue playing internal games. The alternative of leaving all the important stuff to the “policy”-types and informal commentators cannot be the right approach.
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