The headline summarizes the observations of economist Paul De Grauwe, who takes central banks to task for their reliance on so-called Dynamic Stochastic General Equilibrium models (DSGE). De Grauwe objects to some of the fundamental assumptions embedded in them (consumers are rational and all have the same preferences, any disruptions are the result of external shocks, as opposed, say, to internal imbalances, such as misallocation or mispricing of capital).
Another issue that appears to be implicit in these models (and the consequences have been discussed in more detail by economist such as Axel Leijonhufvud, Richard Alford, and Tim Duy) is that the Fed views the economy as a closed system and has not made sufficient allowance for the impact of trade, particularly how cheap imports have led the central bank to misread domestic inflation (ie, excluding the trade sector) and adopt overly lax monetary policies. It seems that this mis-framing of the problem might have been aided and abetted by reliance on DGSE models.
Now it’s a given that any model of a system as complex as an economy is bound to have some shortcomings. But when analyses have biases and limitations, the best approach is to use multiple methodologies and use judgment and empirical cross-checks. Over-reliance on a particular methodology too often leads users to unwittingly default to it.
From De Grauwe at EuroIntelligence:
One of the surprising developments in macroeconomics is the systematic incorporation of the paradigm of the utility maximizing forward looking and fully informed agent into macroeconomic models. This development started with the rational expectations revolution of the 1970s, which taught us that macroeconomic models can only be accepted if agents’ expectations are consistent with the underlying model structure. The real business cycle theory (RBC) introduced the idea that macroeconomic models should be “micro-founded”, i.e. should be based on dynamic utility maximization of individuals. While RBC models had no place for price rigidities and other inertia, the New Keynesian School systematically introduced rigidities of all kinds into similar micro-founded models. These developments occurred in the ivory towers of academia for several decades until in recent years these models were implemented empirically in such a way that they have now become tools of analysis in the boardrooms of central banks. The most successful implementation of these developments are to be found in the Dynamic Stochastic General Equilibrium models (DSGE-models) that are increasingly used in central banks for policy analysis. It is no exaggeration to say that today a central bank that wishes to be respected has to have its own DSGE-model.
These developments are surprising for several reasons. First, while macroeconomic theory enthusiastically embraced the view that agents fully understand the structure of the world in which they operate, other sciences like psychology and neurology increasingly uncovered the cognitive limitations of individuals. We learn from these sciences that agents only understand small bits and pieces of the world in which they live, and instead of maximizing continuously taking all available information into account, agents use simple rules (heuristics) in guiding their behaviour and their forecasts about the future. They do this not because they are irrational, but rather because the complexity of the world is overwhelming. In a way it can be said that using heuristics is a rational response of agents who are aware of their limited capacity to understand the world.
A second source of surprise of the development of macroeconomic modeling in general and the DSGE-models in particular is that other branches of economics, like game theory and experimental economics have increasingly recognized the need to incorporate the limitations agents face in understanding the world. This has led to models that depart from the rational expectations paradigm. DSGE-models have been immune from this trend.
The rational expectations assumption embedded in DSGE-models has another far-reaching implication. When all agents understand how the world functions in all its complexities, there is only one “Truth”. Everybody understands the same Truth. The implication of this extra-ordinary assumption is that one can restrict the analysis to a “representative agent”. As a result, DSGE-models routinely restrict the analysis to a representative agent to fully describe how all agents in the model process information. There is no heterogeneity in the use and the processing of information in these models.
So, what do the DSGE-models teach us about the sources of macroeconomic fluctuations? They tell us a story in which rationality of superbly informed and identical agents reigns. Shocks from the outside occur continuously forcing these agents to re-optimize all the time, which they are eager to do. Unfortunately and inexplicably, the outside world imposes restrictions on this optimizing behaviour. These super-rational creatures would like to adjust their prices and wages instantaneously so as to maximize their utilities but they are prevented from doing so. They have to wait in line to adjust prices (“Calvo-pricing) and as a result they cannot achieve the optimum immediately. Thus, these outside shocks create distortions and departures from optimality. They also create slow adjustment in output and prices. A theory of the business cycles is born. Business cycles arise because exogenous shocks occur. These shocks are transmitted slowly into the economic system, producing protracted movements in output and prices.
Let’s apply this idea to real-life business cycles and let’s concentrate on the US business cycle since the 1990s. Here is the DSGE-story. Around the middle of the 1990s a productivity shock occurs. This raises permanent income of US consumers leading to a consumption boom. It also leads to more inflation and an interest rate hike by the Fed around 2001. After a brief slowdown, US consumption roars further on its upward path. Then suddenly in August 2007 an exogenous and unforeseen shock occurs, i.e. an increase in the financial risk premium. This changes the outlook for rational consumers and the US economy experiences a severe slowdown.
The problem with this business cycle theory is that it is not a theory of the business cycle. In DSGE-models cyclical movements are always triggered by outside shocks. They are not generated within the system. In fact they cannot be. The super-rational and fully informed creatures that populate the DSGE-models would arbitrage away any systematic cyclical movement in prices and output. Thus, our most popular macro economic model that is now used by central bankers has no theory of why after a boom comes a bust. Booms and busts always find their origin outside the macroeconomic landscape.
This is a very unsatisfactory view. The downturn in US economic activity since last year is the result of excesses in the boom experienced before. In this sense the bust is caused by the boom. It is not the result of some new and unexpected financial shock as the DSGE-models tell us.
Macroeconomics is about systematic fluctuations in output, employment and prices. Macroeconomics is also about social interactions between agents who do not understand very well how the world functions. As a result, they watch each other to get clues of what is going on in the world. This leads to herding and group behaviour. This social behaviour is at the core of macroeconomic fluctuations. Keynes gave this a name, “animal spirits”.
All this is absent in DSGE-models where agents who understand the complexity of the world, behave in an atomistic way. There is no need to learn from others, since each individual’s brain contains the full information. Everybody understands the “Truth”.
In his famous AER-article Hayek (1945) stressed that individuals have only very small parts of the available information in their brains. No individual can ever hope to understand and to process the full complexity of the world in which he lives. That’s why markets are so important. They are institutions that allow to efficiently aggregating the divers bits of information stored in individual brains. The socialist economists at the time in contrast assumed that there was one individual, “the planner”, who understood the whole picture, the Truth. By giving him all the power this all-knowing individual could compute all the relevant prices and so force the optimum on the system. Markets were not necessary in this view.
Paradoxically, the rational expectations assumption that is now embedded in macroeconomics created a model that, like in the socialist models of the past, assumes an all-knowing individual, who can compute the optimal plans and set the optimal prices. In such a world, markets are indeed not necessary. We can trust this one individual to do it right.
Macroeconomic modeling should go back to the old Hayekian idea that information is spread among many individuals and that markets are there to aggregate this information, without any individual able to comprehend the whole. This aggregation process is at the core of the macroeconomic fluctuations. Individuals are struggling to understand the complexity of the world. They form opposing beliefs about the “Truth”, but they are willing to learn from others. As a result, we obtain fluctuations in beliefs that have a self-fulfilling aspect and drive the business cycle. The challenge for macroeconomics is to model this aggregation process, instead of assuming it away.