Microfoundations and the DSGE paradigm: Don't Say Goodbye to Evidence

Robert Hall and Michael Woodford are worthy recipients of the Nobel Memorial Prize in Economic Sciences, reflecting the profound influence their work has had on modern macroeconomics. They won the award for contributions to models built on microfoundations, capturing how individual agents’ actions affect macroeconomic outcomes; Woodford’s work is rooted in New Keynesian economics whereas Hall’s has a more empirical thrust. The citation stated that they “have developed new macroeconomic models that have significantly improved our ability to implement effective stabilisation policy [which] can reduce the economy’s peaks and troughs.” The effectiveness of these models is debatable, but the importance of individual decisions to macroeconomic outcomes is not.

While the intellectual ambition behind their work deserves recognition, I have reservations about the direction the discipline has taken in its wake. Indeed, when the Committee’s detailed assessment of their work claimed that the DSGE models resulting from this paradigm “turned out to be of great practical use, as [they] helped steer the economy onto the right path” after the 2008 recession, my antennae started to twitch. The standard models at that time did not incorporate a financial sector – they lacked a mechanism to evaluate policies such as bank recapitalisation and asset purchases, which were among the tools used to promote the post-2008 recovery. Although some models incorporated financial frictions, these were not adequately represented in many of the models central to the pre-crisis consensus.

This is no criticism of the recipients – they did not write the citation after all – and I have great respect for the intellectual abilities of Professors Hall and Woodford. But I have previously expressed reservations about microfounded DSGE models (here, for example) and the imprimatur of a Nobel award does not change my view. Microfounded models are intellectually sophisticated but their tractability often comes at the cost of assumptions that are difficult to reconcile with reality, while their forecasting performance has not clearly surpassed that of the semi-structural models they displaced.

The words of economist Mikhail Dmitriev in a LinkedIn post captured my views rather well: “the field seems to have reached something of an intellectual dead end. Michael Woodford's work … helped establish a powerful and mathematically rigorous framework that shaped decades of research. At the same time, I wonder whether the dominance of this framework has unintentionally narrowed the range of questions, methods, and ideas explored in mainstream macroeconomics. In terms of influence on the field, the prize is entirely deserved. But influence and progress are not necessarily the same thing. It is worth asking whether the intellectual direction that followed has ultimately brought us closer to understanding the real economy.”

Key criticisms of the microfoundations debate

Much of modern mainstream macroeconomics requires aggregate relationships to be derived from the optimising decisions of individual agents. The result is elegant, internally coherent models. But coherence is not the same as explanation, and the requirement has narrowed the range of acceptable answers without clearly improving empirical relevance or predictive power. The point of contention is not whether macroeconomic models should be informed by microeconomic behaviour, but whether every aggregate relationship must be derived from a particular form of individual optimisation, typically combined with rational expectations and equilibrium conditions. These are methodological issues and are not necessary conditions for microfounded analysis. 

Such models are based on the assumption of rational, forward-looking agents who understand their economic environment, form expectations about the future and optimise accordingly. But how do agents form expectations when the future is fundamentally uncertain? Rational expectations impose consistency between agents' expectations and the model, given the information available. But this does not establish that people actually form expectations in this way, particularly when they do not know the “correct” model of the economy. This apparent rigour conceals the arbitrariness of some of the underlying assumptions.

As I noted in my previous post, representative agent models do not capture the differences in household incomes and wealth that have a profound impact on macro outcomes. Nor do they account for financial constraints, market power and strategic interactions. Much of microfounded literature thus ignores the factors that make macro analysis both difficult and endlessly fascinating. The development of heterogeneous-agent models has helped address some of these shortcomings, but it also illustrates how much the results can depend on assumptions about behaviour and the distribution of economic resources.

Moreover, insisting that every relationship comes from an explicit optimisation problem encourages elaborate models whose conclusions depend heavily on functional forms and preference assumptions. Observed statistical relationships may be more stable, and more useful for forecasting, than structural equations derived from a particular theory. A relationship is not scientifically inferior merely because it was estimated rather than derived from first principles.

The literature also downplays institutional factors.  Corporate behaviour depends on factors such as governance, financing arrangements, market structure, bargaining power and uncertainty about demand. Wage formation reflects institutions and social norms, not just the solution to an optimisation problem. These features can be incorporated into microfounded models. But the more they have to accommodate institutions, conventions and changing behaviour, the less convincing the claim becomes that a single, narrowly specified form of microeconomics provides the necessary foundation for macroeconomic analysis.

Finally, and as noted by Mikhail Dmitriev above, other approaches to macroeconomics have been crowded out. Methods built on empirical regularities and econometric relationships do have their place, which gives an important role to semi-structural models. Less mainstream methods such as institutional analysis and stock-flow consistency are also increasingly acknowledged to be important, particularly in the field of finance. Stock-flow-consistent models, for example, ensure that flows of income and expenditure are consistent with the associated changes in financial assets and liabilities, helping to expose balance-sheet relationships that can be overlooked in more stylised frameworks.

Was Lucas right?

One of the reasons why the microfoundations field gained such traction was the criticism aimed by Robert Lucas – himself a Nobel Prize recipient – that estimated macro relationships can shift when policy regimes change. He was right about that, but we should not allow this to exercise a methodological veto over a lot of conventional econometric models. Indeed, microfounded models are not exempt from structural change, since their results depend on preferences, constraints and expectations that may themselves shift. The sensible response is to test for instability, investigate mechanisms and assess forecasting performance, not to assume theory-derived relationships are inherently policy-invariant.

Rational expectations became a central part of the response to the Lucas critique, by making agents' expectations consistent with the model they inhabit. But as I noted in this post, agents can behave sensibly given their information without knowing what is the “correct” model of the economy. They learn from experience, follow rules of thumb, imitate others and revise expectations as circumstances change. In an environment of change, an adaptive process may be more convincing than a fixed model of expectations. Rational expectations often assume away the biggest difficulty agents face: making decisions in a world whose structure they do not fully understand. Too often modern macroeconomics treats such fundamental uncertainty as a computational inconvenience, when in reality it is a core aspect of decision making.

It has not been all bad

We should, of course, acknowledge the good things that have emerged from the microfounded literature, which has provided some discipline on the macro field. Woodford’s framework and Hall’s empirical work provide a foundation on which more useful models may yet be built. The post-2008 move away from representative agent to heterogeneous agent models, prompted by evidence that households have very different marginal propensities to consume, challenged the assumption that a single representative household could adequately capture aggregate behaviour. And perhaps AI-based agents will prove to be another step on the road to better economic understanding.

Nor should we dismiss the Lucas critique. The experience of the Phillips curve provides some support for its central insight: the relationship between inflation and economic activity depends partly on how expectations are formed and how monetary policy is conducted. The breakdown of the original inflation-unemployment trade-off during the 1970s, when inflation expectations became less firmly anchored, and the subsequent flattening of the Phillips curve as monetary policy gained credibility, are consistent with Lucas’s proposition. This does not prove that rational expectations is the correct description of behaviour, or that microfounded models are necessarily superior. But it does suggest that models which treat historically estimated relationships as invariant can be misleading when used to assess changes in policy.

Moreover, Woodford’s work highlights the importance of a coherent welfare criterion. This was lacking in previous frameworks, so optimal-policy analysis was less well defined. Microfounded models have made welfare-based policy analysis more systematic by linking policy choices to the preferences and constraints of economic agents. Whether the criterion is reliable is another matter, since the output gap is unobservable and r* is poorly estimated in real time.

Last word

One of my biggest criticisms of the literature is that microfoundations create incentives to choose assumptions that make models mathematically manageable. The framework can then become a description of what economists know how to solve rather than a convincing representation of the economy. By ignoring financial crises and institutional change, we create stylised models that reflect the world as economists would like it to be, rather than how it is in reality.

This is not to say we should abandon microfoundations but the test of a macro model should be whether it helps us understand economic outcomes, forecast developments and assess policy. Recognition for an important intellectual contribution does not settle that methodological question. Indeed, Lawrence Klein received his Nobel Prize in 1980 “for the creation of econometric models and the application to the analysis of economic fluctuations and economic policies.” Within the next decade, much of the profession had abandoned the foundations of the large-scale structural models he pioneered, in favour of rational expectations and microfounded alternatives. Nobel recognition marks a contribution’s importance, not the permanence of its methods.