Much has been made of the failure of modern macroeconomics to predict or understand the
Great Recession of 2007–2009. In this MACRO FOCUS, our resident time-series econo-
metrician, James Morley*, explains what is currently meant by “modern” macroeconomics,
what is behind its failure, and what can be done to rehabilitate its reputation.
In a recent essay, Narayana Kocherlakota, President of the Federal Reserve Bank of Min-
neapolis, acknowledged that modern macroeconomics failed during the recent financial crisis.
However, his essay misses the point of why it failed.
Like many in academia, Kocherlakota associates modern macroeconomics with a particular
school of thought that takes something called the “Lucas critique” as its guiding principle. The
Lucas critique refers to an argument put forth by the Nobel Prize-winning macroeconomist
Robert Lucas about how the changing expectations of economic agents will confound fore-
casting and policy analysis based on macroeconomic data.
Its main implication is that an eco-
nomic model with “deep structural parameters” related to preferences and technology for
households and firms should provide more reliable forecasts, especially when predicting the
effects of policy, than a model based more on the apparent historical correlations between
macroeconomic variables. This is sometimes referred to as the “microfoundations” approach
to macroeconomics because it presumes that a microeconomic structure — in particular, the
metaphor of optimizing economic agents— is more robust to changes in the policy environ-
ment than macroeconomic correlations.
Rather than question the relevance of the Lucas critique, Kocherlakota explains the recent fail-
ure of modern macroeconomics as due to much narrower issues. In his view, the micro-found-
ed models failed because they lack sufficient complexity, especially in terms of their treatment
of financial markets. Also, he points out, rightly, that the models are driven by “patently unre-
However, the rehabilitation of modern macroeconomics requires a different tack than sug-
gested by Kocherlakota. In particular, macroeconomists need to do more than simply add
complexity to their models. They should also remember that it is empirically testable whether
models that put most of their weight on “deep structural parameters” produce more accurate
predictions than models that put more weight on historical correlations. In doing so, it may
Volume 5, Number 2
June 24, 2010
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* Without implicating anyone, the author wishes to thank Joel Prakken, Ken Matheny, Antulio Bomfim, Alan Auerbach, Tara Sin-