A prophecy that misread could have been...


Evans and Honkapohja: What else has learning theory contributed?
Sargent: A couple of important things. First, it contains some results about rates of convergence to a rational expectations equilibrium that can be informative about how difficult it is to learn an equilibrium. Second, we have discovered that even when convergence occurs with probability one, sample paths can exhibit exotic trajectories called “escape routes.” These escape routes exhibit long-lived departures from a self-confirming equilibrium and can visit objects that qualify as “near equilibria.” The escape paths can be characterized by an elegant control problem and contribute a form of “near rational” dynamics that can have amazing properties. I first encountered these ideas while working on my Conquest book. In-Koo Cho and Noah Williams have pushed these ideas further. I suspect that these escape routes will prove to be a useful addition to our toolkit. For example, they can sustain the kind of drifting parameters that Lucas brought out in the first part of his Critique, but that, until recently, most of us have usually refrained from interpreting as equilibrium outcomes. A good example of the type of phenomena that drifting coefficients with escapes from a self-confirming equilibrium can explain is contained in the recent AER paper on recurrent hyperinflations by Albert Marcet and Juan Pablo Nicolini.
Evans and Honkapohja: With your coauthor Tim Cogley, you have been studying drifting coefficients and volatilities. Did Lucas’s Critique fuel your work with Cogley?
Sargent: Yes. Sims claims that while there is ample evidence for drifting volatilities, the evidence for drifting coefficients is weak. And he uses that fact to argue that U.S. data are consistent with time-invariant government monetary and fiscal policy rules throughout the post–World War II period. So when bad macroeconomic outcomes occurred, it was due to bad luck in the form of big shocks, not bad policy in the form of decision rules that had drifted into becoming too accommodating or too tight. It is true that detecting drifts in the AR coefficients in a VAR is much more difficult than detecting drifts in innovation volatilities—this is clearest in continuous time settings that finance people work in. (Lars Hansen has taught this to me in the context of our work on robustness.) Thus, Sims and other “bad luck, not bad policy” advocates say that the drift spotted by Lucas is misinterpreted if it is regarded as indicating drifting decision rules, e.g., drifting monetary policy rules. The reason is that, by in effect projecting in wrong directions, it misreads stochastic volatility as reflecting drift in agents’ decision rules. These are obviously very important issues that can be sorted out only with an econometric framework that countenances both drifting coefficients and drifting volatilities. Tim and I are striving to sort these things out, and so are Chris and Tao Zha and Fabio Canova.


Evans and Honkapohja
Evans and Honkapohja


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