The Trouble with Rational Expectations in Heterogeneous Agent Models: A Challenge for Macroeconomics

The thesis of this essay is that, in heterogeneous agent macroeconomics, the assumption of rational expectations about equilibrium prices is unrealistic, unnecessarily complicates computations, and should be replaced. This is because rational expectations imply that decision makers (unrealistically) forecast equilibrium prices like interest rates by forecasting cross-sectional distributions. The result is an extreme version of the curse of dimensionality: dynamic programming problems in which the entire cross-sectional distribution is a state variable ("Master equation" a.k.a. "Monster equation"). This problem severely limits the applicability of the heterogeneous-agent approach to some of the biggest questions in macroeconomics, namely those in which aggregate risk and non-linearities are key, like financial crises. This troublesome feature of the rational expectations assumption poses a challenge: what should replace it? I outline three criteria that alternative approaches should satisfy: (1) simplification of the computational solution, (2) consistency with empirical evidence, and (3) (some) immunity to the Lucas critique. I then discuss some potentially promising directions, including temporary equilibrium approaches, incorporating survey expectations, least-squares learning, and reinforcement learning.