Learning to Live in a Liquidity Trap
The Taylor rule in combination with the zero lower bound on nominal rates has been shown to create an unintended liquidity-trap equilibrium. The relevance of this equilibrium has been challenged on the basis that it is not stable under least-square learning. In this paper, we show that the liquidity-trap equilibrium is stable under social learning. The learning mechanism we employ includes three realistic elements: mutation, crossover, and tournaments. We show that agents can learn to have pessimistic sentiments about the central bank's ability to generate price growth, giving rise to a stochastically stable environment characterized by deflation and stagnation.
We thank for comments seminar participants at the July 2017 Stony Brook Workshop on Theoretical and Experimental Macroeconomics. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.