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.