
This paper studies how household inequality shapes the effects of the zero lower bound (ZLB) on nominal interest rates on aggregate dynamics. To do so, we consider a heterogeneous agent New Keynesian (HANK) model with an occasionally binding ZLB and solve for its fully non-linear stochastic equilibrium using a novel neural network algorithm. In this setting, changes in the monetary policy stance influence households’precautionary savings by altering the frequency of ZLB events. As a result, the model features monetary policy non-neutrality in the long run. The degree of long-run non-neutrality, i.e., by how much monetary policy shifts real rates in the ergodic distribution of the model, can be substantial when we combine low inflation targets and high levels of wealth inequality.
ddc:330, Statistics, Game theory, economics, finance, and other social and behavioral sciences, neural networks, nonlinear dynamics, non-linear dynamics, HANK models, E12, E58, heterogeneous agents, D31, E52, E31, E21, E43
ddc:330, Statistics, Game theory, economics, finance, and other social and behavioral sciences, neural networks, nonlinear dynamics, non-linear dynamics, HANK models, E12, E58, heterogeneous agents, D31, E52, E31, E21, E43
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
