Working Paper: NBER ID: w13892
Authors: Lars E.O. Svensson; Noah Williams
Abstract: We study the design of optimal monetary policy under uncertainty in a dynamic stochastic general equilibrium models. We use a Markov jump-linear-quadratic (MJLQ) approach to study policy design, approximating the uncertainty by different discrete modes in a Markov chain, and by taking mode-dependent linear-quadratic approximations of the underlying model. This allows us to apply a powerful methodology with convenient solution algorithms that we have developed. We apply our methods to a benchmark New Keynesian model, analyzing how policy is affected by uncertainty, and how learning and active experimentation affect policy and losses.
Keywords: Optimal monetary policy; Uncertainty; Dynamic stochastic general equilibrium; Markov jump-linear-quadratic
JEL Codes: E42; E52; E58
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Uncertainty (D89) | Monetary Policy (E52) |
| Learning (C91) | Policy Outcomes (D78) |
| Uncertainty (D89) | Policy Outcomes (D78) |
| Experimentation (C90) | Policy Effectiveness (D78) |
| Learning Context (Y80) | Policy Outcomes (D78) |