We study optimal monetary and fiscal policy in a New Keynesian model where occasional declines in agents' confidence can give rise to persistent liquidity trap episodes. Unlike in the case of fundamental-driven liquidity traps, there is no straightforward recipe for mitigating the welfare costs...

We use a version of the New Area-Wide Model (NAWM) developed at the ECB in order to quantify the gains from monetary policy cooperation. The model is calibrated in order to match a set of empirical moments. We then derive the cooperative and (open-loop) Nash monetary policies, assuming that the...

We study optimal monetary policy in a flexible state-dependent pricing framework, in which monopolistic competition and stochastic menu costs are the only distortions. We show analytically that it is optimal to commit to zero inflation in the long run. Moreover, our numerical simulations...

How does the need to preserve government debt sustainability affect the optimal monetary and fiscal policy response to a liquidity trap? To provide an answer, we employ a small stochastic New Keynesian model with a zero bound on nominal interest rates and characterize optimal time-consistent...

We study how the use of judgement or add-factorsʺ in macroeconomic forecasting may disturb the set of equilibrium outcomes when agents learn using recursive methods. We isolate conditions under which new phenomena, which we call exuberance equilibria, can exist in standard macroeconomic...

This paper considers the nominal and real determinacy of equilibria under an exogenously specified path of interest rates in an economy in which taxation is either lump-sum or distortionary. Under lump-sum taxation, we confirm the well-known finding that equilibria display nominal...

This paper examines monetary policy implementation in a sticky price model. The central bank's plan under discretionary optimization is entirely forward-looking and exhibits multiple equilibrium solutions if transactions frictions are not negligibly small. The central bank can then implement...