We provide evidence on the nature of the monetary policy transmission mechanism. To identify policy shocks in a setting with both economic and financial variables, we combine traditional monetary vector autoregression (VAR) analysis with high frequency identification (HFI) of monetary policy...

How do frictions in price setting influence monetary non-neutrality? We revisit this classic question in a quantitative menu cost model with multi-product firms that face idiosyncratic shocks with unsynchronized stochastic volatility. The model matches the unconditional distribution of price...

Forecasting models for output are presented to throw light on monetary transmission. Recent research finds multistep forecasting superior to recursive forecasting from a VAR model when structural breaks are present; there are important political and policy regime breaks in South Africa. The...

Despite convergence pressures, differences in housing and financial market institutions across the 15 member states of the European Union are still enormous. This paper argues that they have profound effects on the responsiveness of output and inflation in the different countries to changes in...

In this Paper we study the role of the exchange rate in conducting monetary policy in an economy with near-zero nominal interest rates as experienced in Japan since the mid-1990s. Our analysis is based on an estimated model of Japan, the United States and the euro area with rational expectations...

We propose a method for estimating a subset of the parameters of a structural rational expectations model by exploiting changes in policy. We define a class of models, midway between a vector autoregression and a structural model, that we call the recoverable structure. We provide an application...

We propose a classical approach to estimate factor-augmented vector autoregressive (FAVAR) models with time variation in the factor loadings, in the factor dynamics, and in the variance-covariance matrix of innovations. When the time-varying FAVAR is estimated using a large quarterly dataset of...