We develop a large Bayesian VAR (BVAR) model of the New Zealand economy that incorporates the conditional forecasting estimation techniques of Waggoner and Zha (1999). We examine the real-time forecasting performance as the size of the model increases using an unbalanced data panel. In a...

We analyse a large Bayesian Vector Autoregression (BVAR) containing almost one hundred New Zealand macroeconomic time series. Methods for allowing multiple blocks of equations with block-specific Bayesian priors are described, and forecasting results show that our model compares favourably to a...

Abstract We develop a Bayesian VAR (BVAR) to produce conditional forecasts for the New Zealand economy. In a real-time out-of-sample forecasting exercise, we find that the BVAR outperforms a selection of other time series models, and it yields forecasts of similar accuracy to the forecasts...

We develop a simple approach to identify economic news and monetary shocks at a high frequency. The approach is used to examine financial market developments in the United States following the Federal Reserve’s May 22, 2013 taper talk suggesting that it would begin winding down its...

Notwithstanding persistently-high unemployment following the Great Recession, inflation in the United States has been remarkably stable. We find that a traditional Phillips curve describes the behavior of inflation reasonably well since the 1960s. Using a non-linear Kalman filter that allows for...