methodology is presented, and via a large set of prediction experiments using the panel dataset of Stock and Watson (2005). One of … difficult to beat in forecasting competitions. In some sense, by using our approach to predictive factor proxy selection, one is …

macroeconomic indicators (not including spreads) perform best when forecasting inflation in non-volatile time periods, while …

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the … information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an … forecasting performance of our proposed model relative to most of the existing alternative specifications. While most of the …

Various inflation forecasting models are compared using a simulated out-of-sample forecasting framework. We focus on … the question of whether monetary aggregates are useful for forecasting inflation, but unlike previous work we examine a … some of our models. Our findings indicate that there are forecasting gains from allowing monetary aggregates to enter into …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …