pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE …

__Abstract__ The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects … for forecasting weekly and monthly horizons. …

This paper revisits inflation forecasting using reduced-form Phillips curve forecasts, that is, inflation forecasts … evidence of autonomous variance breaks and inflation gap persistence. Through a real-time out-of-sample forecasting exercise … quarterly inflation relative to an extended range of forecasting models that are typically used in the literature. …

partial least squares (PLS) regression to extract dynamic factors from the data set. Our forecasting analysis considers ten …

installed based information and provide several ways in which installed base forecasting can be used. We discuss cases of … installed based forecasting at four companies and list the issues involved. Moreover, we provide some models to assess the value …

-of-sample forecasting exercise to study money-income Granger causality, both linear and nonlinear, we believe is new to the literature. The … forecasting results do not suggest that money is nonlinearly Granger causal for output. In fact, they show that by allowing money … to nonlinearly Granger cause output, the forecasting performance of the STVECM is significantly worsened. …

(p) model for all forecast horizons and different AR models for different horizons. Representation, estimation and forecasting …