achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian …

nonstationary or near nonstationary predictors. Unconditionally, the contribution of parameter estimation error to expected loss is … long run. Estimation of parameters for most models dominates imposing a unit root. It is for these models that the effects … implications arise from the dependence of forecast performance on nuisance parameters. Depending on these nuisance parameters …

exploit many predictors, and this chapter surveys these methods. The first group of methods considered is forecast combination … (forecast pooling), in which a single forecast is produced from a panel of many forecasts. The second group of methods is based … increasingly precise as the number of series increases) can be used to forecast individual economic variables. The third group of …

the bootstrapping technique, allow the ex ante probability of, for example, a negative GDP growth forecast for the current …