Forecasting Aggregates with Stochastic Aggregation Weights

Despite the fact that the aggregation weights of many macroeconomic aggregates are time-varying, much of the literature on forecasting aggregates considers the situation of fixed, time-invariant aggregation weights. In this study a framework for contemporaneous aggregation with stochastic weights is developed and different predictors for an aggregate are compared theoretically as well as with simulations. Two examples based on European unemployment and inflation series are used to illustrate the virtue of the theoretical setup and the forecasting results.