Forecasting contemporaneous aggregates with stochastic aggregation weights

Many contemporaneously aggregated variables have stochastic aggregation weights. We compare different forecasts for such variables, including univariate forecasts of the aggregate, a multivariate forecast of the aggregate that uses information from the disaggregated components, a forecast which aggregates a multivariate forecast of the disaggregate components and the aggregation weights, and a forecast which aggregates univariate forecasts of individual disaggregate components and the aggregation weights. In empirical illustrations based on aggregate GDP and money stock series, we find forecast mean squared error reductions when information in the stochastic aggregation weights is used.