Understanding and forecasting aggregate and disaggregate price dynamics

There are doubts regarding the empirical benefits of forecast aggregation. Theoretical research clearly supports forecast aggregation but conflicting results exist in the empirical literature. We search the literature for empirical regularities. One important issue often cited is estimation error and papers which are unsupportive of forecast aggregation often have short spans of data. A second empirical regularity is that researchers frequently use a relatively small number of disaggregates. Our work finds that the greatest benefits to aggregation are realised when a large number of disaggregates are used. This is a natural consequence of the theoretical results. A second critical issue in forecast aggregation is model selection. We suggest a simple guide to model choice based on the empirical properties of the data. In this regard, the extent of comovements between the constituent series determines model choice.