Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Espasa and Mayo provide consistent forecasts for an aggregate economic indicator and its basic components as well as for useful sub-aggregates. To do so, they develop a procedure based on single-equation models that includes the restrictions arisen from the fact that some components share common features. The classification by common features provides a disaggregation map useful in several applications. We discuss their classification procedure and suggest some issues that should be taken into account when designing an algorithm to identify subsets of series that share one common trend.