Identificación de series con tendencias comunes para mejorar las previsiones de agregados

Espasa and Mayo-Burgos (2013) provide consistent forecasts for an aggregate economic indicator and its basic components as well as for useful sub-aggregates. To do this, 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 procedure and suggest some issues that should be taken into account when designing an algorithm to identify subsets of series with one common trend. We also provide a naive algorithm following those suggestions.