Time series reconciliation through flexible least squares estimation

In the paper we optimize a procedure developed recently to reconcile time series by flexible least squares. previous version of author assumed prior knowledge weighting parameter μ Kalaba and Tesfatsion’s so-called “incompatibility cost function”. new version, this is estimated from sample using an iterative method based on Newton-Raphson algorithm. We test improved reconciling monthly growth rates Monthly Economic Activity Estimator (EMAE) Argentina with quarterly Gross Domestic Product. The results suggest that optimal levels would be close 1 (thevalue suggested Tesfatsion as value) but estimating instead keeping it fixed at hardly modifies reconciled series.