Fully reconciled probabilistic GDP forecasts from Income and Expenditure sides


Tommaso Di Fonzo, Daniele Girolimetto


October 2022

   Publication details

Book of Short Papers SIS 2022. Ed. by A. Balzanella, M. Bini, C. Cavicchia, and R. Verde. Pearson, pp. 1376–1381. ISBN: 9788891932310


We propose a complete reconciliation procedure of probabilistic GDP forecasts, resulting in GDP forecasts coherent with both Income and Expenditure sides’ forecasted series, and evaluate its performance on the Australian quarterly GDP series, as compared to the original proposal by Athanasopoulos et al. (2020)1.

  • 1 Athanasopoulos, G., Gamakumara, P., Panagiotelis, A., Hyndman, R.J., Affan, M. (2020), Hierarchical Forecasting, in Fuleky, P. (ed.), Macroeconomic Forecasting in the Era of Big Data, Cham, Springer, 689–719.