Fully reconciled probabilistic GDP forecasts from Income and Expenditure sides

   Authors

Tommaso Di Fonzo, Daniele Girolimetto

   Published

October 6, 2022

   Publication details

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

   Links
Abstract

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.

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