Staff Working Paper No. 764
By Nikoleta Anesti, Ana Beatriz Galvão and Silvia Miranda-Agrippino
We propose a Release-Augmented Dynamic Factor Model (RA-DFM) that allows to quantify the role of a country’s data flow in nowcasting both early GDP releases, and subsequent revisions of official estimates. We use the RA-DFM to study UK GDP early revision rounds, and assemble a comprehensive and novel mixed-frequency dataset that features over 10 years of real-time data vintages. The RA-DFM improves over the standard DFM in real-time when forecasting the first release each quarter, and economic and survey data help forecasting the first revision round. Afterwards, the predictive content of the data flow is largely exhausted.
This version was updated in January 2020.
This dataset includes only the publicly available series used in both the staff working paper and the published (forthcoming in Journal of Applied Econometrics) versions of the paper. For any questions, please contact Nikoleta Anesti.