Nowcasting global economic growth: A factor-augmented mixed-frequency approach
Laurent Ferrara and
Clément Marsilli
Post-Print from HAL
Abstract:
Facing several economic and financial uncertainties, assessing accurately global economic conditions is a great challenge for economists. The International Monetary Fund proposes within its periodic World Economic Outlook report a measure of the global GDP annual growth, that is often considered as the benchmark nowcast by macroeconomists. In this paper, we put forward an alternative approach to provide monthly nowcasts of the annual global growth rate. Our approach builds on a Factor-Augmented MIxed DAta Sampling (FA-MIDAS) model that enables (i) to account for a large monthly database including various countries and sectors of the global economy and (ii) to nowcast a low-frequency macroeconomic variable using higher-frequency information. Pseudo real-time results show that this approach provides reliable and timely nowcasts of the world GDP annual growth on a monthly basis.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (25)
Published in The World Economy, 2019, 42 (3), pp.846-875. ⟨10.1111/twec.12708⟩
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Journal Article: Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach (2019) 
Working Paper: Nowcasting global economic growth: A factor-augmented mixed-frequency approach (2014) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01636761
DOI: 10.1111/twec.12708
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).