A comparison of monthly global indicators for forecasting growth

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Authors

Baumeister, Christiane
Guerin, Pierre

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Publisher

Elsevier

Abstract

This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world real GDP growth using mixed-frequency models. It shows that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecasting accuracy, while other monthly measures have more mixed success. Specifically, the best-performing model yields impressive gains with MSPE reductions of up to 34% at short horizons and up to 13% at long horizons relative to an autoregressive benchmark. The global economic conditions indicator also contains valuable information for assessing the current and future state of the economy for a set of individual countries and groups of countries. This indicator is used to track the evolution of the nowcasts for the U.S., the OECD area, and the world economy during the COVID-19 pandemic and the main factors that drive the nowcasts are quantified.

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Keywords

MIDAS models, Global economic conditions, World GDP growth, Gross domestic product (GDP), Nowcasting, Forecasting, Mixed frequency, Pooling, COVID-19 pandemic, Coronavirus disease 2019 (COVID-19), Mean-squared prediction error (MSPE)

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Citation

Baumeister, C. & Guérin, P. 2021, 'A comparison of monthly global indicators for forecasting growth', International Journal of Forecasting, vol. 37, no. 3, pp. 1276-1295.