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.

本文评估了一组全球经济活动的替代性月度指标的预测内容，以便使用混合频率模型对世界实际GDP季度增长进行临近预报和预测。它表明，最近提出的涵盖全球经济多个维度的指标在预测准确性方面始终保持着重大改进，而其他月度指标则取得了不同的成功。特别是，相对于自回归基准，性能最佳的模型产生了令人印象深刻的收益，MSPE在短期内降低了34％，在长期内降低了13％。全球经济状况指标还包含有价值的信息，可用于评估一组单个国家和国家组的当前和未来经济状况。