In this paper, we assess whether and when multi-country studies pay off for forecasting inflation and output growth. Factor stochastic volatility is adopted to allow for cross-country linkages and model economies jointly. We estimate factors and rely on post-processing, rather than expert judgement, to obtain an estimate for the number of factors. This is different from most existing two-step approaches in the factor literature. Our approach is then used to extend the existing unobserved components model, which assumes that 34 economies are independent. The results suggest that allowing for cross-country linkages yields inflation and output growth forecasts that are highly competitive with those obtained from estimating economies independently. Zooming into the forecast performance over time reveals that allowing for cross-country linkages is of particular importance when interest centres on forecasting periods of uncertainty. Another key finding is that the estimated global factors are correlated with the domestic business cycle. We interpret this to mean that part of the variation captured in global factors reflects a global business cycle.

在本文中，我们评估了多国研究是否以及何时在预测通胀和产出增长方面取得成效。采用因子随机波动来允许跨国联系和模型经济共同。我们估计因素并依靠后处理而不是专家判断来获得因素数量的估计。这与因子文献中大多数现有的两步方法不同。然后，我们的方法被用来扩展现有的不可观察成分模型，该模型假设 34 个经济体是独立的。结果表明，考虑到跨国联系所产生的通胀和产出增长预测与独立估算经济体所获得的预测相比具有很强的竞争力。随着时间的推移放大预测表现表明，当兴趣集中在预测不确定时期时，考虑到跨国联系尤为重要。另一个重要发现是，估计的全球因素与国内商业周期相关。我们将此解释为全球因素中捕获的部分变化反映了全球商业周期。