Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility

Wu, Ping (2024) Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility. International Journal of Forecasting, 40 (3). pp. 903-917. ISSN 0169-2070 (https://doi.org/10.1016/j.ijforecast.2023.07.005)

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Abstract

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.

ORCID iDs

Wu, Ping ORCID logoORCID: https://orcid.org/0000-0001-8023-8040;
CORE (COnnecting REpositories)