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Measuring the Connectedness of the Global Economy

Matthew Greenwood-Nimmo, Viet Hoang Nguyen and Yongcheol Shin ()

International Journal of Forecasting, 2021, vol. 37, issue 2, 899-919

Abstract: We develop a technique to exploit forecast error variance decompositions to evaluate the macroeconomic connectedness embedded in any multi-country macroeconomic model with an approximate vector autoregressive (VAR) representation. We apply our technique to a large global VAR model covering 25 countries and derive vivid representations of macroeconomic connectedness. We find that the US exerts a dominant influence in the global economy and that Brazil, China, and the Eurozone are also globally significant. Recursive analysis over the period of the global financial crisis shows that shocks to global equity markets are transmitted rapidly and forcefully to real trade flows and real GDP.

Keywords: Generalised Connectedness Measures (GCMs); International linkages; Network analysis; Macroeconomic connectedness; Forecast error variance decomposition (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.ijforecast.2020.10.003

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Handle: RePEc:eee:intfor:v:37:y:2021:i:2:p:899-919