Measuring the Connectedness of the Global Economy
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 countr...
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| Veröffentlicht in: | International journal of forecasting 2021-04, Vol.37 (2), p.899-919 |
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| container_issue | 2 |
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| container_title | International journal of forecasting |
| container_volume | 37 |
| creator | Greenwood-Nimmo, Matthew Nguyen, Viet Hoang Shin, Yongcheol |
| description | 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. |
| doi_str_mv | 10.1016/j.ijforecast.2020.10.003 |
| format | Article |
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| ispartof | International journal of forecasting, 2021-04, Vol.37 (2), p.899-919 |
| issn | 0169-2070 1872-8200 |
| language | eng |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Analysis Conferences and conventions Economic aspects Forecast error variance decomposition Generalised Connectedness Measures (GCMs) Global economy International linkages Macroeconomic connectedness Macroeconomics Measurement Network analysis Social aspects |
| title | Measuring the Connectedness of the Global Economy |
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