Greenwood-Nimmo, Matthew, Nguyen, Viet and Shin, Yongcheol (2021) Measuring the Connectedness of the Global Economy. International journal of forecasting. pp. 899-919. ISSN 0169-2070
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 rapidly and forcefully transmitted to real trade flows and real GDP.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2020 International Institute of Forecasters. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. |
Keywords: | Generalised Connectedness Measures (GCMs),international linkages,network analysis,macroeconomic connectedness,forecast error variance decomposition |
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Economics and Related Studies (York) |
Depositing User: | Pure (York) |
Date Deposited: | 18 Nov 2020 10:30 |
Last Modified: | 20 Mar 2025 00:09 |
Published Version: | https://doi.org/10.1016/j.ijforecast.2020.10.003 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.ijforecast.2020.10.003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168121 |
Download
Filename: _R3_GNS_GC.pdf
Description: Measuring the Connectedness of the Global Economy
Licence: CC-BY-NC-ND 2.5