Journal article
Measuring the Connectedness of the Global Economy
Matthew Greenwood-Nimmo, Viet Nguyen, Yongcheol Shin
International Journal of Forecasting | Elsevier | Published : 2021
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.
Grants
Funding Acknowledgements
We are grateful for the insightful comments of Heather Anderson, Sang-Don Bu, Efrem Castelnuovo, Woonkyu Choi, John Hunter, YongMin Kim, Vance Martin, Faek Menla Ali, Kostas Mouratidis, Adrian Pagan, Hail Park, Hashem Pesaran, Kalvinder Shields, Peter Smith, Ron Smith, Benjamin Wong, and Tomasz Wozniak. This work has benefited greatly from the stimulating discussion of delegates at the 21st Annual Symposium of the Society for Nonlinear Dynamics and Econometrics (Milan, March 2013), the Annual Conference of the Scottish Economic Society (Perth, April 2013), the BMRC-QASS Conference on Macro and Financial Economics (London, May 2013), the Econometrics of Social Interaction Symposium (York, May 2013), the 9th International Symposium on Econometric Theory and Applications (Seoul, July 2013), the Econometric Society Australasian Meeting (Sydney, July 2013), the Asian Meeting of the Econometric Society (Singapore, August 2013), the 45th Annual Conference of the Money, Macro and Finance Research Group (London, September 2013), the Econometrics Workshop at Victoria University of Wellington (November 2013), the 11th World Congress of the Econometric Society (Montreal, August 2015), and the 69th European Meeting of the Econometric Society (Geneva, August 2016), as well as the many detailed comments raised by seminar participants at Deakin and Monash Universities, the Universities of Lecce, Melbourne, Seoul, Sheffield, Sogang, Utah, Yonsei and York, the Melbourne Institute: Applied Economic and Social Research, the Sheffield Methods Institute, the Bank of Korea, and the Reserve Bank of New Zealand. Greenwood-Nimmo gratefully acknowledges financial support from the University of Leeds Seedcorn Fund, United Kingdom and the kind hospitality of the Universities of Sheffield and York during visits in 2013-5 when a substantial part of this work was conducted. Nguyen acknowledges funding from the Faculty of Business and Economics at the University of Melbourne, Australia. Shin acknowledges the hospitality of the Melbourne Institute: Applied Economic and Social Research and the Bank of Korea during research visits in the period April-July 2014. The usual disclaimer applies.