Keeping Track of Global Trade in Real Time

32 Pages Posted: 21 Jul 2020

See all articles by Jaime Martinez-Martin

Jaime Martinez-Martin

Banco de España

Elena Rusticelli

Organization for Economic Co-Operation and Development (OECD)

Date Written: July 15, 2020

Abstract

This paper builds an innovative composite world trade cycle index (WTI) by means of a dynamic factor model to perform short-term forecasts of world trade growth of both goods and (usually neglected) services. The selection of trade indicator series is made using a multidimensional approach, including Bayesian model averaging techniques, dynamic correlations and Granger non-causality tests in a linear VAR framework. To overcome the real-time forecasting challenges, the dynamic factor model is extended to account for mixed frequencies, to deal with asynchronous data publication and to include hard and survey data along with leading indicators. Nonlinearities are addressed with a Markov switching model. In the empirical application, simulations analysis in pseudo real-time suggest that: i) the global trade index is a very useful tool for tracking and forecasting world trade in real time; ii) the model is able to infer global trade cycles very precisely and better than several competing alternatives; and iii) global trade finance conditions seem to lead the trade cycle, in line with the theoretical literature.

Keywords: real-time forecasting, world trade, dynamic factor models, markov switching models

JEL Classification: E32, C22, E27

Suggested Citation

Martinez-Martin, Jaime and Rusticelli, Elena, Keeping Track of Global Trade in Real Time (July 15, 2020). Banco de Espana Working Paper No. 2019, Available at SSRN: https://ssrn.com/abstract=3654008 or http://dx.doi.org/10.2139/ssrn.3654008

Elena Rusticelli

Organization for Economic Co-Operation and Development (OECD)

2 rue Andre Pascal
Paris Cedex 16, 75775
France

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