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Keeping track of global trade in real time

Author

Listed:
  • Jaime Martínez-Martín

    (Banco de España)

  • Elena Rusticelli

    (OECD)

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.

Suggested Citation

  • Jaime Martínez-Martín & Elena Rusticelli, 2020. "Keeping track of global trade in real time," Working Papers 2019, Banco de España.
    • Handle: RePEc:bde:wpaper:2019
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    References listed on IDEAS

    as
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    Cited by:

    1. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    2. Amélie Charles & Olivier Darné, 2022. "Backcasting world trade growth using data reduction methods," The World Economy, Wiley Blackwell, vol. 45(10), pages 3169-3191, October.

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    More about this item

    Keywords

    real-time forecasting; world trade; dynamic factor models; markov switching models;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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