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Keeping track of global trade in real time

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  • Martínez-Martín, Jaime
  • Rusticelli, Elena

Abstract

This paper builds an innovative composite world trade-cycle index by means of a dynamic factor model for short-term forecasts of world trade growth of both goods and (usually neglected) services. Trade indicators are selected using a multidimensional approach, including Bayesian model averaging techniques, dynamic correlations, and Granger non-causality tests in a linear vector autoregression framework. To overcome 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. Pseudo-real-time empirical simulations suggest that: (i) the global trade index is a 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, a conclusion that is in line with the theoretical literature.

Suggested Citation

  • Martínez-Martín, Jaime & Rusticelli, Elena, 2021. "Keeping track of global trade in real time," International Journal of Forecasting, Elsevier, vol. 37(1), pages 224-236.
    • Handle: RePEc:eee:intfor:v:37:y:2021:i:1:p:224-236
    DOI: 10.1016/j.ijforecast.2020.04.005
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    2. 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.

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    More about this item

    Keywords

    Real-time forecasting; World trade; Bayesian model averaging; Dynamic factor model; Markov switching model;
    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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