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Modelling global trade flows: results from a GVAR model

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  • Matthieu Bussiere
  • Alexander Chudik
  • Giulia Sestieri

Abstract

This paper uses a Global Vector Auto-Regression (GVAR) model featuring 21 emerging market and advanced economies to investigate the factors behind the dynamics of global trade flows, with a particular view on the issue of global trade imbalances and on the conditions of their unwinding. The GVAR approach enables us to make two key contributions: first, to model international linkages among a large number of countries, which is a key asset given the diversity of countries and regions involved in global imbalances, and second, to model exports and imports jointly. The latter proves to be very important due to the internationalization of production chains. The model can be used to gauge the effect on trade flows of various scenarios, such as an output shock in the United States, a shock to the US real effective exchange rate and shocks to foreign (e.g., German and Chinese) variables. Results indicate that changes in domestic and foreign demand have a much stronger effect on trade flows than changes in relative trade prices. In addition, we show how the model can be used to monitor trade developments, with an application to the Great Trade Collapse.

Suggested Citation

  • Matthieu Bussiere & Alexander Chudik & Giulia Sestieri, 2012. "Modelling global trade flows: results from a GVAR model," Globalization Institute Working Papers 119, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddgw:119
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    JEL classification:

    • F10 - International Economics - - Trade - - - General
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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