Analyzing exchange rate uncertainty and bilateral export growth in China: A multivariate GARCH-based approach

Abstract

Dramatic changes to exchange rate policy for the world's largest exporter have arguably ushered in the optimal environment for studying the effects of exchange rate uncertainty on trade. This study builds on the recent literature by using an extremely general model that measures volatility using the flexible multivariate DCC-GARCH model to analyze the impact exchange rate uncertainty has on bilateral export growth for China's ten largest export markets. All model parameters are estimated simultaneously and lagged values of uncertainty are included for a full year, where significant effects are found. The more general methods potentially overcome issues associated with inefficient two-step methods and the assumption that volatility impacts are close to instantaneous. Using a comprehensive sample that spans 1994–2017, the paper presents evidence that exchange rate uncertainty has no impact on trade with the United States, which strongly contrasts a robust finding of trade deterring impacts for almost all remaining countries. The unifying methodology is also used to analyze nominal uncertainty itself. Here, it is found that Chinese inflation may be a positive contributor to risk in an environment where many exogenous events, such as the Asian currency crisis, are associated with periods of heightened yuan uncertainty.