Assessing the impact of China's trade policy uncertainty on the dry bulk shipping freight rates
Keywords:
BDI, China, TPU, ANN, Out-of-sample forecast performance, Trade Policy Uncertainty, dry bulk market, Artificial Neural NetworksAbstract
The impetus for our research lies in the multifaceted and pivotal role of China in the dry bulk market, encompassing its positions as a leading global exporter, a dominant shipbuilder, and a major shipowner. However, the effects of uncertainty arising from trade policy and particularly Chinese trade policy (CTPU) on the dynamics of the dry bulk market have remained unexplored by empirical studies. This study addresses this gap by analyzing the impact of CTPU on the Baltic Dry Index (BDI),
a key indicator of international trade and the global economy.
Performing the Granger causality test and the impulse response function, we demonstrate a decline in sea-transportation demand and cost in the dry bulk market due to a spike in CTPU, yielding results consistent with option theory. This effect is observed across all BDI sub-indices and lasts approximately one year, by the end of which the markets fully recover. By developing artificial neural networks, we effectively avoid in-sample bias and underscore the out-of-sample predictability of
CTPU on BDI, establishing it as a key determinant of the latter.
Based on our findings, we propose strategies for various maritime stakeholders and supply chain managers to maximize profitability and enhance operational efficiency in transportation.
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Copyright (c) 2025 DIMITRIS Georgoulas, Stratos Papadimitriou
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