This paper examines the relative importance of key variables for the prediction of international sugar prices. Understanding movements in world sugar prices helps policy-makers and participants in the sugar value chain to formulate effective investment strategies and forecast the effects of market shocks more accurately. We combine a Bayesian model averaging (BMA) technique to address specification uncertainty with an out-of-sample analysis to evaluate price predictability. Results show that world sugar quotations are mostly influenced by their own dynamics, changes in international staple food prices, sugar production costs, and macroeconomic variables. The predictability of the BMA is found to be generally high, compared with a sample of benchmark time series approaches.

中文翻译：

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预测国际糖价：贝叶斯模型平均分析

本文研究了关键变量对预测国际糖价的相对重要性。了解世界食糖价格的走势有助于食糖价值链的决策者和参与者制定有效的投资策略，并更准确地预测市场冲击的影响。我们将贝叶斯模型平均（BMA）技术（用于解决规格不确定性）与样本外分析相结合，以评估价格可预测性。结果表明，世界糖报价主要受其自身动态，国际主食价格变化，糖生产成本以及宏观经济变量的影响。与基准时间序列方法的样本相比，发现BMA的可预测性通常很高。