This paper uses Meta-Granger analysis to explain and summarize the mixed results in the literature on the impact of financial speculation on commodity prices. The sample covers 2106 manually collected p-values from Granger causality (GC) tests reported in 54 prior studies. Our results show that the heterogeneity in previous findings can be largely explained by the commodity type under examination, the sample period of the data, the measurement of the focus variables (return, volatility, or spread), and the inclusion of control variables in the GC model. Even after accounting for 23 observable differences in study and test design, our results indicate that studies published in higher ranked journals present significantly less evidence for speculation to drive commodity prices. Moreover, we use the Meta-Granger results to predict ‘best choice’ models considering preferred model setups. The results reveal that the hypothesis of Granger non-causality between speculation and commodity prices cannot be rejected at standard significance levels when assuming a best choice study design and various variations of it. We conclude that either there is no genuine overall speculation effect in agricultural, energy and metal markets, or the research design of the frequently applied GC testing is not powerful enough to detect those effects.

本文采用Meta-Granger分析对文献中关于金融投机对商品价格影响的混合结果进行解释和总结。样本涵盖2106个人工采集的p- 54 项先前研究报告的格兰杰因果关系 (GC) 检验值。我们的结果表明，先前研究结果的异质性在很大程度上可以通过所检查的商品类型、数据的样本期、焦点变量（回报、波动性或价差）的测量以及控制变量的包含来解释。 GC 模型。即使在研究和测试设计中考虑了 23 个可观察到的差异后，我们的结果表明，发表在排名较高的期刊上的研究提供的投机推动商品价格的证据明显较少。此外，我们使用 Meta-Granger 结果来预测考虑首选模型设置的“最佳选择”模型。结果表明，当假设最佳选择研究设计及其各种变体时，在标准显着性水平上不能拒绝投机与商品价格之间的格兰杰非因果关系假设。我们得出结论，要么在农业、能源和金属市场中没有真正的整体投机效应，要么频繁应用的 GC 测试的研究设计不足以检测这些影响。