ABSTRACT

Trade policy uncertainty is at an all-time high in the United States and continues to escalate. This paper empirically examined the ability of US trade policy uncertainty to predict global output volatility. To this end, a battery of econometric tests was employed—Toda and Yamamoto linear Granger causality test, nonparametric test for nonlinear causality, and nonlinear Granger causality test in frequency domain. Findings based on standard linear Granger causality tests suggested that US trade policy uncertainty is not a significant predictor of global output volatility. Further tests, however, showed that due to the presence of nonlinearities in the US trade policy uncertainty–global output volatility nexus, the linear Granger causality framework initially relied upon might have led to misspecification. Consequently, a nonparametric causality test was further conducted. The test results showed that in fact the US trade policy uncertainty is a significant predictor of global output volatility. To further verify the findings, the powerful frequency domain-based Granger causality test which is able to detect causality at short, medium and longer horizons was conducted. The test findings again confirmed that trade policy uncertainty emanating from the United States is a significant predictor of global output volatility.

摘要

贸易政策的不确定性在美国处于历史最高水平，并且还在不断升级。本文从经验上考察了美国贸易政策不确定性预测全球产出波动的能力。为此，采用了一系列计量经济学测试，包括Toda和Yamamoto线性Granger因果关系测试，非线性因果关系的非参数测试以及频域中的非线性Granger因果关系测试。基于标准线性格兰杰因果关系检验的发现表明，美国贸易政策的不确定性并不是全球产出波动的重要预测指标。然而，进一步的测试表明，由于美国贸易政策的不确定性（全球产出波动关系）中存在非线性，最初依赖的线性格兰杰因果关系框架可能会导致错误指定。所以，进一步进行了非参数因果关系检验。测试结果表明，实际上，美国贸易政策的不确定性是全球产出波动的重要预测指标。为了进一步验证这一发现，进行了基于频域的强大Granger因果关系测试，该测试能够在短，中和较长的水平范围内检测因果关系。测试结果再次证实，源自美国的贸易政策不确定性是全球产出波动的重要预测指标。