This study aims to examine the impacts of changing US trade policy uncertainty (henceforth, TPU Index) on US bilateral trade balance with China from a nonlinear methodology perspective.
The nonlinear auto regressive distributed lag (ARDL) model, recently developed by Shin et al. (2014), is applied. This model decomposes the TPU Index series into its increases (TPU+) and decreases (TPU−) and creates two new TPU Index series.
Empirical findings indicate that increases in the TPU Index improve the US bilateral trade balance only in the short-run (no long-run impact). However, decreases in the TPU Index worsen the US trade balance in the short run but improve it in the long run. Apart from these effects detected on US–China bilateral trade balances, this empirical study draws the conclusion that changing trade policy uncertainty plays a significant determining role for bilateral trade volumes.
Decomposed TPU index with the nonlinear ARDL model enables us to examine the separate impacts of the changes in TPU+ and TPU− indexes on US bilateral trade balance with China. Therefore, this model may discover potentially concealed-hidden true impacts of TPU index on US bilateral trade balance with this country.
