Asymmetries in the Oil Market : Accounting for the Growing Role of China Through Quantile Regressions

This paper investigates the role of political tensions between the US and China and global market forces in explaining oil price fluctuations. To this end, we rely on quantile regressions—quantile autoregressive distributed lag (QARDL) error-correction model—to account for possible asymmetric effects of those determinants, depending on both the level of oil prices and the period. Our results show evidence of a quantile-dependent long-term relationship between oil prices and their determinants over the 1958-2022 period, with an exacerbated effect of US-China political tensions in times of high oil prices. Furthermore, this quantile-dependent cointegrating relationship is time-varying across quantiles, highlighting the increased role played by China in the oil market since the mid-2000s