Differential impacts of the US–China trade war and the outbreak of COVID-19 on Chinese air quality

PurposeOver the last couple of years, the Chinese manufacturing sector was affected by the onset of the US–China trade war and the outbreak of coronavirus disease 2019 (COVID-19). In such a scenario air quality in China has encountered a shock, and the impacts of these two incidents are unknown. In this study, the authors analyze the convergence of air quality in China in the presence of multiple structural breaks and how the impacts of these two events are different from each other.Design/methodology/approachIn order to assess the nature of shocks in the presence of multiple structural breaks, unit root tests with multiple structural breaks are employed.FindingsThe results reveal that air quality in China is showing the sign of convergence, and it is consistent across 18 provinces which are worst hit by the outbreak of COVID-19. In the presence of transitory shocks, the impact of COVID-19 outbreak is found to be higher, whereas the impact of the US–China trade war is found to be more persistent. Lastly, the outbreak of COVID-19 has been found to have more impact on pollutants with higher severity of health hazard.Originality/valueTo the best of the authors’ knowledge, this is the first study that contributes to the empirical literature in terms of investigating the convergence of overall air pollution and individual air pollutants taking COVID-19 and the trade war into account.

Multiple structural breaks in cointegrating regressions: a model selection approach

In this paper, we propose a new approach to model structural change in cointegrating regressions using penalized regression techniques. First, we consider a setting with known breakpoint candidates and show that a modified adaptive lasso estimator can consistently estimate structural breaks in the intercept and slope coefficient of a cointegrating regression. Second, we extend our approach to a diverging number of breakpoint candidates and provide simulation evidence that timing and magnitude of structural breaks are consistently estimated. Third, we use the adaptive lasso estimation to design new tests for cointegration in the presence of multiple structural breaks, derive the asymptotic distribution of our test statistics and show that the proposed tests have power against the null of no cointegration. Finally, we use our new methodology to study the effects of structural breaks on the long-run PPP relationship.