In this paper, we analyze the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk and economic policy uncertainty in the US within a time-frequency framework. The coherence wavelet method and the wavelet-based Granger causality tests applied to US recent daily data unveil the unprecedented impact of COVID-19 and oil price shocks on the geopolitical risk levels, economic policy uncertainty and stock market volatility over the low frequency bands. The effect of the COVID-19 on the geopolitical risk substantially higher than on the US economic uncertainty. The COVID-19 risk is perceived differently over the short and the long-run and may be firstly viewed as an economic crisis. Our study offers several urgent prominent implications and endorsements for policymakers and asset managers.
The present paper implements the quantile autoregressive lagged (QARDL) approach of Cho et al. (2015) and the Granger causality in quantiles tests of Troster et al. (2018) to explore the nonlinear effects of US energy consumption, economic growth, and tourist arrivals on carbon dioxide (CO2) emission. Our results unveil the existence of substantial reversion to the long-run equilibrium connectedness between the variables of interest and CO2 emissions. The outcomes show that tourist arrivals decrease CO2 emissions in the long term for each quantile. In addition, we found that the output growth positively influences the carbon emissions at lower quantiles but negatively influences the carbon emissions at upper quantiles. Moreover, our findings of short-term dynamics validate an asymmetric short-run effect of tourist arrivals and economic growth on CO2 emissions in the US economy. Further results and their corresponding policy implications are discussed.