The nexus of environmental quality with renewable consumption, immigration, and healthcare in the US: wavelet and gradual-shift causality approaches.

Given that the volume of carbon emissions in the US is a significant share of the global greenhouse gas emissions, some salient factors are being currently examined so as to reverse the threat to global environmental sustainability. To this regard, the current study investigates the co-movement and long-term and short-term causal relationship between CO2 emission (a proxy for environmental quality) and renewable consumption, immigration, and healthcare by using the wavelet coherence approach which primarily provides information on dynamic correlations over time and for different time scales. The coherence approach allows the one-dimensional time data into the bi-dimensional time-frequency sphere between the variables. In addition to investigating the causal relationship between CO2 and renewable consumption, immigration, and healthcare, this study also employs gradual-shift causality and Toda-Yamamoto causality tests. With this, the study found a high variation for CO2 emission in the US at 8 scales (8 quarters) from 1999 to 2008. Additionally, there is significant feedback causality between CO2 emission and renewable consumption at different scales while a positive correlation between the variables is observed in the short run. Similarly, the result reveals that immigration significantly causes CO2 emission in the US from 2008 to 2010 and a two-way causality is detected between CO2 emission and healthcare at different frequencies and time period. Moreover, the Toda-Yamamoto causality and gradual-shift causality tests provide supportive evidence to the outcomes of the wavelet coherence-based causality test in this study. Overall, the investigation offers significant policy directive especially toward addressing the potential adverse effects from the country's immigration and healthcare amendments.