Exploring the impacts of tourism development and exchange rate on renewable energy demand in China: A nonlinear perspective

The demand for carbon-free or renewable energy sources is on the rise due to their role in boosting environmental performance and controlling emissions. The majority of previous research is based on the symmetry assumption while analyzing the association between tourism demand (TD), exchange rate volatility (ERV), and renewable energy consumption (REC). To plug this hole, this research scrutinizes the impact of TD and ERV on REC in China. To investigate the short and long-run implications of TD and ERV on REC, this analysis employs the autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) techniques. The study's innovative approach enhances its scientific value through a novel and insightful examination of the variables of interest. The linear model results indicate that TD has a positive and significant long-run impact on REC. Conversely, ERV has a negative and significant long-run impact on REC. The NARDL model finds that a positive TD shock significantly and positively affects REC in the long run, while a negative TD shock does not exert a noticeable impact on REC. A positive ERV shock significantly and negatively affects REC in the long term, whereas a negative ERV shock has an insignificant impact on REC. Conversely, only a positive ERV shock has a significant positive impact on REC in the short run. These findings imply that policymakers must adopt stable and reliable foreign exchange market policies and promote sustainable tourism practices at tourist hotspots.