Climate uncertainty and tourism demand in China: new evidence from the QARDL model

Purpose Tourism literature mostly examines tourism impact on global warming, however, there are very few studies that capture the effects the other way round. With the current concerns about the climate change globally, this study explores the role of environmental instability on international tourist flow in a dynamic framework for a case of China. Design/methodology/approach To address the asymmetric and disentangling long- and short-term relationships, the quantile autoregressive distributed lag (QARDL) model has been employed to investigate the impacts of ecological footprint (EFP) and CO2 emissions on tourism arrivals in China during 1995–2018. Moreover, to estimate the impact of economic factors on tourism, real-gross-domestic-product (RGDP), real-effective-exchange-rate (RER) and trade-openness (TO) are incorporated. Findings The results show some asymmetric effects of both environmental instability and economic variables on tourist arrivals in China. The long- and short-run results indicate that economic growth enhances tourist arrivals for both the periods, however, lower RER and more TO attract tourist numbers for the lower quantiles in the long run. The Granger-causality test reveals the evidence of a bi-directional causality between tourism and EFP and CO2 emission. Research limitations/implications The quantile-based impacts of EFP and CO2 emissions on tourist arrivals provide significant policy implications for both tourism sector policymakers and environmentalists in China. Practical implications This study highlights the dynamic impacts on environmental instability on tourists’ arrivals by determining the EFP, CO2 emissions, RGDP, RER and TO using QARDL approach. Originality/value This study reflects a unique way of exploring environmental instability at tourism destinations through QARDL, signifying the EFP, CO2, RGDP, RER and TO.