The role of economic conditions and sustainable rural development on the sustainability of tourism development: evidence from China.

At present, tourism is counted among those industries which have gained global attention due to rapid growth. Hence, a constant diversification in terms of destination is needed in tourism development. The recent trends of industry highlight the demand of alternative tourism types, among which nature-related tourism appears to be an emerging concept. In this regard, the present article investigates the impact of economic conditions and sustainable rural development on the sustainability of tourism development in China. The current research has gathered secondary data from the World Bank from 1981 to 2020. The quartile autoregressive distributed lag model has been applied to test the association between the variables. The results revealed that GDP, inflation, FDI, exchange rate, energy use, gross savings, and sustainable rural development have a significant and positive association with the sustainability of tourism development in China. Findings offer managerial implications recommending the local government to focus on the sustainability of rural development and economic conditions that may lead to the implementation of tourism-related development projects. This study also guides the policymakers in establishing policies related to tourism development using different economic conditions and sustainable rural development.

The effects of green growth, environmental-related tax, and eco-innovation towards carbon neutrality target in the US economy.

This study aims to examine the nexus between green growth and carbon neutrality targets in the context of the USA while observing the role of ecological innovation, environmental taxes, and green energy. For this purpose, data were collected from 1970 to 2015 for all the variables of interest. This research utilized the quantile autoregressive distributed lag (QARDL) method due to its various benefits, such as depicting the causality patterns based on different quantiles for different variables like green growth, ecological innovation, environmental taxes, and renewable energy. The findings through the QARDL method showed that the error correction coefficient was significant and negative with the expected negative sign for the different quantiles. The findings showed a significant and negative impact of green growth, square of green growth, ecological innovation, and environmental taxes in determining the carbon dioxide (CO2) emissions for the USA's economy under the long-run estimation. Meanwhile, the outcome for the short-term estimation confirmed that the past and lagged values of CO2 emission were significantly and negatively linked with the current and lagged values of CO2 emission. On the other hand, it was found that green growth and square of green growth, ecological innovation, environmental taxes, and renewable energy played their vital role in reducing haze pollution like PM2.5. Besides, this research also covers the limitations and policy implications.