Dynamic connection between inward foreign direct investment, renewable energy, economic growth and carbon emission in China: evidence from partial and multiple wavelet coherence.

This paper presents a fresh understanding of the vigorous connection between inward FDI, renewable energy consumption, economic growth and carbon emission in the Chinese economy employing novel Morlet wavelet analysis. Wavelet correlation, continuous wavelet transform and partial and the multiple wavelet coherence analyses are applied on variables under study for data acquired during the period 1979 to 2017. The outcome of these analyses reveals that the connections among the variables progress over frequency and time. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages, although time domain reveals inconsistent associations among the considered variables. The wavelet analysis according to economic point of view supports that inward foreign direct investment (FDI) and renewable energy consumption help to enhance economic condition in Chinese economy. The results also suggested that inward FDI enhances the environmental degradation in medium and long run in China. The results emphasize the significance of having organized strategies by the policymakers to cope with huge environmental degradation occurred for a couple of decades in China.

Water resources and tourism development in South Asia: an application of dynamic common correlated effect (DCCE) model.

The current study explores the relationship between water resources and tourism in South Asia for the period of 1995-2017. The study employs the CIPS unit root test for stationarity of the variables and the CD test for cross-sectional dependence among cross-sectional units. As for the long-run parameters, a novel technique, known as dynamic common correlated effect (DCCE) model, is used which was recently developed by Chudik and Pesaran (J Econ 188:393-420, 2015b). The outcomes from the DCCE method suggest that water resources have a positive impact on tourism in South Asia. It is also proven that ignoring cross-sectional dependence among the cross-sectional units may bring about misleading outcomes. The findings of the study can be helpful for policymakers to understand the role of water resources in boosting tourism and contributing to the economic prosperity of South Asian countries.

Nexus of FDI, population, energy production, and water resources in South Asia: a fresh insight from dynamic common correlated effects (DCCE).

The purpose of this study is to explore the empirical relationship between foreign direct investment (FDI), population, energy production, and water resources in South Asia. The newly developed approach dynamic common correlated effects (DCCE) by Chudik and Pesaran (Journal of Econometrics 188:393-420, 2015a) for measuring co-integration has been applied in the present study. This procedure provides significant robust outcomes in the presence of cross-sectional dependence among the cross-sectional units. The findings confirmed that earlier models, such as mean group (MG), pooled mean group (PMG), and augmented mean group (AMG), which have been used in the literature for long data, provide misleading results in the presence of cross-sectional dependence among the cross-sectional units. A statistically significant and negative result has been observed between FDI, population, energy production, and water resources in South Asia. The governments of South Asian economies must encourage green FDI initiatives for water management, ensuring water security, securing natural resources for enhancing the sustainable development of regional economies.