Solar energy technology adoption and diffusion by micro, small, and medium enterprises: sustainable energy for climate change mitigation.

This research intends to identify influential factors in adopting and diffusing solar energy technology (SET) by micro-, small-, and medium-sized enterprises (MSMEs) in two tehsils of Multan district in Pakistan's Punjab province. To this end, the influential factors are identified through studying literature surveys and conducting questionnaires. Following that, partial least squares-based path modeling is employed.

Empirics on heterogeneous links among urbanization, the intensity of electric power consumption, water-based emissions, and economic progress in regional China.

This study investigates the heterogeneous causal linkages between urbanization, the intensity of electric power consumption, water-based pollutant emissions, and GRP in regional China by developing an urbanization-augmented "Stochastic Impacts by Regression on Population, Affluence, and Technology" (STIRPAT) model. A whole country panel of 29 provinces as well as region sub-panels of China, for the period 1999 to 2018, are estimated employing common correlated effects mean group approach (CCEMGA), which offers robustness against heterogeneous characteristics and cross-sectionally dependent series. From the theoretic modeling aspect, the intensity of electric power consumption and urbanization have been introduced as the determinants of water-based pollutant emissions in the STIRPAT modeling framework.

Revealing heterogeneous causal links among financial development, construction industry, energy use, and environmental quality across development levels.

This work investigates the dynamic heterogeneous causal links among financial development, construction industry, energy use, and environmental quality across the development levels, for 30 Chinese provinces during the period 2001-2016. For this purpose, a model of environmental quality has been constructed introducing the financial development and construction industry as endogenous factors. A Pedroni's cointegration is employed and found the long-run cointegrating mechanism among the variables of interest.