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. The results showed that (1) enterprises' size, perceived SET's ease of use, and perceived SET's reliability are the top three driving factors. (2) The perceived SET's price, perceived level of competition's pressure, and MSME's energy cost intensity are the barriers to the adoption and diffusion of SET, while the lack of technical knowledge about SET is a neutral factor. (3) Perceived SET's price, MSMEs' energy cost intensity, and enterprises' size are among the most important factors based on the effect size and path coefficients, while the lack of technical knowledge about SET, preferences of MSMEs' customers, and eco-labels and green stickers have lower importance. Since the adoption of SET is a rational decision that is concretely dependent on economic incentives, it is recommended to lower the price of SET to scale up the adoption and diffusion of SET by Pakistani MSMEs.

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. Based on empirical results, first, GRP growth has shown appealing behavior in the form of its heterogeneous impacts on water-based pollutant emissions growth in the case of different regions. For instance, its impact is noted to be positive and statistically significant for the western region, which turned positive but statistically insignificant for the intermediate region. And it further turned significantly negative in the case of the eastern region. We call this phenomenon as "development level-based emission mitigation effect." Second, in terms of the impact of GRP growth on urbanization, the "development-based urbanization ladder effect" has been found. Based on heterogeneous causal links, firstly, the existence of a positive bilateral causal link between the intensity of electric power consumption and GRP growth and urbanization and GRP growth has been validated. Secondly, a positive unidirectional causal link emerged from urbanization to the intensity of electric power consumption and water-based pollutant emissions growth. Thirdly, the causal connection between GRP growth and water-based pollutant emissions growth remained very interesting and of mixed nature. Based on empirical findings, useful policies are extended. Graphical abstract.

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. The dynamic common correlated effects mean group approach (DCCEMGA) is adopted to estimate the impact elasticities. Moreover, for robustness check, a sensitivity analysis is conducted employing common correlated effects mean group approach (CCEMGA). The main results are first, a two-way positive causal bridge is existent between gross domestic product (GDP) and energy use, construction industry and GDP, and financial development and GDP. In terms of the contribution of the construction industry to economic performance, construction industry-driven growth acceleration impact is observed. Second, a one-way positive causal link is identified running from financial development (both the banking sector and stock market) to the construction industry and is termed as finance-driven construction promotion effect. Also, a one-sided positive causal connection is operating from financial development and construction industry to energy use and carbon dioxide emissions. Finally, a standard environmental Kuznets curve (EKC), financial development-augmented EKC, and construction industry-augmented EKC hypotheses are found valid in the whole country and eastern region of China. Based on empirics, a regional heterogeneity has been observed in terms of the degree of impact and statistical significance while comparing the regional panels. The sensitivity analysis proved the empirical results to be robust and reliable. Moreover, based on the findings, policy recommendations are documented. Graphical abstract.