Revealing heterogeneous causal links among financial development, construction industry, energy use, and environmental quality across development levels
2020
Ahmad, Munir | Jabeen, Gul | Hayat, Muhammad Khizar | Khan, Rana Ejaz Ali | Qamar, Shoaib
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
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