Green Development Efficiency and Its Influencing Factors in China’s Iron and Steel Industry

Abstract

Analyzing the potential for green development and its influencing factors is an important part of the energy savings and low-carbon economic growth of China’s iron and steel industry (ISI). Many studies have concentrated on improving the ISI’s energy use and pollution control efficiencies, analyzing the influencing factors from the perspectives of regions and firms. However, no study has focused on measuring the provincial green development efficiency (GDE) in the ISI. The selected driving forces of the GDE do not consider regional or industrial characteristics. In this study, based on provincial panel data for 2006–2015 in China, the GDE of the Chinese ISI was evaluated using the super-slack-based measure (super-SBM) model. China’s 28 provinces were divided into different groups through cluster analysis. Then, a Tobit model was constructed to explore the factors influencing the GDE. The key results show the following: (1) The GDE values decline, fluctuating from 0.628 in 2006 to 0.571 in 2015, decreasing by 1.1% annually. Among the provinces, wide differences exist in the GDE values for the ISI, with the highest average GDE value being observed in Beijing and the lowest in Shanxi. (2) The provinces with high R&D expenditure inputs and high GDE values are mostly located in the eastern region, while the provinces with low R&D expenditure inputs and low GDE values are located in the central and western regions. (3) The export demand, property structure, and capital investment have significant positive effects on the ISI’s GDE in the eastern and western regions, while the energy consumption structure and industry scale have negative impacts on the improvement of the GDE in the central region. (4) Specific policy recommendations for sustainable development in the ISI mainly include further strengthening investment in R&D, expanding exports, adjusting energy consumption structures, and deepening the reform of stated-own enterprises.

Evaluation of Green Development Efficiency of the Major Cities in Gansu Province, China

“…It suffices to say that GD's theoretical premise is the symbiotic relationship between natural, economic, and social systems and the complex positive and negative interactions between them [43]. Thus, in the context of this study, GD encompasses the constraints of pollutant treatment and utilization, ecological efficiency, social and economic development [27], energy consumption [27], and the efficient allocation of labor and capital input [28].…”

“…Moreover, the Chinese government views GD as an essential tool for human, ecological, and social development in the present and future. More importantly, the connotation of Chinese GD encompasses the living environment [23], rational energy consumption [28], pollutant emission reduction [10], natural resource conservation [46], and other issues related to sustainable development. As one of the top world economies, China's GD has far-reaching implications on global sustainable development and economic prosperity.…”

“…To intuitively understand GD dynamics, researchers introduced the concept of "efficiency" to quantify it [27,28]. From the theoretical analysis, green development efficiency is important because it provides a basis for comparing GD at the global, national, regional, and city levels.…”

“…However, there is room for improvement in Chinese GD due to unbalanced development among its regions and cities [21,33]. Earlier studies (e.g., [28]) show that GDE in Gansu is low and ranks 25th among the 30 Chinese provinces used in the study [30]. To this end, our knowledge of GD in the cities in Gansu province is still limited.…”

“…Green development can be viewed as a practical way of achieving sustainable development [27]. Based on panel data from 28 provinces in China and using research and development expenditure input as a key indicator, [28] found differences in green development efficiency (GDE) of the provinces with Beijing (1.273) and Shanxi (0.219) ranking the highest and lowest, respectively. Similarly, [29] reported that in spatial terms, China's green innovation efficiency is unbalanced across the 30 provinces considered in their study from 2009-2017.…”