Does industrial agglomeration improve effective energy service: An empirical study of China’s iron and steel industry

Wu, Rongxin; Lin, Boqiang

doi:10.1016/j.apenergy.2021.117066

Cited by 45 publications

(18 citation statements)

References 75 publications

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“…In addition to enhancing R&D innovation and technology introduction, the ISI should also improve its management and production structure. Firms need to avoid sloppy production and reduce the energy waste caused by human factors [ 76 ].…”

Section: Empirical Discussionmentioning

confidence: 99%

“…Data for each energy use are obtained from the Statistical Yearbook of each province and data for conversion factors comes from the China Energy Statistical Yearbook. For some provinces without energy data reports, we draw on the studies of [ 76 , 77 ] for estimation. The available official data generally contain statistics on energy consumption and do not include statistics on energy prices.…”

Section: Model Construction and Datamentioning

confidence: 99%

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Does Energy Efficiency Realize Energy Conservation in the Iron and Steel Industry? A Perspective of Energy Rebound Effect

Lin

2022

IJERPH

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The energy rebound effect may weaken the impact of energy efficiency improvement on energy consumption. Therefore, the rebound effect is an important consideration in energy and environmental policies. This study takes the iron and steel industry as the research object, which is a large energy consumption sector in China, and the improved technique is used to estimate the energy rebound effect. The study constructs the dynamic energy efficiency utilizing provincial data from 2000 to 2019. The energy rebound effect from factor substitution and output expansion is then calculated. The research further discusses regional differences in the energy rebound effect. The results indicate that the technical progress of the iron and steel industry promotes energy efficiency improvements. The eastern region shows the best energy efficiency performance, followed by the central area, and the western region performs the worst in energy efficiency. The industrial energy rebound effect is 0.4297, which partially offsets the energy reduction caused by energy efficiency improvements. Factor substitution and output growth produce the industrial energy rebound effect. Furthermore, the rebound effect exhibits distinct geographical features. The policy suggestions are finally proposed to mitigate the industrial rebound effect and achieve energy and carbon reductions.

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Section: Empirical Discussionmentioning

confidence: 99%

Section: Model Construction and Datamentioning

confidence: 99%

Does Energy Efficiency Realize Energy Conservation in the Iron and Steel Industry? A Perspective of Energy Rebound Effect

Lin

2022

IJERPH

Self Cite

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“…Therefore, the market competition degree of urban enterprises is measured by the number of private listed companies existing in the city in that year. (3) Industrial agglomeration ( agg ): location entropy, regional average concentration rate, and economic or employment density are often used to measure industrial agglomeration (Liu and Zhang 2021 ; Wang et al 2022a ; Wu and Lin 2021 ). Since the information industry is mainly included in the secondary and tertiary industries, this study uses the ratio of the sum of the output value of the secondary and tertiary industries to the urban construction land area to measure the degree of information industry agglomeration.…”

Section: Methodsmentioning

confidence: 99%

Can data center green reform facilitate urban green technology innovation? Evidence from China

Liu

Yang

2023

Environ Sci Pollut Res

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With the expansion of the digital information industry, the size of global data centers is exploding. As part of a high-energy-consuming industry, data centers can support sustainable urban development through green transformation. This study uses a quasi-natural experiment of China’s national green data center pilot policy implemented in 2015 to examine the impact of data center green transformation on green technology innovation in cities. Using a difference-in-difference (DID) analysis, this study finds that the national green data center pilot policy leads to higher levels of green technology innovation in cities, but the spillover effect of the policy on neighboring cities is insignificant. The mechanism test showed that the national green data center pilot policy could facilitate urban green technological innovation through capital deepening, market competition, and industrial agglomeration. In addition, the policy impact is more pronounced for cities with poorer environments, less civilization, high levels of network infrastructure, and more innovative endowments. The findings can provide new guidance for cleaner regional production from the standpoint of data center green development.

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“…Economic competition provokes a "race to the bottom" in energy and ecological efficiency. Wu and Lin (2021) and Zakari et al (2022) deem that local governments may take the strategy of reducing tax revenues or relaxing environmental regulations or both the aforementioned in order to win a competitive edge and increase the tax base. Local government tax competition aggravates environmental pollution.…”

Section: Government Competition and Energy Efficiencymentioning

confidence: 99%

Government competition, corruption and green total factor energy efficiency: An empirical analysis from china

Zhao

Yan

Yang

et al. 2022

Front. Environ. Sci.

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Currently, global warming and resource and environmental constraints are becoming formidable. Improving green total factor energy efficiency (GTFEE) is an effective tactic to alleviate carbon emissions and resource scarcity, and also a practical demand for the sustainable and healthy development of China’s economy. This study applies the super efficiency SBM model to calculate GTFEE of China’s 30 provinces over the period from 2006 to 2020, and then the dynamic spatial Durbin model (SDM) is employed to investigate the impact of government competition on GTFEE. Furthermore, the influence path between government competition and GTFEE is identified by the intermediary effect model. The findings reveal that as a whole, local government competition has undermined GTFEE both in local and adjacent areas, but significant differences exist in different regions. After the robustness tests, the conclusions remain valid. The intermediary effect results show that government competition indirectly inhibits GTFEE by triggering corruption. Based on this, policymakers should establish an effective performance appraising for local governments to spark a cycle of virtuous competition and cooperation among regions. Meanwhile, the anti-corruption system should be improved so as to shape a favorable institutional atmosphere for the improvement of GTFEE, and ultimately promote the sustainable development of China’s economy.

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Does industrial agglomeration improve effective energy service: An empirical study of China’s iron and steel industry

Cited by 45 publications

References 75 publications

Does Energy Efficiency Realize Energy Conservation in the Iron and Steel Industry? A Perspective of Energy Rebound Effect

Does Energy Efficiency Realize Energy Conservation in the Iron and Steel Industry? A Perspective of Energy Rebound Effect

Can data center green reform facilitate urban green technology innovation? Evidence from China

Government competition, corruption and green total factor energy efficiency: An empirical analysis from china

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