Interstate energy efficiency of Indian paper industry: A slack-based non-parametric approach

Bhat, Javed Ahmad; Haider, Salman; Kamaiah, Bandi

doi:10.1016/j.energy.2018.07.138

Cited by 28 publications

(14 citation statements)

References 60 publications

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“…Industrial-level energy conservation and carbon emissions reduction have attracted wide attention of scholars. For example, Bhat et al (2018), Haider and Bhat (2019), , Haider and Mishra (2019) analyzed the energy efficiency of paper and iron and steel industry. As an emerging industry, high-tech industry is receiving increasing attention due to its role in sustainable economic growth and less environment burden.…”

Section: Literature Reviewmentioning

confidence: 99%

Direct and indirect impacts of high-tech industry development on CO2 emissions: empirical evidence from China

Liu

Wang

et al. 2020

Environ Sci Pollut Res

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Vigorously developing high-tech industry has been considered to be an effective way to coordinate economic growth with excessive carbon dioxide (CO 2) emissions. However, previous studies have not explored the heterogeneous impacts of hightech industry on CO 2 emissions in regions with different levels of high-tech industry development, and not distinguished the direct and indirect impacts. Based on STIRPAT model, this study investigates the impacts of high-tech industry development on CO 2 emissions in China between 2005 and 2016. Adopting the K-medians cluster method, effects in regions with high, middle, and low levels of high-tech industry development are considered. Indirect effects of high-tech industry development on CO 2 emissions by affecting industry structure upgrades and economic growth are explored. Empirical results illustrate a positive Ushaped nonlinear link between the level of high-tech industry development and CO 2 emissions at the national level and regional (high, middle, and low) level. In terms of indirect impacts, high-tech industry development attenuates the reduction of CO 2 emissions due to industry structure upgrades, and promotes economic growth to increase CO 2 emissions slightly. The indirect impact intensity gradually decreases as the level of high-tech industry development decreases across three regions. Reasonable implications of our findings are proposed. Keywords CO 2 emissions. High-tech industry. STIRPAT model. Heterogeneous effect. Nonlinear relationship Responsible editor: Eyup Dogan

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Section: Literature Reviewmentioning

confidence: 99%

Direct and indirect impacts of high-tech industry development on CO2 emissions: empirical evidence from China

Liu

Wang

et al. 2020

Environ Sci Pollut Res

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“…They found the statistically significant relationship and role of ISO certification in low‐carbon emission growth. Bhat, Haider, and Kamaiah () applied SBM and estimated feasible energy‐saving of Indian pulp and paper industry using region‐level data and found major energy efficiency gap among states. At state‐level, Haider and Mishra () show enormous energy efficiency gap across states and massive energy‐saving potential in the iron and steel industry.…”

Section: Literature Reviewmentioning

confidence: 99%

Reducing the energy consumption of Indian iron and steel industry through enhancing energy efficiency: Role of regional coordination

Haider

Mishra

2020

Journal of Public Affairs

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This article aims at estimating the energy efficiency of the iron and steel industry in production theoretic approach. Taking a regional perspective, we have done a meta‐frontier analysis combined with the slack‐based measure of data envelopment analysis (DEA). The results depict huge energy efficiency gap exists across four regions. The northern region is the best performer under group frontier than meta‐frontier DEA. South and west regions are relatively well‐performed under meta‐frontier than group frontier while the eastern region performs moderately well under both frontiers. The results show the significant energy efficiency improvement opportunities available across regions can be realised through technological advancement and energy management.

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“…Also, Suzuki [16], Jebali [17], Wang [18], and other scholars also researched the measurement of energy efficiency at the national level. By contrast, at the provincial or state level, Bhat et al [19] calculated the energy consumption efficiency and estimated energy saving potential for each Indian state. Ghiyasi [20] quantified the energy consumption efficiency for each Iranian province.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing the Economic-Environmental Efficiency of Energy Consumption and Spatial Patterns in China

Peng

Zhao

et al. 2019

Sustainability

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The improvement of energy consumption efficiency represents a significant task and a critical step toward sustainable energy transformations. This study uses a data envelopment analysis (DEA) and spatial autocorrelation method to conduct comprehensive measurement and assessment research on the economic-environmental efficiency of energy consumption in 31 Chinese provinces. It then carries out a synthetic study on energy consumption efficiency in the context of temporal and spatial dimensions, analyzes the characteristics and patterns related to temporal and spatial evolution, and systematically summarizes the temporal and spatial evolution processes associated with China’s economic-environmental efficiency in energy consumption. The results show that economic efficiency and environmental efficiency, both directly related to energy consumption, are positively correlated and display a parallel and synchronizing relationship. China’s energy consumption efficiency displays an upward trend in general, although differences exist between economic efficiency and environmental efficiency about the growth rate and overall development level. In other words, economic efficiency is generally higher than environmental efficiency. A positive spatial correlation occurs between economic and environmental efficiency in energy consumption across all the Chinese provinces studied. Furthermore, some cluster characteristic can be identified. Accurately, the eastern coastal area of China with a higher efficiency represents a spatial cluster of high values, whereas the midwestern inland area of China with a lower efficiency represents a spatial cluster of low values. Therefore, a descending pattern is displayed from the east to the west. As time goes by, the extent of clustering could become more prominent, accompanied by an increasing spatial cluster of high values and a decreasing spatial cluster of low values. Accordingly, China needs to improve its energy consumption efficiency further and promote sustainable energy transformations.

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Interstate energy efficiency of Indian paper industry: A slack-based non-parametric approach

Cited by 28 publications

References 60 publications

Direct and indirect impacts of high-tech industry development on CO2 emissions: empirical evidence from China

Direct and indirect impacts of high-tech industry development on CO2 emissions: empirical evidence from China

Reducing the energy consumption of Indian iron and steel industry through enhancing energy efficiency: Role of regional coordination

Assessing the Economic-Environmental Efficiency of Energy Consumption and Spatial Patterns in China

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