Does directed technological change get greener: Empirical evidence from Shanghai's industrial green development transformation. (October 2016)
- Record Type:
- Journal Article
- Title:
- Does directed technological change get greener: Empirical evidence from Shanghai's industrial green development transformation. (October 2016)
- Main Title:
- Does directed technological change get greener: Empirical evidence from Shanghai's industrial green development transformation
- Authors:
- Shao, Shuai
Luan, Ranran
Yang, Zhenbing
Li, Chengyu - Abstract:
- Highlights: We adopt the stochastic frontier analysis based on translog production function. We measure factor output elasticity and green total factor productivity growth rate. We investigate the degrees of technological change biased to production factors. Shanghai's industrial technological change biases to energy use and capital saving. Shanghai's industrial green development transformation needs to be further advanced. Abstract: The degree of technological change biased to the environmental factor is crucial to industrial sustainable development. Using the stochastic frontier analysis method based on the translog production function and the panel data of 32 industrial sub-sectors in Shanghai over 1994–2011, this paper combines the evolution dynamic of the frontier technological structure with the evolution dynamic of technological change direction to estimate the output elasticities of production factors and the growth rate of green total factor productivity. Also, we investigate and compare the degrees of technological change biased to four production factors, i.e., capital, labor, energy, and carbon emissions. The results show that the industrial green total factor productivity in Shanghai presents an overall upward trend and mainly depends on the technical efficiency change. The improvements of labor productivity, R&D intensity, and energy efficiency can effectively enhance the green technical efficiency, while capital deepening has a mitigation effect on the greenHighlights: We adopt the stochastic frontier analysis based on translog production function. We measure factor output elasticity and green total factor productivity growth rate. We investigate the degrees of technological change biased to production factors. Shanghai's industrial technological change biases to energy use and capital saving. Shanghai's industrial green development transformation needs to be further advanced. Abstract: The degree of technological change biased to the environmental factor is crucial to industrial sustainable development. Using the stochastic frontier analysis method based on the translog production function and the panel data of 32 industrial sub-sectors in Shanghai over 1994–2011, this paper combines the evolution dynamic of the frontier technological structure with the evolution dynamic of technological change direction to estimate the output elasticities of production factors and the growth rate of green total factor productivity. Also, we investigate and compare the degrees of technological change biased to four production factors, i.e., capital, labor, energy, and carbon emissions. The results show that the industrial green total factor productivity in Shanghai presents an overall upward trend and mainly depends on the technical efficiency change. The improvements of labor productivity, R&D intensity, and energy efficiency can effectively enhance the green technical efficiency, while capital deepening has a mitigation effect on the green technical efficiency. The technological change of Shanghai's industrial production biases to energy use and capital saving, causing a high energy demand of industrial development. Under the dual impacts of economic development and energy-saving and emission-reduction policies, the degree of technological change biased to the environmental factor (carbon emissions) displays strong and weak alternations, indicating that the green bias of industrial technological change in Shanghai is not stable and that the green transformation of industrial development model needs to be further advanced. … (more)
- Is Part Of:
- Ecological indicators. Volume 69(2016)
- Journal:
- Ecological indicators
- Issue:
- Volume 69(2016)
- Issue Display:
- Volume 69, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 69
- Issue:
- 2016
- Issue Sort Value:
- 2016-0069-2016-0000
- Page Start:
- 758
- Page End:
- 770
- Publication Date:
- 2016-10
- Subjects:
- Directed technological change -- Output elasticity of production factors -- Green total factor productivity growth -- Green development transformation -- Stochastic frontier analysis
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2016.04.050 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3648.877200
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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