The Experts below are selected from a list of 148347 Experts worldwide ranked by ideXlab platform

Jane Golley - One of the best experts on this subject based on the ideXlab platform.

  • green productivity growth in china s Industrial Economy
    Energy Economics, 2014
    Co-Authors: Shiyi Chen, Jane Golley
    Abstract:

    This paper uses a Directional Distance Function (DDF) and the Malmquist–Luenberger Productivity Index to estimate the changing patterns of ‘green’ total factor productivity (GTFP) growth of 38 Chinese Industrial sectors during the period 1980–2010. Unlike the measures of traditional total factor productivity (TFP) growth, the DDF incorporates carbon dioxide emissions as an undesirable output directly into the production technology, which credit sectors for simultaneously reducing their emissions and increasing their output. Our estimates of aggregate and sector-level GTFP growth reveal that Chinese industry is not yet on the path towards sustainable, low-carbon growth. A dynamic panel data analysis of the determinants of GTFP across sectors is used to identify factors that might rectify this situation, including state owned enterprise (SOE) reform, the growth of small private enterprises, continued openness to foreign investment and higher spending on R&D, particularly in emission-intensive sectors.

Ye Huai-zhen - One of the best experts on this subject based on the ideXlab platform.

  • Grey Control System of Regional Logistics Capability and Industrial Economy
    Journal of Wuhan University of Technology, 2009
    Co-Authors: Ye Huai-zhen
    Abstract:

    To find an effective way that consumes less logistics resources while develops the regional Economy fast,we broke the relationship of regional Economy and regional logistics capability(RLC) down into the relationship of regional Industrial Economy and key elements of RLC.Choosing three key elements of RLC as control variables,a grey control system of RLC and Industrial Economy is built;then chose Jiangsu province as a sample,obtained the calculation results of control model.The research shows that calculation method of model is simple,and the results are scientific,reasonable and practical.

  • Control Model of Regional Logistics Capability and Industrial Economy Based on Grey System
    2008 International Conference on Intelligent Computation Technology and Automation (ICICTA), 2008
    Co-Authors: Zhou Tai, Ye Huai-zhen
    Abstract:

    To effectively understand the impetus function of improving regional logistics capability in promoting regional economic growth and optimizing the Industrial structure, the authors established a control model of regional logistics capability and Industrial Economy. First of all, the authors analyzed comprehensively the elements of regional logistics capability, and based on this chose three key elements as control variables; then by using the principle and method of grey system theory, the authors built a grey control system of regional logistics capability and Industrial Economy; finally, choosing Sichuan province of China as a regional sample, the authors calculated the actual parameter values of the model according to the raw data of Sichuan province from 1999 to 2005 and analyzed the calculated result. The case study indicates that the model can reflect the characteristics of the relation between regional logistics capability and Industrial Economy perfectly, and the result is reasonable and scientific.

Yu-rui Huang - One of the best experts on this subject based on the ideXlab platform.

  • Does OFDI Promote Green Growth of China's Industrial Economy?—from the Perspective of Provincial Panel Data
    DEStech Transactions on Social Science Education and Human Science, 2019
    Co-Authors: Hui Fang, Yu-rui Huang
    Abstract:

    Based on the theory of OFDI and the extended Cobb-Douglas production function, this paper uses provincial panel data to study the mechanism and promoting effect of OFDI on the green growth of local Industrial Economy. The research finds that although provincial OFDI can indirectly and directly promote the green growth of local Industrial Economy through various investment effects, its comprehensive promotion effect is negative in the current period; OFDI can strengthen the green growth of local Industrial Economy through environmental regulation, while OFDI can restrain the green growth of local Industrial Economy through consumption level of Residents. When environmental protection regulations and residents' consumption level are added, OFDI has a significant promoting effect on the green growth of local Economy in industry. Finally, on the basis of the conclusions of the study, the corresponding policy recommendations are put forward.

  • Does OFDI Promote Green Growth of China's Industrial Economy?—from the Perspective of Provincial Panel Data Hui FANG
    DEStech Transactions on Social Science Education and Human Science, 2019
    Co-Authors: Hui Fang, Yu-rui Huang
    Abstract:

    Based on the theory of OFDI and the extended Cobb-Douglas production function, this paper uses provincial panel data to study the mechanism and promoting effect of OFDI on the green growth of local Industrial Economy. The research finds that although provincial OFDI can indirectly and directly promote the green growth of local Industrial Economy through various investment effects, its comprehensive promotion effect is negative in the current period; OFDI can strengthen the green growth of local Industrial Economy through environmental regulation, while OFDI can restrain the green growth of local Industrial Economy through consumption level of Residents. When environmental protection regulations and residents' consumption level are added, OFDI has a significant promoting effect on the green growth of local Economy in industry. Finally, on the basis of the conclusions of the study, the corresponding policy recommendations are put forward.

Shiyi Chen - One of the best experts on this subject based on the ideXlab platform.

  • green productivity growth in china s Industrial Economy
    Energy Economics, 2014
    Co-Authors: Shiyi Chen, Jane Golley
    Abstract:

    This paper uses a Directional Distance Function (DDF) and the Malmquist–Luenberger Productivity Index to estimate the changing patterns of ‘green’ total factor productivity (GTFP) growth of 38 Chinese Industrial sectors during the period 1980–2010. Unlike the measures of traditional total factor productivity (TFP) growth, the DDF incorporates carbon dioxide emissions as an undesirable output directly into the production technology, which credit sectors for simultaneously reducing their emissions and increasing their output. Our estimates of aggregate and sector-level GTFP growth reveal that Chinese industry is not yet on the path towards sustainable, low-carbon growth. A dynamic panel data analysis of the determinants of GTFP across sectors is used to identify factors that might rectify this situation, including state owned enterprise (SOE) reform, the growth of small private enterprises, continued openness to foreign investment and higher spending on R&D, particularly in emission-intensive sectors.

Yawen Sun - One of the best experts on this subject based on the ideXlab platform.

  • green total factor productivity growth and its determinants in china s Industrial Economy
    Sustainability, 2018
    Co-Authors: Chaofan Chen, Qingxin Lan, Ming Gao, Yawen Sun
    Abstract:

    This paper employs directional distance function (DDF) and the global Malmquist–Luenberger (GML) productivity index to measure the green total factor productivity (GTFP) growth of China’s 36 Industrial sectors from 2000 to 2014. Based on this, this paper ascertains the determinants of GTFP from the perspectives of institution, technology, and structure, and the determinant factors that affect GTFP are empirically tested by a dynamic panel data (DPD) model. The research shows that, considering energy consumption and environmental undesirable outputs, the Industrial GTFP goes backwards by 0.02% per year on average, and the contributions of GTFP to output growth are far from the target value of 50% in all Industrial sectors, which indicates that the growth of Industrial Economy sacrifices resources and environment to a certain degree. In terms of the determinant factors of GTFP, environmental regulation does improve the GTFP, while environmental regulation is difficult to promote GTFP by the route of technological innovation. Compared with technology importation, the driving effect of independent research and development on GTFP is obvious, especially promoting the GTFP of moderately and lightly polluting industries, while the driving effect in heavily polluting industries is poor. Endowment structure and property right structure play a positive role in improving GTFP, but the impacts of capital structure and energy structure on GTFP are poor.