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Measurement of Environmentally Sensitive Productivity Growth in Korean Industries

Author

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  • Chung, Yeimin

    (Korea University)

  • Heshmati, Almas

    (Jönköping University)

Abstract

This study measures productivity growth using the Metafrontier Malmquist-Luenberger productivity growth index (MML index) method and decomposes the index. The results are compared with those obtained from the conventional Malmquist-Luenberger (ML) productivity growth index. MML has two advantages compared with the ML index. The former is able to consider undesirable output as a by-product of production which accounts for producer group heterogeneities. As a result, it enables separation and estimation of changes in the technological gap between regional and global frontier technologies. The proposed index is employed to measure productivity growth and decompose its components in 14 Korean industrial sectors during the period between 1981 and 2007. For the purpose of detailed analysis of policy effects, the study period was divided into three decades. The results show that technology innovation can be regarded as a more important factor of productivity growth, rather than efficiency change. The chemical and Petrochemical, Machinery and Transport equipment industries are treated as global innovators in the whole period. However, the result differs according to decades. It is found that the groups with higher energy efficient technology and profitability obtain a higher productivity growth rate in comparison with their low energy efficient technology industry counterparts. Policy implications of the empirical results are discussed.

Suggested Citation

  • Chung, Yeimin & Heshmati, Almas, 2013. "Measurement of Environmentally Sensitive Productivity Growth in Korean Industries," IZA Discussion Papers 7235, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp7235
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    Cited by:

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    3. Wenwen Li & Wenping Wang & Yu Wang & Yingbo Qin, 2017. "Industrial structure, technological progress and CO2 emissions in China: Analysis based on the STIRPAT framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1545-1564, September.
    4. Li, Ke & Lin, Boqiang, 2015. "Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China," Energy Economics, Elsevier, vol. 48(C), pages 230-241.
    5. Qing Yang & Xingzi Wan & Huimin Ma, 2015. "Assessing Green Development Efficiency of Municipalities and Provinces in China Integrating Models of Super-Efficiency DEA and Malmquist Index," Sustainability, MDPI, vol. 7(4), pages 1-19, April.
    6. Wei, Yigang & Li, Yan & Wu, Meiyu & Li, Yingbo, 2019. "The decomposition of total-factor CO2 emission efficiency of 97 contracting countries in Paris Agreement," Energy Economics, Elsevier, vol. 78(C), pages 365-378.
    7. Chaofan Chen & Qingxin Lan & Ming Gao & Yawen Sun, 2018. "Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy," Sustainability, MDPI, vol. 10(4), pages 1-25, April.
    8. Lizhan Cao & Zhongying Qi & Junxia Ren, 2017. "China’s Industrial Total-Factor Energy Productivity Growth at Sub-Industry Level: A Two-Step Stochastic Metafrontier Malmquist Index Approach," Sustainability, MDPI, vol. 9(8), pages 1-22, August.
    9. Lin, Boqiang & Xu, Mengmeng, 2018. "Regional differences on CO2 emission efficiency in metallurgical industry of China," Energy Policy, Elsevier, vol. 120(C), pages 302-311.
    10. Sinwoo Lee & Dong-Woon Noh & Dong-hyun Oh, 2018. "Characterizing the Difference between Indirect and Direct CO 2 Emissions: Evidence from Korean Manufacturing Industries, 2004–2010," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    11. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.

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    More about this item

    Keywords

    Malmquist-Luenberger productivity (ML) index; DEA; undesirable output; CO2 emission; Metafrontier Malmquist-Luenberger productivity (MML) index; productivity change;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth

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