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Carbon-sensitive Meta-Productivity Growth and Technological Gap: An Empirical Analysis of Indian Thermal Power Sector

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  • Surender Kumar

    (Department of Economics, Delhi School of Economics)

  • Rakesh Kumar Jain

    (Indian Railways, Government of India & Department of Business Economics, South Campus, University of Delhi)

Abstract

This paper measures carbon-sensitive efficiency and productivity growth in technologically heterogeneous coal-fired thermal power plants in India for the period of 2000 to 2013. It uses a unique data set of 56 plants, obtained petitioning the Right to Information Act 2005. We apply ‘within-MLE’ fixed effects stochastic frontier model to get consistent estimates of meta-directional output distance function. The thermal power plants are grouped in two categories: central sector and state sector. We find that the state sector plants have higher potential to simultaneously increase electricity generation and reduce carbon emission than the central sector plants. If all the state and central sectors plants were made to operate on the meta-frontier, reduction of 98 million tonnes of CO2 could have been achieved. Carbon-sensitive productivity growth in the central sector plants is higher than the plants in state sector, though in both the sectors productivity growth is governed by carbon-sensitive innovation effect. Commercialisation or autonomy in electricity generation also induces carbon-sensitive productivity growth and reduces carbon-sensitive productivity growth gap.

Suggested Citation

  • Surender Kumar & Rakesh Kumar Jain, 2019. "Carbon-sensitive Meta-Productivity Growth and Technological Gap: An Empirical Analysis of Indian Thermal Power Sector," Working papers 297, Centre for Development Economics, Delhi School of Economics.
  • Handle: RePEc:cde:cdewps:297
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    References listed on IDEAS

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    Keywords

    Carbon-sensitive productivity; Luenberger productivity indicator; Stochastic meta-frontier; Indian thermal power plants;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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