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Evidence On The Future Prospects Of Indian Thermal Power Sector In The Perspective Of Depleting Coal Reserve

Author

Listed:
  • Sukanya Ghosh
  • P.P. Sengupta
  • Biman Maity

Abstract

Increasing industrial growth throughout the world largely depends on availability of electricity. The overall situation in the power sector provides an optimistic view. However, insight into the thermal power industry provides a bleak picture. Thermal power stations mostly depend upon coal as a basic raw material. Economists project that India has a little over 250 billion metric tons of coal reserve to sustain continued and progressive demand for thermal power generation in the next 40-50 years. Indian thermal stations have started importing expensive coal from other countries to maintain generation and supply. Every thermal power station emits CO2. Suspended Particulate Matter (SPM), fly ash and effluents create health hazards and contribute to global warming. This paper develops a model based on Auto Regressive Integrated Moving Average (ARIMA) to depict the future prospects of coal based thermal power sector of India. The evidence shows that India needs to identify alternative sources of power generation to grow without damaging world and maintaining sustainability.

Suggested Citation

  • Sukanya Ghosh & P.P. Sengupta & Biman Maity, 2012. "Evidence On The Future Prospects Of Indian Thermal Power Sector In The Perspective Of Depleting Coal Reserve," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 6(1), pages 77-89.
    • Handle: RePEc:ibf:gjbres:v:6:y:2012:i:1:p:77-89
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    References listed on IDEAS

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    More about this item

    Keywords

    Insight; CO2; SPM; Fly ash; Global warming; ARIMA Model; Sustainability;
    All these keywords.

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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