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Attracting Private Investment to Renewable Energy Projects in India

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  • Zhang, Ming
  • Guo, Manfeng

Abstract

Attracting private investments to renewable energy projects is a topic of significant debate within academic circles. This study investigates the relationship between green fiscal policy and green monetary policy concerning investments in renewable energy in India, spanning from 1990 to 2021, employing the ARDL (Autoregressive Distributed Lag) technique. The findings reveal that green taxes can positively or negatively impact investments in renewable energy sources. Furthermore, green monetary policy, mainly through the provision of green loans, accelerates investment inflows into renewable energy sources in the short and long terms. Challenges hindering private investment in India's renewable energy sector include compounded risk and inflation. Nonetheless, financial development and literacy rates are crucial in expanding investment in renewable energy sources. Based on these findings, practical policy recommendations for India entail enhancing sustainable literacy through green education, promoting social inclusivity, and establishing effective monetary and fiscal policies.

Suggested Citation

  • Zhang, Ming & Guo, Manfeng, 2024. "Attracting Private Investment to Renewable Energy Projects in India," Utilities Policy, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:juipol:v:90:y:2024:i:c:s0957178724001097
    DOI: 10.1016/j.jup.2024.101816
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    More about this item

    Keywords

    Investment; Energy resources; Sustainability; Green loans; Green tax; India;
    All these keywords.

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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