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Uncertainty in Estimates, Incentives, and Emission Reductions in REDD+ Projects

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  • Jichuan Sheng

    (Institute of Climate Change and Public Policy, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, Jiangsu, China
    Business School, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, Jiangsu, China)

  • Weihai Zhou

    (Business School, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, Jiangsu, China)

  • Alex De Sherbinin

    (Center for International Earth Science Information Network (CIESIN), The Earth Institute at Columbia University, P.O. Box 1000, Palisades, NY 10964, USA)

Abstract

The accurate monitoring and measurement of emission reductions is a critical step in Reducing Emissions from Deforestation and Degradation (REDD+). However, the existence of uncertainty in emission reduction estimates affects the performance of REDD+ projects. We assert that incentive could be a valuable policy tool for reducing monitoring errors and transaction costs. Using Stackelberg models and simulation research, this paper examines the effects of uncertainty and incentive on performance and stakeholder benefits of REDD+ projects. Finally, the uncertainties in REDD+ projects are further discussed, and equilibrium errors, emission reductions, and stakeholder benefits in different scenarios are compared. The results show that errors do affect the measured value of carbon emissions and compensation payments. However, incentive for investors can reduce monitoring errors and improve the performance of REDD+ projects. Therefore, in the future, incentive should be provided to investors rather than landholders.

Suggested Citation

  • Jichuan Sheng & Weihai Zhou & Alex De Sherbinin, 2018. "Uncertainty in Estimates, Incentives, and Emission Reductions in REDD+ Projects," IJERPH, MDPI, vol. 15(7), pages 1-21, July.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1544-:d:159204
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