A public emission reduction project offers saleable carbon credits to encourage individual residents to participate in activities with low carbon emissions: if the residents participate, they will earn carbon credits that can be sold to polluting firms for carbon offsetting. This study explores the economic and environmental implications of these projects.
The authors develop a multiperiod model to incorporate the decisions of individual residents and a polluting firm. The model captures residents' difference in estimating the price of carbon credits: A proportion of residents are naive residents who shortsightedly take the previous market price of carbon credits as the basis of their decision-making.
A public emission reduction project can improve the cost-efficiency of carbon reduction, increase both the profit of the polluting firm and consumer surplus, but may hurt the welfare of the participating residents. Reducing transaction costs of carbon credits may cause a greater loss to participating residents. As the ratio of naive residents decreases, the overall welfare of participating residents increases and the number of participating residents decreases.
To encourage more residents to reduce carbon emissions, the project should be promoted to new areas (e.g. rural areas) where there are more naive residents. Although reducing transaction costs is an effective way to increase the economic viability of the project, the government should pay attention to protecting the welfare of residents, and educating residents is an effective way to improve their overall welfare.
This paper is the first to reveal the economic and environmental implications of public emission reduction projects.
This paper is supported by the Key Program of National Social Science Foundation of China (Grant No. 20AJY008). The authors contributed equally to the paper and author names are in alphabetical order.
Han, J., Kong, L., Wang, W. and Xie, J. (2022), "Motivating individual carbon reduction with saleable carbon credits: policy implications for public emission reduction projects", Industrial Management & Data Systems, Vol. 122 No. 5, pp. 1268-1305. https://doi.org/10.1108/IMDS-12-2021-0764
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