Poverty mitigation via solar panel adoption: Smart contracts and targeted subsidy design

An emerging application of FinTech in the commodities market pivots on a blockchain-enabled Peer-to-Peer energy exchange platform, wherein solar energy feed-in tariffs are self-executed via “smart contracts”. With subsidy design versus mechanism design models, this paper evaluates the instrumental value of smart contracts towards poverty mitigation in developing economies via securing sustainable revenue for rural households. We investigate how the adoption levels of solar panels interact with adoption barriers and household energy behaviors. Smart contracts can be applied for self-executing the green energy financing and subsidy distribution process. For the government-led subsidy design scheme, we propose Cournot quantity competition models that incorporate spatial heterogeneity (energy-poor and energy-rich regions) and uncertainty in energy generation costs. We find that the government's aggregate subsidy expenditure decreases in solar uncertainty, and it is optimal to select households from a single region only for high uncertainty. Smart contracts facilitate heterogeneity and uncertainty to soften quantity competition, benefitting households in both regions and the government. For the mechanism design scheme, we demonstrate that both regions can be chosen only under the incomplete information case with inaccurate forecasts about market conditions and a relatively low baseline energy price. The self-executing feature of smart contracts helps mitigate the potential risks of renegotiation between multiple parties. Moreover, a public policy supported by mechanism design is more likely to outperform that based on market competition regarding cost-effectiveness only when the latter chooses a single region. Otherwise, quantity competition would be significantly softened by contingency-dependent smart contracts under heterogeneous market conditions.