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Mandates, which establish minimum use quotas for certain goods, are becoming increasingly popular policy tools to promote renewable energy use. In addition to mitigating the pollution externality of conventional energy, clean energy mandates have the goal of promoting research and development (R&D) investments in renewable energy technology. But how well do mandates perform as innovation incentives? To address this question, we develop a partial equilibrium model to examine the R&D incentives induced by a mandate, and compare this policy to two benchmark situations: laissez faire and a carbon tax. Innovation is stochastic and the model permits an endogenous number of multiple innovators. We present both analytical results and conclusions based on numerical simulations. We find that the optimal mandate is larger than it would be without the prospect of innovation, that neglecting the outlook for innovation significantly reduces welfare, and that the optimal mandate is more sensitive to assumptions about the innovation process than an optimal carbon tax. Furthermore, we find that mandates create relatively strong incentives for R&D investment in low‐quality innovations, but relatively weak incentives to invest in high‐quality innovations. We also rank policies by expected welfare. An optimal carbon tax has higher expected welfare than an optimal mandate, and both have higher expected welfare than laissez faire. Moreover, in our endogenous innovation setting, a stronger result obtains: a simple carbon tax equal to the damage from pollution (unadjusted for the prospect of innovation) has higher expected welfare than an optimal mandate.
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Clancy et al. (2017) studied this question.
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