Synthesis report of SIMPATIC micro-econometric research on clean innovation and the impact of climate policy

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An essential margin for the reduction of greenhouse gas (GHG) emissions is the development of new emission reducing technologies and processes. It is well established that market forces alone are unlikely to provide optimal levels of R&D towards this kind of innovation, because of the combination of both positive knowledge externalities and negative environmental externalities.

Policies that primarily target the environmental externality such as carbon emissions pricing – through carbon taxing or a trading system – might not only reduce GHG emissions. By putting a price on carbon, they could also provide incentives for companies to direct R&D to clean areas. Direct empirical evidence on the underlying mechanisms is very limited. There are a few studies showing a link between energy prices and clean innovation. However these rely on aggregate data or are very specific in terms of geographic range or the sector of the economy considered. Consequently, providing empirically robust evidence on this issue is a major objective of our work. Importantly, the impact of climate policy on innovation is a first order issue to adequately model policy scenarios in integrated assessment model and similar macro models.

Because of the presence of knowledge externalities, even a global carbon price could lead to a sub-optimal innovation level in clean technologies. Policies that directly target the knowledge externality are needed. But how strong must these policies be? The answer to this question crucially depends on the degree of knowledge spillovers in clean technologies compared to other (in particular dirty) technology areas. There is a striking lack of evidence on this issue, and another objective of our current work is to provide accurate measures of knowledge spillovers in clean technologies that can be used to inform policies and be fed into macro-models.

We are currently making progress along all of these lines. In the following section we summarise current results. We try to as much as possible translate our results into simple elasticities that can easily be integrated into a macro-modelling framework. We also give a short preview on on-going work and the kind of results we expect to uncover in the coming months.