We conduct a systematic, interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions). Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (1) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers - general energy prices, carbon prices, and targeted interventions that build markets. (2) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (3) Overall Innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modeling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research.
Energy system optimization models (ESOMs) such as MARKAL/TIMES are used to support energy policy analysis worldwide. ESOMs cover the full life-cycle of fuels from extraction to end-use, including the associated direct emissions. Nevertheless, the life-cycle emissions of energy equipment and infrastructure are not modelled explicitly. This prevents analysis of questions relating to the relative importance of emissions associated with the build-up of infrastructure and other equipment required for decarbonization.
Replacing traditional technologies by renewables can lead to an increase of emissions during early diffusion stages if the emissions avoided during the use phase are exceeded by those associated with the deployment of new units. Based on historical developments and on counterfactual scenarios in which we assume that selected renewable technologies did not diffuse, we conclude that onshore and offshore wind energy have had a positive contribution to climate change mitigation since the beginning of their diffusion in EU27. In contrast, photovoltaic panels did not pay off from an environmental standpoint until very recently, since the benefits expected at the individual plant level were offset until 2013 by the CO2 emissions related to the construction and deployment of the next generation of panels. Considering the varied energy mixes and penetration rates of renewable energies in different areas, several countries can experience similar time gaps between the installation of the first renewable power plants and the moment in which the emissions from their infrastructure are offset.
The analysis demonstrates that the time-profile of renewable energy emissions can be relevant for target-setting and detailed policy design, particularly when renewable energy strategies are pursued in concert with carbon pricing through cap-and-trade systems.