The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project

By Köhler Jonathan, Michael Grubb, David Popp, Ottmar Edenhofer. 2006

174 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9e57cc4c374d2ac9509facaa3ce23952a3e2cae2

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In Economics and Econometrics

Citations in the corpus

The experience curve theory and its application in the field of electricity generation technologies – A literature review (2018, background): “A number of reviews of experience curve literature have previously been published, covering both electricity generation technologies in general [4,12,13] and individual technologies, such as wind [14–16] and solar PV [17].”
Accuracy of progress ratios determined from experience curves: the case of crystalline silicon photovoltaic module technology development (2008, background): “In many climate-economy models the lack of uncertainty analysis is considered to be an important deficiency and incorporation of uncertainties into such models is viewed as a major challenge.(12) As an example, why consideration of uncertainty is important we can consider PV implementation scenarios”
Induced Technological Change: Exploring its Implications for the Economics of Atmospheric Stabilization: Synthesis Report from the innovation Modeling Comparison Project (2006, background): “Examples of the papers which compare these models in a qualitative way are Sijm (2004), Clarke and Weyant (2002), Löschel (2002), Weyant and Olavson (1999), Grubb, Köhler and Anderson (2002), and Köhler et al. (2006), the latter includes an up to date survey of ETC in the literature.”
Innovation and Climate Policy (2010, background): “3 For recent reviews of the growing literature on the macroeconmic effects of endogenous technological change for climate policy, see Köhler et al (2006) and Gillingham et al. (2008).”
Energy, the Environment, and Technological Change (2009, background): “7 Köhler et al. (2006) includes a review of these studies.”
Issues related to mitigation in the long-term context (2007, background): “• Technological patterns in sectors such as energy, transportation, building, waste, agriculture and forestry – the treatment of technology in economic models has received considerable attention and triggered the most difficult debates within the scientific community working in this field (Edmonds a”
Relating R&D and Investment Policies to CCS Market Diffusion Through Two-Factor Learning (2013, background): “In the electricity supply industry, we observe a large range between about 2% for hydropower or supercritical coal plants and up to about 30% for wind and solar power plants (McDonald and Schrattenholzer, 2001; Köhler et al., 2006; Junginger et al, 2010).”
Feed-In Tariffs for Photovoltaics: Learning by Doing in Germany (2011, unknown): “Hence, Köhler et al. (2006) point out that floor costs are often specified for learning curves, which act as a lower bound on costs when technologies mature.”
Impact of Trade Openness and Human Capital on Economic Growth: A Comparative Investigation of Asian Countries (2020, background): “This theory is also concentrated on the positive and spillover effects of knowledge, which ultimately lead an economy towards development [21].”