Energie : papiers de recherche moissonnés (5/01/2017)
Énergie et développement : dossier. Mondes en développement, n° 176 – 2016/4 http://www.cairn.info/revue-mondes-en-developpement-2016-4.htm
- Accès à l’énergie et lutte contre le changement climatique : opportunités et défis en Afrique subsaharienne / Arman Avadikyan, Claire Mainguy
- Consommation d’énergie et croissance économique en Afrique subsaharienne / Florian Grosset, Phu Nguyen-Van
- Action publique et politiques de diversification du mix énergétique vers les énergies renouvelables en Afrique de l’Ouest. Focus sur le cas des agrocarburants au Burkina Faso / Charly Djerma Gatete, et al.
- Les enjeux du développement de l’énergie solaire au Bénin. Quelques pistes de réflexion pour une approche territoriale / Christophe Beaurain, Mahugnon Bérenger Amoussou
- Projets d’accès à l’électricité : comment en mesurer les bénéfices / Clara Kayser-Bril, Pascal Augareils
The Response of Consumer Spending to Changes in Gasoline Prices / Michael Gelman, Yuriy Gorodnichenko, Shachar Kariv, Dmitri Koustas, Matthew D. Shapiro, Dan Silverman, Steven Tadelis. NBER, Dec. 2016, 42 p. (NBER Working Paper No. 22969) http://www.nber.org/papers/w22969 – draft : http://www-personal.umich.edu/~shapiro/papers/gasprices.pdf
This paper estimates how overall consumer spending responds to changes in gasoline prices. It uses the differential impact across consumers of the sudden, large drop in gasoline prices in 2014 for identification. This estimation strategy is implemented using comprehensive, daily transaction-level data for a large panel of individuals. The estimated marginal propensity to consume (MPC) is approximately one, a higher estimate than estimates found in less comprehensive or well-measured data. This estimate takes into account the elasticity of demand for gasoline and potential slow adjustment to changes in prices. The high MPC implies that changes in gasoline prices have large aggregate effects.
Improving Decision Making for Public R&D Investment in Energy: Utilizing Expert Elicitation in Parametric Models / Gabriel Chan and Laura Diaz Anadon. Energy Policy Research Group, 2016, 54 p. (EPRG Working Paper 1631) http://www.eprg.group.cam.ac.uk/wp-content/uploads/2017/01/1631-Text.pdf
Effective decision making to allocate public funds for energy technology research, development, and demonstration (R&D) requires considering alternative investment opportunities that can have large but highly uncertain returns and a multitude of positive or negative interactions. This paper proposes and implements a method to support R&D decisions that propagates uncertainty through an economic model to estimate the benefits of an R&D portfolio, accounting for innovation spillovers and technology substitution and complementarity. The proposed method improves on the existing literature by: (a) using estimates of the impact of R&D investments from one of the most comprehensive sets of expert elicitations on this topic to date; (b) using a detailed energy-economic model to estimate evaluation metrics relevant to an energy R&D portfolio: e.g., system benefits, technology diffusion, and uncertainty around outcomes; and (c) using a novel sampling and optimization strategy to calculate optimal R&D portfolios. This design is used to estimate an optimal energy R&D portfolio that maximizes the net economic benefits under an R&D budget constraint. Results parameterized based on expert elicitations conducted in 2009-2011 in the United States provide indicative results that show: (1) an expert-recommended portfolio in 2030, relative to the BAU portfolio, can reduce carbon dioxide emissions by 46 million tonnes, increase economic surplus by $29 billion, and increase renewable energy generation by 39 TWh; (2) uncertainty around the estimates of R&D benefits is large and overall uncertainty increases with greater investment levels; (3) a 10-fold expansion from 2012 levels in the annual R&D budget for utility-scale energy storage, bioenergy, advanced vehicles, fossil energy, nuclear energy, and solar photovoltaic technologies can be justified by returns to economic surplus; (4) the greatest returns to publicR&D investment are in energy storage and solar photovoltaics; and (5) the current allocation of energy R&D funds is very different from optimal portfolios. Taken together, these results demonstrate the utility of applying new methods to improve the cost-effectiveness and environmental performance in a deliberative approach to energy R&D portfolio decision making.
A Review of Factors Influencing the Cost Development of Electricity Generation Technologies / Sascha Samadi, Wuppertal Institute for Climate, Environment and Energy, Energies, vol. 9, n° 11, 2016 http://www.mdpi.com/1996-1073/9/11/970
This article reviews the literature on the past cost dynamics of various renewable, fossil fuel and nuclear electricity generation technologies. It identifies 10 different factors which have played key roles in influencing past cost developments according to the literature. These 10 factors are: deployment-induced learning, research, development and demonstration (RD&D)-induced learning, knowledge spillovers from other technologies, upsizing, economies of manufacturing scale, economies of project scale, changes in material and labour costs, changes in fuel costs, regulatory changes, and limits to the availability of suitable sites. The article summarises the relevant literature findings for each of these 10 factors and provides an overview indicating which factors have impacted on which generation technologies. The article also discusses the insights gained from the review for a better understanding of possible future cost developments of electricity generation technologies. Finally, future research needs, which may support a better understanding of past and future cost developments, are identified.