A Statement on the Appropriate Role for Research and Development in Climate Policy

This statement is issued by a group of economists and scientists which met at Stanford University on October 18, 2008 to discuss the role of research and development (R&D) in developing effective policies for addressing the adverse potential consequences of climate change. We believe that climate change is a serious issue that governments need to address. We also believe that research and development needs to be a central part of governments’ strategies for responding to this challenge. Solutions to manage long-term risks will require the development and global deployment of a range of technologies for energy supply and end-use, land-use, agriculture and adaptation that are not currently commercial. A key potential benefit of focused scientific and technological research and development investment is that it could dramatically reduce the cost of restricting greenhouse gas emissions by encouraging the development of more affordable, better performing technologies.

Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58030/1/20271_ftp.pd

Up-scaling, formative phases, and learning in the historical diffusion of energy technologies

The 20th century has witnessed wholesale transformation in the energy system marked by the pervasive diffusion of both energy supply and end-use technologies. Just as whole industries have grown, so too have unit sizes or capacities. Analysed in combination, these unit level and industry level growth patterns reveal some consistencies across very different energy technologies. First, the up-scaling or increase in unit size of an energy technology comes after an often prolonged period of experimentation with many smaller-scale units. Second, the peak growth phase of an industry can lag these increases in unit size by up to 20 years. Third, the rate and timing of up-scaling at the unit level is subject to countervailing influences of scale economies and heterogeneous market demand. These observed patterns have important implications for experience curve analyses based on time series data covering the up-scaling phases of energy technologies, as these are likely to conflate industry level learning effects with unit level scale effects. The historical diffusion of energy technologies also suggests that low carbon technology policies pushing for significant jumps in unit size before a ‘formative phase’ of experimentation with smaller-scale units are risky

Archimedean copulas derived from utility functions

The inverse of the (additive) generator of an Archimedean copula is a strictly decreasing and convex function, while utility functions (applying to risk averse decision makers) are nondecreasing and concave. This provides a basis for deriving an inverse generator of an Archimedean copula from a utility function. If we derive the inverse of the generator from the utility function, there is a link between the magnitude of measures of risk attitude (like the very common Arrow-Pratt coefficient of absolute risk aversion) and the strength of dependence featured by the corresponding Archimedean copula. Some new copula families are derived, and their properties are discussed. A numerical example about modelling dependence of coupled lives is included

Observatories of the Solar Corona and Active Regions (OSCAR)

Coronal Mass Ejections (CMEs) and Corotating Interaction Regions (CIRs) are major sources of magnetic storms on Earth and are therefore considered to be the most dangerous space weather events. The Observatories of Solar Corona and Active Regions (OSCAR) mission is designed to identify the 3D structure of coronal loops and to study the trigger mechanisms of CMEs in solar Active Regions (ARs) as well as their evolution and propagation processes in the inner heliosphere. It also aims to provide monitoring and forecasting of geo- effective CMEs and CIRs. OSCAR would contribute to significant advancements in the field of solar physics, improvements of the current CME prediction models, and provide data for reliable space weather forecasting. These objectives are achieved by utilising two spacecraft with identical instrumentation, located at a heliocentric orbital distance of 1 AU from the Sun. The spacecraft will be separated by an angle of 68° to provide optimum stereoscopic view of the solar corona. We study the feasibility of such a mission and propose a preliminary design for OSCAR

A Multi-Country Trade and Tourism with Endogenous Capital and Knowledge

Background: The study models a dynamic interaction among economic growth, structural change, knowledge accumulation, international trade and tourist flows. Objective: The purpose of this study is to introduce endogenous knowledge into a multi-country growth model with trade and tourism proposed by Zhang. The study models a dynamic interaction among economic growth, structural change, knowledge accumulation, international trade and tourist flows. Methods/Approach: The model is based on Arrow’s learning by doing, the Solow one-sector growth model, the Oniki-Uzawa neoclassical trade model, and the Uzawa two-sector growth model. We first build the multi-country neoclassical growth model of endogenous knowledge with international tourism. Then we show that we can follow the motion of the -country world economy with differential equations. Results: We simulate the motion of the three-country global economy. We carry out a comparative dynamic analysis by simulation with regard to the knowledge utilization efficiency, the efficiency of learning by doing, the propensity to save, the propensity to tour other countries, and the population. Conclusions: The global economy has a unique equilibrium

"A convenient truth": air travel passengers' willingness to pay to offset their CO2 emissions

Several economic reviews demonstrate the substantial costs related to climate change and consequently call for early action. These reviews, however, have been limited to measuring ‘objective’ risks and expected material damage related to climate change. The ‘subjective’ perceived risk of climate change and society’s willingness to pay (WTP) to avoid these risks are expected to provide an important additional motivation for direct action. We investigate whether and why air travel passengers—an increasingly important source of greenhouse gas emissions—are supportive of measures that increase the cost of their travel based on the polluter pays principle and compensate the damage caused by their flight. Compared to the results of the few previous studies that have elicited WTP estimates for climate policy more generally, our results appear to be at the lower end of the scale, while a comparison to estimates of the social cost of carbon shows that the average WTP estimate in this study is close to the estimated marginal damage cost. Although significant differences are found between travellers from Europe, North America, Asia and the rest of the world, we show that there exists a substantial demand for climate change mitigation action. The positive risk premium over and above the expected property damage cost assessments should be accounted for more explicitly in economic reviews as it will add to the burden of proof of direct action. Measurements of passenger WTP will help policy makers to design effective financial instruments aimed at discouraging climate-unfriendly travel activities as well as to generate funds for the measures directed at climate change mitigation and adaptation. Based on stated WTP by travellers to offset their greenhouse gas emissions, funds in the order of magnitude of €23 billion could be generated annually to finance climate change mitigation activities

Preference elicitation techniques for group recommender systems

A key issue in group recommendation is how to combine the individual preferences of different users that form a group and elicit a profile that accurately reflects the tastes of all members in the group. Most Group Recommender Systems (GRSs) make use of some sort of method for aggregating the preference models of individual users to elicit a recommendation that is satisfactory for the whole group. In general, most GRSs offer good results, but each of them have only been tested in one application domain. This paper describes a domain-independent GRS that has been used in two different application domains. In order to create the group preference model, we select two techniques that are widely used in other GRSs and we compare them with two novel techniques. Our aim is to come up with a model that weighs the preferences of all the individuals to the same extent in such a way that no member in the group is particularly satisfied or dissatisfied with the final recommendations. © 2011 Elsevier Inc. All rights reserved.Partial support provided by Consolider Ingenio 2010 CSD2007-00022, Spanish Government Project MICINN TIN2008-6701-C03-01 and Valencian Government Project Prometeo 2008/051. FPU grant reference AP2009-1896 awarded to Sergio Pajares-Ferrando.García García, I.; Pajares Ferrando, S.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2012). Preference elicitation techniques for group recommender systems. Information Sciences. 189:155-175. https://doi.org/10.1016/j.ins.2011.11.037S15517518

An introduction to continuous optimization for imaging

International audienceA large number of imaging problems reduce to the optimization of a cost function , with typical structural properties. The aim of this paper is to describe the state of the art in continuous optimization methods for such problems, and present the most successful approaches and their interconnections. We place particular emphasis on optimal first-order schemes that can deal with typical non-smooth and large-scale objective functions used in imaging problems. We illustrate and compare the different algorithms using classical non-smooth problems in imaging, such as denoising and deblurring. Moreover, we present applications of the algorithms to more advanced problems, such as magnetic resonance imaging, multilabel image segmentation, optical flow estimation, stereo matching, and classification