Energy market projections and differentiated carbon abatement in the European Union

We analyze the economic effects of the differentiated targets for carbon abatement in six European Union member states. Our recursively-dynamic model includes a detailed representation of trade and energy consumption and incorporates optimistic projections for future energy markets provided by the European Commission as the Business-as-Usual scenario. In the base case we find that the EU implementation of the Kyoto Protocol implies low overall costs and a relatively even cost distribution across member states. We also show that a less optimistic development in energy efficiency implies higher costs in all countries, especially in those with high abatement costs. Finally, we find that uniform abatement targets increase overall costs marginally but changes the cost distribution significantly, holding total EU emissions constant. --

Effects of Seasonal MSL Variability on Extreme Sea Levels in the German Bight

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Energy Market Projections and Differentiated Carbon Abatement in the European Union

We analyze the economic effects of the differentiated targets for carbon abatement in six European Union member states. Our recursively-dynamic model includes a detailed representation of trade and energy consumption and incorporates optimistic projections for future energy markets provided by the European Commission as the Business-as-Usual scenario. In the base case we find that the EU implementation of the Kyoto Protocol implies low overall costs and a relatively even cost distribution across member states. We also show that a less optimistic development in energy efficiency implies higher costs in all countries, especially in those with high abatement costs. Finally, we find that uniform abatement targets increase overall costs marginally but changes the cost distribution significantly, holding total EU emissions constant

Risky business? Welfare state reforms and government support in Britain and Denmark

Are welfare state reforms electorally dangerous for governments? Political scientists have only recently begun to study this seemingly simple question, and existing work still suffers from two shortcomings. First, it has never tested the reform–vote link with data on actual legislative decisions for enough points in time to allow robust statistical tests. Secondly, it has failed to take into account the many expansionary reforms that have occurred in recent decades. Expansions often happen in the same years as cutbacks. By focusing only on cutbacks, estimates of the effects of reforms on government popularity become biased. This article addresses both shortcomings. The results show that voters punish governments for cutbacks, but also reward them for expansions, making so-called compensation, a viable blame-avoidance strategy. The study also finds that the size of punishments and rewards is roughly the same, suggesting that voters’ well-documented negativity bias does not directly translate into electoral behavior

User community vs. producer innovation development efficiency: A first empirical study

In this paper we report upon a first empirical exploration of the relative efficiency of innovation development by product users vs. product producers. In a study of over 50 years of product innovation in the whitewater kayaking field, we find users in aggregate were approximately 3× more efficient at developing important kayaking product innovations than were producers in aggregate. We speculate that this result is driven by what we term “efficiencies of scope” in problem-solving. These can favor an aggregation of many user innovators, each spending a little, over fewer producer innovators benefitting from higher economies of scale in product development. We also note that the present study explores only one initial point on what is likely to be a complex efficiency landscape

The Performance of the Robo-AO Laser Guide Star Adaptive Optics System at the Kitt Peak 2.1-m Telescope

Robo-AO is an autonomous laser guide star adaptive optics system recently commissioned at the Kitt Peak 2.1-m telescope. Now operating every clear night, Robo-AO at the 2.1-m telescope is the first dedicated adaptive optics observatory. This paper presents the imaging performance of the adaptive optics system in its first eighteen months of operations. For a median seeing value of $1.31^{\prime\prime}$, the average Strehl ratio is 4\% in the $i^\prime$ band and 29\% in the J band. After post-processing, the contrast ratio under sub-arcsecond seeing for a $2\leq i^{\prime} \leq 16$ primary star is five and seven magnitudes at radial offsets of $0.5^{\prime\prime}$ and $1.0^{\prime\prime}$, respectively. The data processing and archiving pipelines run automatically at the end of each night. The first stage of the processing pipeline shifts and adds the data using techniques alternately optimized for stars with high and low SNRs. The second "high contrast" stage of the pipeline is eponymously well suited to finding faint stellar companions.Comment: 12 pages, 16 figures, to be submitted to PAS

An approximate Markov model for the wright-fisher diffusion and its application to time series data

The joint and accurate inference of selection and demography from genetic data is considered a particularly challenging question in population genetics, since both process may lead to very similar patterns of genetic diversity. However, additional information for disentangling these effects may be obtained by observing changes in allele frequencies over multiple time points. Such data is common in experimental evolution studies, as well as in the comparison of ancient and contemporary samples. Leveraging this information, however, has been computationally challenging, particularly when considering multi-locus data sets. To overcome these issues, we introduce a novel, discrete approximation for diffusion processes, termed mean transition time approximation, which preserves the long-term behavior of the underlying continuous diffusion process. We then derive this approximation for the particular case of inferring selection and demography from time series data under the classic Wright- Fisher model and demonstrate that our approximation is well suited to describe allele trajectories through time, even when only a few states are used. We then develop a Bayesian inference approach to jointly infer the population size and locus-specific selection coefficients with high accuracy, and further extend this model to also infer the rates of sequencing errors and mutations. We finally apply our approach to recent experimental data on the evolution of drug resistance in Influenza virus, identifying likely targets of selection and finding evidence for much larger viral population sizes than previously reported