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The present article explores the structure of and recent developments in research activities in the polar regions. Based on a bibliographic study of published papers indexed in the ISI Web of Science during the period 1981-2007, we have analyzed trends in publication, scientific disciplines and subdisciplines, coauthorship, and international collaboration within the field of polar research. We have uncovered several rather striking trends. Scientific output in terms of refereed publications has increased far more rapidly in polar research compared to science in general, quadrupling rather than doubling over the surveyed period. There is a nearly 1:1 ratio between papers covering the Arctic relative to the Antarctic, with the vast majority within either the geosciences (40%) or biology (33%). There has been particularly a steep rise in the number of climate-related papers. The U.S.A. is by far the largest contributor to polar research on both the Arctic and the Antarctic, followed by Canada, the U.K., Germany, Norway, and Russia. The number of coauthored papers has grown markedly, reflecting geopolitical shifts and changing national and international funding priorities during the period. We believe our publication-based survey reveals interesting developments in scientific activities and international cooperation in general, and in polar science strategies and priorities in particular. [ABSTRACT FROM AUTHOR]

Novel periodic extensions of dynamic long-memory regression models with autoregressive conditional heteroscedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specifications are estimated simultaneously by the method of approximate maximum likelihood. The methods are implemented for time series of 1,200-4,400 daily price observations in tour European power markets. Apart from persistence, heteroscedasticity, and extreme observations in prices, a novel empirical finding is the importance of day-of-the-week periodicity in the autocovariance function of electricity spot prices. In particular, the very persistent daily log prices from the Nord Pool power exchange of Norway are effectively modeled by our framework, which is also extended with explanatory variables to capture supply-and-demand effects. The daily log prices of the other three electricity markets--EEX in Germany, Powernext in France, and APX in The Netherlands are less persistent, but periodicity is also highly significant. The dynamic behavior differs from market to market and depends primarily on the method of power generation: hydro power, power generated from fossil fuels, or nuclear power. The article improves on existing models in capturing the memory characteristics, which are important in derivative pricing and real option analysis. [ABSTRACT FROM AUTHOR]