878 resultados para electricity prices


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Germany’s decision to give up the use of nuclear energy will force it to find a conventional low-carbon energy source as a replacement; in the short term, in addition to coal, this is likely to be gas. Due to their continued high debt and the losses associated with the end of atomic power, German companies will not be able to spend large funds on investing in conventional energy. First of all, they will aim to raise capital and repay their debts. The money for this will come from selling off their less profitable assets; this will include sales on the gas market. This will create opportunities for natural gas exporters and extraction companies such as Gazprom to buy back some of the German companies’ assets (electricity companies, for example). The German companies will probably continue to seek to recover the costs incurred in the investment projects already underway, such as Nord Stream, the importance of which will grow after Russian gas imports increase. At the same time, because of their debts, the German companies will seek to minimise their investment costs by selling some shares on the conventional energy market, to Russian corporations among others; the latter would thus be able to increase their stake in the gas market in both Western (Germany, Great Britain, the Benelux countries) and Central Europe (Poland, the Czech Republic). It is possible that while establishing the details of cooperation between the Russian and German companies, Russia will try to put pressure on Germany to give up competing projects such as Nabucco. However, a well-diversified German energy market should be able to defend itself against attempts to increase German dependence on Russian gas supplies and the dictates of high prices.

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This paper empirically analyses a dataset of more than 7,300 agricultural land sales transactions from 2001 and 2007 to identify the factors influencing agricultural land prices in Bavaria. We use a general spatial model, which combines a spatial lag and a spatial error model, and in addition account for endogeneity introduced by the spatially lagged dependent variable as well as other explanatory variables. Our findings confirm the strong influence of agricultural factors such as land productivity, of variables describing the regional land market structure, and of non-agricultural factors such as urban pressure on agricultural land prices. Moreover, the involvement of public authorities as a seller or buyer increases sales prices in Bavaria. We find a significant capitalisation of government support payments into agricultural land, where a decrease of direct payments by 1% would decrease land prices in 2007 and 2001 by 0.27% and 0.06%, respectively. In addition, we confirm strong spatial relationships in our dataset. Neglecting this leads to biased estimates, especially if aggregated data is used. We find that the price of a specific plot increases by 0.24% when sales prices in surrounding areas increase by 1%.