935 resultados para electricity market
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The seminal work of J. B. Jefferys highlighted two unusual features of the Victorian equity market, namely high share denomination and uncalled capital. This article examines the extent to which publicly traded company stocks in the nineteenth century had these features. It also analyses the effect of these features on stock returns using monthly data for the London Stock Market over the period 1825–70. We find that stocks with unpaid capital earned a higher return, which is consistent with investors being rewarded for the risk of a call on their personal assets. We also find that stocks with a high share denomination earned a lower return, which is consistent with the view that this feature was conducive to superior corporate governance.
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This article examines the nature of labour market exclusion in Belfast and policy responses to the dilemmas of ethnic space. It highlights the value of an area-based approach to understanding the way in which social and ethno-sectarian segregation mediates access to production sites and job opportunities in the wider urban economy. Research from the Belfast metropolitan labour market is used to identify the importance of employment in neutral areas, which can stimulate access from ethnically and socially polarised communities. The article argues for a spatial approach to understanding the structuring of labour market opportunities and constraints and it concludes by highlighting the implications for policy and practice in ethnically territorialised spaces.
Investor Behaviour in a Nascent Capital Market: Scottish Bank Shareholders in the Nineteenth Century
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Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.
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Recent cold winters and prolonged periods of low wind speeds have prompted concerns about the increasing penetration of wind generation in the Irish and other northern European power systems. On the combined Republic of Ireland and Northern Ireland system there was in excess of 1.5 GW of installed wind power in January 2010. As the penetration of these variable, non-dispatchable generators increases, power systems are becoming more sensitive to weather events on the supply side as well as on the demand side. In the temperate climate of Ireland, sensitivity of supply to weather is mainly due to wind variability while demand sensitivity is driven by space heating or cooling loads. The interplay of these two weather-driven effects is of particular concern if demand spikes driven by low temperatures coincide with periods of low winds. In December 2009 and January 2010 Ireland experienced a prolonged spell of unusually cold conditions. During much of this time, wind generation output was low due to low wind speeds. The impacts of this event are presented as a case study of the effects of weather extremes on power systems with high penetrations of variable renewable generation.
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This article examines the impact of pension deficits on default risk as measured by the premia on corporate credit default swaps (CDS). We find highly significant evidence that unfunded pension liabilities raise one- and five-year CDS premia. However, this relation is not homogeneous across countries, with the U.S. CDS market leading its European counterparts in the pricing of defined-benefit pension risk.
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We study the residential demand for electricity and gas, working with nationwide household-level data that cover recent years, namely 1997-2007. Our dataset is a mixed panel/multi-year cross-sections of dwellings/households in the 50 largest metropolitan areas in the United States as of 2008. We estimate static and dynamic models of electricity and gas demand. We find strong household response to energy prices, both in the short and long term. From the static models, we get estimates of the own price elasticity of electricity demand in the -0.860 to -0.667 range, while the own price elasticity of gas demand is -0.693 to -0.566. These results are robust to a variety of checks. Contrary to earlier literature (Metcalf and Hassett, 1999; Reiss and White, 2005), we find no evidence of significantly different elasticities across households with electric and gas heat. The price elasticity of electricity demand declines with income, but the magnitude of this effect is small. These results are in sharp contrast to much of the literature on residential energy consumption in the United States, and with the figures used in current government agency practice. Our results suggest that there might be greater potential for policies which affect energy price than may have been previously appreciated. (C) 2011 Elsevier B.V. All rights reserved.
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In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured.