91 resultados para voluntary demand


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Conventional seemingly unrelated estimation of the almost ideal demand system is shown to lead to small sample bias and distortions in the size of a Wald test for symmetry and homogeneity when the data are co-integrated. A fully modified estimator is developed in an attempt to remedy these problems. It is shown that this estimator reduces the small sample bias but fails to eliminate the size distortion.. Bootstrapping is shown to be ineffective as a method of removing small sample bias in both the conventional and fully modified estimators. Bootstrapping is effective, however, as a method of removing. size distortion and performs equally well in this respect with both estimators.

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In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

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A novel two-step paradigm was used to investigate the parallel programming of consecutive, stimulus-elicited ('reflexive') and endogenous ('voluntary') saccades. The mean latency of voluntary saccades, made following the first reflexive saccades in two-step conditions, was significantly reduced compared to that of voluntary saccades made in the single-step control trials. The latency of the first reflexive saccades was modulated by the requirement to make a second saccade: first saccade latency increased when a second voluntary saccade was required in the opposite direction to the first saccade, and decreased when a second saccade was required in the same direction as the first reflexive saccade. A second experiment confirmed the basic effect and also showed that a second reflexive saccade may be programmed in parallel with a first voluntary saccade. The results support the view that voluntary and reflexive saccades can be programmed in parallel on a common motor map. (c) 2006 Elsevier Ltd. All rights reserved.

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Media content distribution on-demand becomes more complex when performed on a mass scale involving various channels with distinct and dynamic network characteristics, and, deploying a variety of terminal devices offering a wide range of capabilities. It is practically impossible to create and prepackage various static versions of the same content to match all the varying demand parameters of clients for various contexts. In this paper we present a profiling management approach for dynamically personalised media content delivery on-demand integrated with the AXMEDIS Framework. The client profiles comprise the representation of User, Device, Network and Context of content delivery based on MPEG-21:DIA. Although the most challenging proving ground for this personalised content delivery has been the mobile testbed i.e. the distribution to mobile handsets, the framework described here can be deployed for disribution, by the AXMEDIS PnP module, through other channels e.g. satellite, Internet to a range of client terminals e.g. desktops, kiosks, IPtv and other terrminals whose baseline terminal capabilities can be made availabe by the manufacturers as is normal.

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This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

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The 1930s witnessed an intense struggle between gas and electricity suppliers for the working class market, where the incumbent utility—gas—was also a reasonably efficient (and cheaper) General Purpose Technology for most domestic uses. Local monopolies for each supplier boosted substitution effects between fuel types—as alternative fuels constituted the only local competition. Using newly-rediscovered returns from a major national household expenditure survey, we employ geographically-determined instrumental variables, more commonly used in the industrial organization literature, to show that gas provided a significant competitor, tempering electricity prices, while electricity demand was also responsive to marketing initiatives.

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A Bayesian method of estimating multivariate sample selection models is introduced and applied to the estimation of a demand system for food in the UK to account for censoring arising from infrequency of purchase. We show how it is possible to impose identifying restrictions on the sample selection equations and that, unlike a maximum likelihood framework, the imposition of adding up at both latent and observed levels is straightforward. Our results emphasise the role played by low incomes and socio-economic circumstances in leading to poor diets and also indicate that the presence of children in a household has a negative impact on dietary quality.