Demand Uncertainty and the Regulated Firm

[Introduction] In this paper, we investigate the impact of demand uncertainty on the choice of plant capacity by a regulated firm. Over the past few years, demand uncertainty has become a major element in the decision-making of utilities, and particularly in their decision-making with respect to capacity choices. In a recent study by SRI [1977], it was reported that to maximize expected consumers' surplus, more generating capacity was required for the electric utility industry when operating under demand uncertainty than under demand certainty.1 This finding raises the question whether the structure of rate regulation of electric utilities provides the appropriate incentives for them to invest in more capacity under demand uncertainty then under certainty. The present paper addresses such questions

Demand Uncertainty and the Regulated Firm

Demand uncertainty is an important element of many regulated markets. Firms often must select plant size before actual demand is observed, and with some expectation of regulatory action if the actual levels of profit or rate of return do not fall within accepted ranges. We analyze a model of a regulated firm that faces a relatively complex regime of price regulation, reflecting to at least some extent the multiple aspects suggested by Joskow (1974). The firm behaves as though it expects the current tariff to remain in effect unless, at the actual demand observed after plant size is chosen, one of two things occurs. First, if profits are negative, the firm plans to petition for and expects to receive a new tariff yielding zero economic profits. Second, if the rate of return on capital exceeds some specified maximum, the firm expects the regulator to reduce the tariff so that the firm earns only that maximum

Modelling the evolution of distributions : an application to major league baseball

We develop Bayesian techniques for modelling the evolution of entire distributions over time and apply them to the distribution of team performance in Major League baseball for the period 1901-2000. Such models offer insight into many key issues (e.g. competitive balance) in a way that regression-based models cannot. The models involve discretizing the distribution and then modelling the evolution of the bins over time through transition probability matrices. We allow for these matrices to vary over time and across teams. We find that, with one exception, the transition probability matrices (and, hence, competitive balance) have been remarkably constant across time and over teams. The one exception is the Yankees, who have outperformed all other teams

Numerical experiments on short-term meteorological effects on solar variability

A set of numerical experiments was conducted to test the short-range sensitivity of a large atmospheric general circulation model to changes in solar constant and ozone amount. On the basis of the results of 12-day sets of integrations with very large variations in these parameters, it is concluded that realistic variations would produce insignificant meteorological effects. Any causal relationships between solar variability and weather, for time scales of two weeks or less, rely upon changes in parameters other than solar constant or ozone amounts, or upon mechanisms not yet incorporated in the model

A parallel adaptive mesh refinement algorithm

Over recent years, Adaptive Mesh Refinement (AMR) algorithms which dynamically match the local resolution of the computational grid to the numerical solution being sought have emerged as powerful tools for solving problems that contain disparate length and time scales. In particular, several workers have demonstrated the effectiveness of employing an adaptive, block-structured hierarchical grid system for simulations of complex shock wave phenomena. Unfortunately, from the parallel algorithm developer's viewpoint, this class of scheme is quite involved; these schemes cannot be distilled down to a small kernel upon which various parallelizing strategies may be tested. However, because of their block-structured nature such schemes are inherently parallel, so all is not lost. In this paper we describe the method by which Quirk's AMR algorithm has been parallelized. This method is built upon just a few simple message passing routines and so it may be implemented across a broad class of MIMD machines. Moreover, the method of parallelization is such that the original serial code is left virtually intact, and so we are left with just a single product to support. The importance of this fact should not be underestimated given the size and complexity of the original algorithm

Experiences influencing walking football initiation in 55-75 year-old adults

Adults aged 55 and older are least likely to play sport. Despite research suggesting this population experiences physical and psychological benefits when doing so, limited research focuses on older adult sport initiation, especially in “adapted sports” such as walking football. The aim of this study was to explore initiation experiences of walking football players between 55 and 75 years old. Semistructured interviews took place with 17 older adults playing walking football for 6 months minimum ( Mage = 64). Inductive analysis revealed six higher order themes representing preinitiation influences. Eight further higher order themes were found, relating to positive and negative experiences during initiation. Fundamental influences preinitiation included previous sporting experiences and values and perceptions. Emergent positive experiences during initiation included mental development and social connections. Findings highlight important individual and social influences when initiating walking football, which should be considered when encouraging 55- to 75-year-old adults to play adapted sport. Policy and practice recommendations are discussed

Determining the ejection rate and energy spectrum of protons after muonic capture on aluminum

Observation of neutrinoless muon-to-electron conversion in the presence of a nucleus would be unambiguous evidence of physics Beyond the Standard Model. Two experiments, COMET at J-PARC and Mu2e at Fermilab, will search for this process in the next few years. These experiments will provide upper-limits on this branching ratio up to 10,000 times better than previously published. COMET/Mu2e developed a joint venture, the AlCap Experiment, to measure particle emission spectra from muonic interactions in several materials. Targeting a significant source of damage and background hits in COMET/Mu2e detectors, AlCap measured the charged particle and neutron spectra following nuclear capture on the candidate target materials aluminum and titanium, as well as in many structural and shielding materials capable of producing other backgrounds. Additionally, COMET/Mu2e are exploring schemes for determining the number of in-target muon stops via AlCap’s measurement of the photon spectra produced by both atomic and nuclear capture. AlCap performed three data-taking campaigns between 2013 and 2015 at the Paul Scherrer Institut in Switzerland, each geared towards different measurements of photon, neutron, and charged particle emission due to interactions of muons stopping in materials. During the final campaign, AlCap collected heavy charged particle data. In this thesis, I present a measurement of the proton emission spectrum for an aluminum target from the most recent campaign and compare it with the results of previous and current parallel analyses. I also discuss the impact on Mu2e