Public leisure provision under Compulsory Competitive Tendering: the maintenance of ideological dominance?

Although much has been written about the effect on services of public sector restructuring, little is yet available on public leisure provision. This omission is addressed by considering how the delivery of public leisure services in Britain has been affected by the imposition of Compulsory Competitive Tendering (CCT). In particular, it focuses on the changing relationship between the central and local levels of government recognising, on the part of local government, a continuum of structural responses to central initiatives which have, in some cases, conspired to reduce the impact of CCT on public leisure provision. The paper concludes that although attempts have been made to protect local services, the outcome of the CCT process has been the regeneration of public leisure provision away from its service roots, but within an enduring ideological paradigm of conservative professionalism.

Direct Computation of Stochastic Flow in Reservoirs with Uncertain Parameters

A direct method is presented for determining the uncertainty in reservoir pressure, flow, and net present value (NPV) using the time-dependent, one phase, two- or three-dimensional equations of flow through a porous medium. The uncertainty in the solution is modelled as a probability distribution function and is computed from given statistical data for input parameters such as permeability. The method generates an expansion for the mean of the pressure about a deterministic solution to the system equations using a perturbation to the mean of the input parameters. Hierarchical equations that define approximations to the mean solution at each point and to the field covariance of the pressure are developed and solved numerically. The procedure is then used to find the statistics of the flow and the risked value of the field, defined by the NPV, for a given development scenario. This method involves only one (albeit complicated) solution of the equations and contrasts with the more usual Monte-Carlo approach where many such solutions are required. The procedure is applied easily to other physical systems modelled by linear or nonlinear partial differential equations with uncertain data.

On the long time behavior of free stochastic Schrödinger evolutions

We discuss the time evolution of the wave function which is the solution of a stochastic Schrödinger equation describing the dynamics of a free quantum particle subject to spontaneous localizations in space. We prove global existence and uniqueness of solutions. We observe that there exist three time regimes: the collapse regime, the classical regime and the diffusive regime. Concerning the latter, we assert that the general solution converges almost surely to a diffusing Gaussian wave function having a finite spread both in position as well as in momentum. This paper corrects and completes earlier works on this issue.

On a stochastic Trotter formula with application to spontaneous localization models

We consider the relation between so called continuous localization models—i.e. non-linear stochastic Schrödinger evolutions—and the discrete GRW-model of wave function collapse. The former can be understood as scaling limit of the GRW process. The proof relies on a stochastic Trotter formula, which is of interest in its own right. Our Trotter formula also allows to complement results on existence theory of stochastic Schrödinger evolutions by Holevo and Mora/Rebolledo.

Structure, conduct and the stochastic volatility of food markets: theory and empirics

The relationship between price volatility and competition is examined. Atheoretic, vector auto regressions on farm prices of wheat and retail prices of derivatives (flour, bread, pasta, bulgur and cookies) are compared to results from a dynamic, simultaneous-equations model with theory-based farm-to-retail linkages. Analytical results yield insights about numbers of firms and their impacts on demand- and supply-side multipliers, but the applications to Turkish time series (1988:1-1996:12) yield mixed results.

First order k-th moment finite element analysis of nonlinear operator equations with stochastic data

We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(\alpha ,u)=0 for random input \alpha (\omega ) with almost sure realizations in a neighborhood of a nominal input parameter \alpha _0. Under some structural assumptions on the parameter dependence, we prove existence and uniqueness of a random solution, u(\omega ) = S(\alpha (\omega )). We derive a multilinear, tensorized operator equation for the deterministic computation of k-th order statistical moments of the random solution's fluctuations u(\omega ) - S(\alpha _0). We introduce and analyse sparse tensor Galerkin discretization schemes for the efficient, deterministic computation of the k-th statistical moment equation. We prove a shift theorem for the k-point correlation equation in anisotropic smoothness scales and deduce that sparse tensor Galerkin discretizations of this equation converge in accuracy vs. complexity which equals, up to logarithmic terms, that of the Galerkin discretization of a single instance of the mean field problem. We illustrate the abstract theory for nonstationary diffusion problems in random domains.

The significance of occupancy steadiness in residential consumer response to Time of Use pricing: Evidence from a stochastic adjustment model

The recent roll-out of smart metering technologies in several developed countries has intensified research on the impacts of Time-of-Use (TOU) pricing on consumption. This paper analyses a TOU dataset from the Province of Trento in Northern Italy using a stochastic adjustment model. Findings highlight the non-steadiness of the relationship between consumption and TOU price. Weather and active occupancy can partly explain future consumption in relation to price.

The stochastic component in choice and regression to the mean

In this article, we illustrate experimentally an important consequence of the stochastic component in choice behaviour which has not been acknowledged so far. Namely, its potential to produce ‘regression to the mean’ (RTM) effects. We employ a novel approach to individual choice under risk, based on repeated multiple-lottery choices (i.e. choices among many lotteries), to show how the high degree of stochastic variability present in individual decisions can distort crucially certain results through RTM effects. We demonstrate the point in the context of a social comparison experiment.

Dominance in the Tetra Pak case: an empirical approach

The 1991 decision of the European Commission on the Tetra Pak case was based on information which seemed to prove the firm's anti-competitive behavior. The Tetra Pak case is investigated here focusing on the meaning of multimarket dominance, using empirical techniques. We find that a more rigorous analysis of the data available would not confirm the Commission's assertions. That is, it cannot be concluded with certainty that the Commission was right to relate Tetra Pak's dominance in the aseptic sector to its market power in the non-aseptic sector. Our results suggest a general framework for the analysis of abusive transfer of market power across vertically or/and horizontally related markets.

Leader of the pack? German monetary dominance in Europe prior to EMU

In this paper, the monetary policy independence of European nations in the years before European Economic and Monetary Union (EMU) is investigated using cointegration techniques. Daily data is used to assess pairwise relationships between individual EMU nations and ‘lead’ nation Germany, to assess the hypothesis that Germany was the dominant European nation prior to EMU. By and large our econometric investigations support this hypothesis, and lead us to conclude that the only European nation to lose monetary policy independence in the light of monetary union was Germany. Our results have important policy implications. Given that the loss of monetary policy independence is generally viewed as the main cost of monetary unification, our findings suggest a reconsideration of the costs and benefits of monetary integration. A country can only lose what it has, and in Europe the countries that joined EMU — spare Germany — apparently did not have much to lose, at least not in terms of monetary independence. Instead, they actually gained monetary policy influence by getting a seat in the ECB's governing council which is responsible for setting interest policy in the euro area.

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models.

Species diversity and dominance-richness relationships for ground and arboreal ant (Hymenoptera: Formicidae) assemblages in Namibian desert, saltpan, and savannah

Namibia has high levels of invertebrate endemism, but biodiversity research has been geographically and taxonomically limited. In South African savannah, species richness of ground-foraging ant assemblages is regulated by dominant ant species, but this pattern has not been tested in other arid environments. In this study, we provide a description of ant diversity at baits in three different Namibian habitats (savannah, saltpan and desert), and we test the relationship between ant dominance and richness for ground-foraging and arboreal species. Forty-two ant species were collected in this study, with species richness being highest in the saltpan, followed by savannah and then desert. Ant assemblages were most similar between the savannah and desert, due to shared arboreal species. Similarity between savannah and saltpan ant assemblages was due to an overlap in ground-foraging species. Ground ants were more diverse than arboreal ants, and several species were observed at baits for both strata, although the degree of overlap varied with habitat type. The dominance-richness relationship varied depending on habitat and sampling strata. We found a unimodal relationship in the saltpan, but not in the savannah. For ground ants the relationship was logarithmic, with increasing abundance of dominants leading to decreasing overall species richness. However, no trend was observed for the arboreal ant assemblage. In the desert, low ant abundance meant that we were unable to assign species dominance, possibly due to reduced foraging activity caused by high temperatures. The lack of a consistent dominance-richness trend across assemblages may be the result of varying degrees of environmental stress or competition. Our study is a preliminary description of diversity and dominance in Namibia, and we hope it stimulates further research on ant assemblages in arid regions of Africa.

Using lexical diversity measures to operationalise language dominance in bilinguals

Treffers-Daller and Korybski propose to operationalize language dominance on the basis of measures of lexical diversity, as computed, in this particular study, on transcripts of stories told by Polish-English bilinguals in each of their languages They compute four different Indices of Language Dominance (ILD) on the basis of two different measures of lexical diversity, the Index of Guiraud (Guiraud, 1954) and HD-D (McCarthy & Jarvis, 2007). They compare simple indices, which are based on subtracting scores from one language from scores for another language, to more complex indices based on the formula Birdsong borrowed from the field of handedness, namely the ratio of (Difference in Scores) / (Sum of Scores). Positive scores on each of these Indices of Language Dominance mean that informants are more English-dominant and negative scores that they are more Polish-dominant. The authors address the difficulty of comparing scores across languages by carefully lemmatizing the data. Following Flege, Mackay and Piske (2002) they also look into the validity of these indices by investigating to what extent they can predict scores on other, independently measured variables. They use correlations and regression analysis for this, which has the advantage that the dominance indices are used as continuous variables and arbitrary cut-off points between balanced and dominant bilinguals need not be chosen. However, they also show how the computation of z-scores can help facilitate a discussion about the appropriateness of different cut-off points across different data sets and measurement scales in those cases where researchers consider it necessary to make categorial distinctions between balanced and dominant bilinguals. Treffers-Daller and Korybski correlate the ILD scores with four other variables, namely Length of Residence in the UK, attitudes towards English and life in the UK, frequency of usage of English at home and frequency of code-switching. They found that the indices correlated significantly with most of these variables, but there were clear differences between the Guiraud-based indices and the HDD-based indices. In a regression analysis three of the measures were also found to be a significant predictor of English language usage at home. They conclude that the correlations and the regression analyses lend strong support to the validity of their approach to language dominance.