Lancaster University

About: Lancaster University is a education organization based out in Lancaster, Lancashire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 13080 authors who have published 44563 publications receiving 1692277 citations. The organization is also known as: The University of Lancaster & Lancaster University.

Do Better-Governed Australian Firms Make More Informative Disclosures?

Abstract: We investigate whether and if so, how, corporate governance quality is related to the information flows from a company and how the stock market and its agents respond. Specifically, we study links between the quality of a firm's corporate governance (CGQ) and the informativeness of its disclosures. We employ a novel, intra-year timeliness metric, in the spirit of Ball and Brown (1968) and Brown et al. (1999), to capture the average speed of price discovery throughout the year. Our results suggest the answer to our question is Yes: better-governed firms do make more informative disclosures.

Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions

Abstract: The major implementational problem for reversible jump Markov chain Monte Carlo methods is that there is commonly no natural way to choose jump proposals since there is no Euclidean structure in the parameter space to guide our choice We consider mechanisms for guiding the choice of proposal The first group of methods is based on an analysis of acceptance probabilities for jumps Essentially, these methods involve a Taylor series expansion of the acceptance probability around certain canonical jumps and turn out to have close connections to Langevin algorithms The second group of methods generalizes the reversible jump algorithm by using the so-called saturated space approach These allow the chain to retain some degree of memory so that, when proposing to move from a smaller to a larger model, information is borrowed from the last time that the reverse move was performed The main motivation for this paper is that, in complex problems, the probability that the Markov chain moves between such spaces may be prohibitively small, as the probability mass can be very thinly spread across the space Therefore, finding reasonable jump proposals becomes extremely important We illustrate the procedure by using several examples of reversible jump Markov chain Monte Carlo applications including the analysis of autoregressive time series, graphical Gaussian modelling and mixture modelling

Second-order analysis of spatial clustering for inhomogeneous populations.

Abstract: Motivated by recent interest in the possible spatial clustering of rare diseases, the paper develops an approach to the assessment of spatial clustering based on the second-moment properties of a labelled point process. The concept of no spatial clustering is identified with the hypothesis that in a realisation of a stationary spatial point process consisting of events of two qualitatively different types, the type 1 events are a random sample from the superposition of type 1 and type 2 events. A diagnostic plot for estimating the nature and physical scale of clustering effects is proposed. The availability of Monte Carlo tests of significance is noted. An application to published data on the spatial distribution of childhood leukaemia and lymphoma in North Humberside is described.

Linkages of plant traits to soil properties and the functioning of temperate grassland

Abstract: Summary 1. Global change is likely to alter plant community structure, with consequences for the structure and functioning of the below-ground community and potential feedbacks to climate change. Understanding the mechanisms behind these plant–soil interactions and feedbacks to the Earth-system is therefore crucial. One approach to understanding such mechanisms is to use plant traits as predictors of functioning. 2. We used a field-based monoculture experiment involving nine grassland species that had been growing on the same base soil for 7 years to test whether leaf, litter and root traits associated with different plant growth strategies can be linked to an extensive range of soil properties relevant to carbon, nitrogen and phosphorus cycling. Soil properties included the biomass and structure of the soil microbial community, soil nutrients, soil microclimate and soil process rates. 3. Plant species with a high relative growth rate (RGR) were associated with high leaf and litter quality (e.g. low toughness, high nitrogen concentrations), an elevated biomass of bacteria relative to fungi in soil, high rates of soil nitrogen mineralization and concentrations of extractable inorganic nitrogen, and to some extent higher available phosphorus pools. 4. In contrast to current theory, species with a high RGR and litter quality were associated with soils with a lower rate of soil respiration and slow decomposition rates. This indicates that predicting processes that influence carbon cycling from plant traits may be more complex than predicting processes that influence nitrogen and phosphorus cycling. 5. Root traits did not show strong relationships to RGR, leaf or litter traits, but were strongly correlated with several soil properties, particularly the biomass of bacteria relative to fungi in soil and measures relating to soil carbon cycling. 6. Synthesis. Our results indicate that plant species from a single habitat can result in significant divergence in soil properties and functioning when grown in monoculture, and that many of these changes are strongly and predictably linked to variation in plant traits associated with different growth strategies. Traits therefore have the potential to be a powerful tool for understanding the mechanisms behind plant–soil interactions and ecosystem functioning, and for predicting how changes in plant species composition associated with global change will feedback to the Earth-system.