Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

The effect of external supply knowledge acquisition,development activities and organizational status on the supply performance of SMEs

Given the increasingly strategic role of external resources, acquiring knowledge about current suppliers and the broader supply market is an important and demanding task for the purchasing and supply management (PSM) function of a firm. Performance-improvement-oriented application of external supply knowledge present further challenges for the function. To examine this, we draw on the knowledge-based view and develop a hypothesized model in which supply knowledge acquisition drives PSM exploration and exploitation orientations which in turn mediate the organizational status of PSM function in terms of supply performance. We test the model on an SME-focused and survey-based dataset, using structural equation modelling. Our results indicate that an exploitative orientation is associated with knowledge gained from the supply base, whereas an explorative orientation is predominantly associated with supply market knowledge and less with supply base knowledge, suggesting natural pairings. The findings also show how an exploitative development orientation mediates the positive association of the PSM function's organizational status with supply performance. Driven by supply base knowledge, a status-empowered exploitative PSM orientation may suppress supply market based explorative orientation in resource-scarce SMEs, thus appearing to serve as the sole path to supply performance. Our research contributes by pointing out the significance of the knowledge-resource, and the knowledge-based view, in understanding performance in PSM.     

An Examination of the Interaction Between Modelling and Its Relationship with Construction Kits: Lessons from the Past and for the Future

Construction kits have played a significant part in nurturing the growth and development of the minds and manipulation-based skills of children (and adults) in formal and non-formal education settings. These kits have origins rooted in the representation of the built world and now have a diversity of form and function, including technical versions with moving parts. This article examines some of the historically based ideas that lie behind the role that kits may have in terms of physical modelling. The article traces the transformation of kits from simple bricks and blocks into more complicated pieces for space-filling and achieving the transfer of forces and motion. This transformation occurred during the Victorian era when the influence of the ideas of educationalists and, perhaps rather strangely, exponents of early aviation, played major roles in determining the diversity of forms of construction kit and modelled possibilities that are now to be seen in classrooms and homes. The article ends with a review of some of the lessons from the past and present that will need to be considered in relation to concrete modelling in schools for the future. This revised version was published online in July 2006 with corrections to the Cover Date.     

Tourism as an alternative source of regional growth in Portugal: a panel data analysis at NUTS II and III levels

The role of tourism is of vital economic importance, particularly for small countries with a privileged geographical location and favourable weather conditions. This paper examines the importance of tourism as a conditioning factor for higher regional growth in Portugal by employing the conditional convergence hypothesis of Barro and Sala-i-Martin, associated with the endogenous growth theory. The panel data estimation approach provides evidence of the positive impact of tourism (through the accommodation capacity) on the growth in per-capita income among the Portuguese regions, increasing the rate of convergence. Therefore, tourism can be considered as an alternative source for stimulating higher regional growth in Portugal, if the supply characteristics of this sector are improved.     

Crossing spatial analyses and livestock economics to understand deforestation processes in the Brazilian Amazon: the case of São Félix do Xingú in South Pará

The Amazon is the largest tropical forest area on Earth, and has been undergoing rapid deforestation for the last four decades. In the Brazilian Amazon, large‐scale pasture for cattle ranching and soybean production are the main land uses, leading to a yearly deforestation rate of 0.5%. These conversions are mostly located in frontier areas distributed along the so‐called “arc of deforestation”. Within this large zone, various land use change processes are interacting through several modes of land valuation and organisation. From several case studies in the State of Pará (Brazil), the current project aims at analysing how landscape dynamics are related to infrastructure development, ecological conditions, zoning policies and to the evolution and the organisation of the production, consumption and marketing chains of livestock products. This paper presents the results for one test site, the region of São Félix do Xingú, South of Pará This region is the focus of land speculation, cattle expansion, and deforestation. Road construction, investments in electrical energy, financial credit for cattle, and the land reform policies have all fuelled this process. All these factors make this region one of the most dynamic agricultural frontiers in the Brazilian Amazon. The main objective of the paper is to improve our understanding of deforestation processes by crossing spatial analyses and 1ivestock economics.studies, and to characterise the role and impact of various natural and anthropic factors in the location and development of the main types of farmers, and their policy implications.     

Learning in Design and Technology: The Impact of Social and Cultural Influences on Modelling

The paper introduces the highly problematic nature of modelling in design and technology education and examines the relationship between cognitive and concrete modelling. Its aim is to gain insight into what learners do, rather than what others say they ought to do in their learning activities. The variety of purposes that educators have for learners’ modelling are discussed through examining the contested curriculum justification for design and technology education itself. The paper proposes that learners’ modelling cannot be extracted from the social milieu in which they act and it provides some insights of these social influences through the analysis of two case studies. Their settings are a girls’ secondary school and a college of higher education. Each case study is presented independently but organised with a common format to consider a) the impact of assessment on learning intentions and outcomes; b) cultural influences on learning and modelling; c) social influences on learning and modelling. A discussion of the emergent themes considers implications for teachers. This revised version was published online in July 2006 with corrections to the Cover Date.     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

Extending working hours: why not work 42 h rather than 38?—a CGE analysis for Germany

Faced with a record level of unemployment, the present debate in Germany is to extend the weekly hours of work. In this paper the employment effects of an economy-wide increase in weekly hours are quantified on the basis of a computable general equilibrium model for different specifications of the wage setting rule and the use of additional policy-induced public income. The simulation results back the argument of the opponents of longer working time that not more jobs will be created. However, when the higher tax revenues from GDP growth are used to reduce social security contributions, then the claim of the proponents that more jobs will be created can be supported.     

Conditioning as disintegration

Conditional probability distributions seem to have a bad reputation when it comes to rigorous treatment of conditioning. Technical arguments are published as manipulations of Radon–Nikodym derivatives, although we all secretly perform heuristic calculations using elementary definitions of conditional probabilities. In print, measurability and averaging properties substitute for intuitive ideas about random variables behaving like constants given particular conditioning information.
One way to engage in rigorous, guilt-free manipulation of conditional distributions is to treat them as disintegrating measures—families of probability measures concentrating on the level sets of a conditioning statistic. In this paper we present a little theory and a range of examples—from EM algorithms and the Neyman factorization, through Bayes theory and marginalization paradoxes—to suggest that disintegrations have both intuitive appeal and the rigor needed for many problems in mathematical statistics.     

Nonparametric efficiency analysis: A multivariate conditional quantile approach

This paper focuses on nonparametric efficiency analysis based on robust estimation of partial frontiers in a complete multivariate setup (multiple inputs and multiple outputs). It introduces α-quantile efficiency scores. A nonparametric estimator is proposed achieving strong consistency and asymptotic normality. Then if α increases to one as a function of the sample size we recover the properties of the FDH estimator. But our estimator is more robust to the perturbations in data, since it attains a finite gross-error sensitivity. Environmental variables can be introduced to evaluate efficiencies and a consistent estimator is proposed. Numerical examples illustrate the usefulness of the approach.