Purpose - This paper aims to provide insights into Arabic-Australian community attitudes regarding social innovation of a new shared model of accommodation for the 65+ age group to facilitate independent behavior within a shared living environment.Design/methodology/approach - A survey of 520 people of whom 65 per cent were Arabic speakers either by mother or second language. Survey responses were filtered to Arabic speakers and further analyzed to identify groups characterized by the latent attitudes underlying responses.Findings - The results confirmed the presence of two small groups representing in aggregate 13 per cent of sample variance who have positive attitudes toward 65+ age group shared accommodation for either themselves or their parents. These respondents focused on companionship and cultural factors rather than potential financial or medical benefits from the new model.Research limitations/implications - The application of an empirical Bayes methodology to the limited data in this research implicitly restricts the interpretation of the results to the Australian-Arabic community that was investigated.Practical implications - The results of this research provide a sound basis for private sector interest in exploring differentiated architectures and business models that will facilitate choices of shared accommodation by the Australian-Arabic 65+ year age group.Social implications - This finding aligns with increasing health and mobility more widely among the rapidly growing 65+ year old segment of the Australian population and with recent Australian Government restructuring of age care to introduce greater personal accountability for self-care.Originality/value - This research is original and important in setting future directions for expanding the richness of choice in Australian-Arabic community retirement living.

Mainstream computable general equilibrium analysis developed out of Lief Johansen's regional economic analysis based on the simultaneous settlement of commodity markets in quantity and price. The work of John von Neumann, Paul Samuelson, Wassily Leontief, Anne Carter, Michael Farrell and Thijs ten Raa has combined in an alternative bottom-up Integrated Assessment Model, which embodies Johansen attributes while exploiting the unique property of models having regions that trade and adjust to evolving natural advantages and environmental constraints through regional industry specialization. Such specialization has recently become a major focus in many nations seeking competitive niche business models in intermediate products and capital goods, which today comprise 70 per cent of the global supply chain. This research demonstrates a non-monetary or policy application of the Doctrine of Balanced Growth operates to equalize consumption growth at the policy nexus of international free-trade agreements and specialization of regional industry segments. Our knowledge of domestic industry policy and international trade policy is advanced by this demonstration that model results conform with a non-monetary Doctrine of Balanced Growth. This study is based on 2007 year data from the Global Trade Analysis Project.

Compiling, deploying and utilising large-scale databases that integrate environmental and economic data have traditionally been labour-and cost-intensive processes, hindered by the large amount of disparate and misaligned data that must be collected and harmonised. The Australian Industrial Ecology Virtual Laboratory (IELab) is a novel, collaborative approach to compiling large-scale environmentally extended multi-region input-output (MRIO) models.The utility of the IELab product is greatly enhanced by avoiding the need to lock in an MRIO structure at the time the MRIO system is developed. The IELab advances the idea of the "mother-daughter" construction principle, whereby a regionally and sectorally very detailed "mother" table is set up, from which "daughter" tables are derived to suit specific research questions. By introducing a third tier - the "root classification"-IELab users are able to define their own mother-MRIO configuration, at no additional cost in terms of data handling. Customised mother-MRIOs can then be built, which maximise disaggregation in aspects that are useful to a family of research questions.The second innovation in the IELab system is to provide a highly automated collaborative research platform in a cloud-computing environment greatly expediting workflows and making these computational benefits accessible to all users.Combining these two aspects realises many benefits. The collaborative nature of the IELab development project allows significant savings in resources. Timely deployment is possible by coupling automation procedures with the comprehensive input from multiple teams. User-defined MRIO tables, coupled with high performance computing, mean that MRIO analysis will be useful and accessible for a great many more research applications than would otherwise be possible. By ensuring that a common set of analytical tools such as for hybrid life-cycle assessment is adopted, the IELab will facilitate the harmonisation of fragmented, dispersed and misaligned raw data for the benefit of all interested parties. (C) 2014 Elsevier B.V. All rights reserved.

This research demonstrates a solution for the DICE 2007 integrated assessment model in the continuous domain through the use of a Runge-Kutta sampling technique for solving differential transcendental equations. The use of a savings ratio helper constraint was not required. It is shown that the introduction of a savings ratio constraint leads to a 12% underestimation of maximum atmospheric temperature rise. In addition, evidence of a savings ratio within economic data was unable to be confirmed using the equivalent proxy of an investment ratio and model selection techniques for mixed Gaussian probabilistic graphical models. However, evidence of a dilute intertemporal relationship between investment and an increase in production was detected. The results of this research support the use of Runge-Kutta sampling differential transcendental solvers with Chebyshev function outputs for continuous solutions in integrated assessment models without the requirement for helper constraints.

Extreme transcendental differential equations are found in many applications including geophysical climate change models. Solution of these systems in continuous time has only been feasible with the recent development of Runge−Kutta sampling transcendental differential equation solvers with Chebyshev function output such as Mathematica 9's NDSolve function. This paper presents the challenges and means of solving the widely used DICE 2007 integrated assessment model in continuous time. Application of the solution technique in a mobile policy tool is discussed.

Asset turnover has been used for approximately a century in corporate capital allocation. Capital expansion coefficients have been used in the Leontief Dynamic Model but the use of asset turnover ratios to regulating production growth in Computable General Equilibrium models has been limited. This research investigates the hypothesis that there is a causal relationship between productive assets and production of commodities. The hypothesis is tested in global economic data using static and chain probabilistic graphical model selection. It was found that the hypothesis is supported for a significant number of commodities. The confirmation of the hypothesis establishes that production to assets ratios for commodities are endogenous regulators of production growth.

The use of Computable General Equilibrium modelling in evidence-based policy requires an advanced policy making frame of reference, advanced understanding of neoclassical economics and advanced operations research capabilities. This paper examines developments in neoclassical economic models for the analysis of strategy and policy. Regions and industries have the ever-present challenge of building a future where production is competitive and employment is durable. In this context, the inhibitor effects of potential climate constraints on regional industries and bilateral trade is currently a topic of major concern to polity. Threats often bring opportunities and these are sometimes major disruptions to traditional industry structure. Therefore of equal interest to some policy makers are the strategic opportunities that a window of superior domestic productivity and resource expansiveness may bring to nations seeking a transformative boost in export performance. The Spatial Climate Economic Policy Tool for Regional Equilibria (Sceptre) is an intertemporal, multiregional general equilibrium model for investigating regional and industry strategies in the presence of global policies such as carbon emission constraints. In its simplest mode, Sceptre translates global climate policies to regional and commodity effects. This is achieved by bringing together traditional markets for commodities with new markets in carbon commodities. These new markets are emission permits trading and a technology function for carbon abatement and amelioration. A general equilibrium is settled by optimising a social welfare function, in the mode of a Negishi format, within a nonlinear economic-climate feedback loop. Both the technology function for carbon abatement and amelioration and the economic-climate feedback loop have precedent in William Nordhaus' DICE model. The social welfare function comprises regional economic expansion factors, which are developed in a multiregional context using a data envelopment or benchmarking technique successfully applied by Thjis ten Raa to single period national and bilateral models. In a novel intertemporal innovation, Sceptre draws together disciplines of economics and finance by substituting resource constraints with Dupont sales to asset ratios in order to dynamically link and mediate the stocks and flows of each commodity. This avoids the issue in Ramsey models that investment is merely an uncontrolled residual of production and consumption, and the issue in the Leontief Bmatrix approach that final industry assets are cannibalised. Regionally aggregated Make and Use matrices drawn from GTAP's Social Accounting Matrices are used in the underling economic model as regional-commodity production function tableaux. Outputs for policy

Biggs' Study Process Questionnaire is used to measure the constructive alignment of student choice with deep and shallow approaches to learning in established undergraduate and postgraduate engineering subjects designed for pull-learning, in contrast to push-teaching. Dividend output factors of increased student marks are established for a deep approach to learning and the inverse of a Shallow Approach to learning. Empirical Bayesian analysis comprising Exploratory Factor Analysis and Bayesian Confirmatory Strategies is used to deeply mine and draw inferences from relatively small sample sizes. This research confirms Biggs' suggestion that the tendency of education to erode towards Shallow Learning may be addressed through curriculum design that constructively aligns student choices with deep engagement. Students in subjects designed for pull-learning do appreciate the constructive alignment of their choices with deep engagement. Furthermore, there is a dividend payoff in marks for both deep engagement and the opposite of shallow engagement. The findings provide considerable optimism for the development of pull-learning techniques to increase the generic work-ready skills of graduate engineering students.

The use of Computable General Equilibrium modelling in evidence-based policy requires an advanced policy making frame of reference, advanced understanding of neoclassical economics and advanced operations research capabilities. This paper examines developments in the policy making frame of reference. The process of evidence-driven policy places importance on the validation of potential policies using models. At national, bilateral and multilateral levels, policy analysis has increasingly relied on neoclassical computable general equilibrium models having substantial precedence. Bayesian analysis suggests that a policy which survives a validation test using such a model has a much better chance of being successful than a policy that fails such a test. Yet the 2008-9 Global Financial Crisis demonstrated that policies verified with neoclassical models neither predicted the Global Financial Crisis nor were able to address it. Governments across the world used massive Keynesian stimulus to restabilise economies. Neoclassical models became much maligned within Keynesian and behavioural economics circles. This paper investigates the continuing role of neoclassical models in evidence-driven policy with reference to the deductivism of Sir Karl Popper and Thomas Kuhn, inductivism and the controversial objective theory of evidence. While policy making has always been messy, in recent decades policy makers may have succumbed to the human fallibility of justifying pragmatism with simplified ideological paradigms that inappropriately place over-reliance on neoclassical free market mathematical models because these models are self-reinforcing of the ideology. It is suggested that future policy making will be even messier, with policy makers placing less importance on such simplified paradigms and taking more responsibility for managing plurality in the political process. It is concluded that neoclassical models will continue to have a role in testing policies but those features of neoclassical models that led to the failures in understanding the Global Financial Crisis will need to be addressed. For example, to be relevant such models will need to close for both households and investment and be cognisant of distributional effects such as the sweep of income to various classes of citizens through wage and taxation policies.

The use of Computable General Equilibrium modelling in evidence-based policy requires an advanced policy making frame of reference, advanced understanding of neoclassical economics and advanced operations research capabilities. This paper examines developments in the advanced operations research capability of a modern generalised mathematical software platform. Intertemporal general equilibrium modelling has become feasible over recent decades due to the development of powerful computer software and hardware. Software for this purpose has traditionally been highly specialised in its ability to define optimisation problems, presolve, and submit the modified mathematical specification to industrial strength optimisation algorithms. In the last two years, general purpose mathematical software has achieved industrial strength. For example, Mathematica now provides interior point optimisation, a technology that has taken three decades to evolve from mathematical research into a general application. It is now possible to take advantage of the many other attributes of general purpose modelling suites, for example graphics for data visualisation that greatly enhance the execution of research and communication of results to policy makers. This paper outlines techniques for the application of Mathematica to data mining of the GTAP database and in using interior point optimisation for Computable General Equilibrium modelling.

The use of Computable General Equilibrium modelling in evidence-based policy requires an advanced policy making frame of reference, advanced understanding of neoclassical economics and advanced operations research capabilities. This paper examines developments in the policy making frame of reference. The process of evidence-driven policy places importance on the validation of potential policies using models. At national, bilateral and multilateral levels, policy analysis has increasingly relied on neoclassical computable general equilibrium models having substantial precedence. Bayesian analysis suggests that a policy which survives a validation test using such a model has a much better chance of being successful than a policy that fails such a test. Yet the 2008-9 Global Financial Crisis demonstrated that policies verified with neoclassical models neither predicted the Global Financial Crisis nor were able to address it. Governments across the world used massive Keynesian stimulus to restabilise economies. Neoclassical models became much maligned within Keynesian and behavioural economics circles. This paper investigates the continuing role of neoclassical models in evidence-driven policy with reference to the deductivism of Sir Karl Popper and Thomas Kuhn, inductivism and the controversial objective theory of evidence. While policy making has always been messy, in recent decades policy makers may have succumbed to the human fallibility of justifying pragmatism with simplified ideological paradigms that inappropriately place over-reliance on neoclassical free market mathematical models because these models are self-reinforcing of the ideology. It is suggested that future policy making will be even messier, with policy makers placing less importance on such simplified paradigms and taking more responsibility for managing plurality in the political process. It is concluded that neoclassical models will continue to have a role in testing policies but those features of neoclassical models that led to the failures in understanding the Global Financial Crisis will need to be addressed. For example, to be relevant such models will need to close for both households and investment and be cognisant of distributional effects such as the sweep of income to various classes of citizens through wage and taxation policies.

The use of Computable General Equilibrium modelling in evidence-based policy requires an advanced policy making frame of reference, advanced understanding of neoclassical economics and advanced operations research capabilities. This paper examines developments in the advanced operations research capability of a modern generalised mathematical software platform. Intertemporal general equilibrium modelling has become feasible over recent decades due to the development of powerful computer software and hardware. Software for this purpose has traditionally been highly specialised in its ability to define optimisation problems, presolve, and submit the modified mathematical specification to industrial strength optimisation algorithms. In the last two years, general purpose mathematical software has achieved industrial strength. For example, Mathematica now provides interior point optimisation, a technology that has taken three decades to evolve from mathematical research into a general application. It is now possible to take advantage of the many other attributes of general purpose modelling suites, for example graphics for data visualisation that greatly enhance the execution of research and communication of results to policy makers. This paper outlines techniques for the application of Mathematica to data mining of the GTAP database and in using interior point optimisation for Computable General Equilibrium modelling.