Taxation of multinational banks : using formulary apportionment to reflect economic reality

The taxation of multinational banks is currently governed by general principles of international tax. However, there are characteristics exclusive to multinational banks that may warrant consideration of a separate taxing regime, as the current system does not produce a result that accurately reflects the economic source of the income or the location of the economic activity. The suggested alternative is unitary taxation using global formulary apportionment.

Impacts of invasive plants on Australian rangelands

In Australia, the spread and dominance of non-native plant species has been identified as a serious threat to rangeland biodiversity and ecosystem functioning. Rangelands extend over 70% of Australia’s land mass or more than 6 million km2. These rangelands consist of a diverse set of ecosystems including grasslands, shrub-lands, and woodlands spanning numerous climatic zones, ranging from arid to mesic. Because of the high economic, social, and environmental values, sustainable management of these vast landscapes is critical for Australia’s future. More than 2 million people live in these areas and major industries are ranching, mining, and tourism. In terms of biodiversity values, 53 of 85 of Australia’s biogeographical regions and 5 of 15 identified biodiversity hotspots are found in rangelands.

Security constrained economic dispatch considering wind energy conversion systems

The available wind power is stochastic and requires appropriate tools in the OPF model for economic and reliable power system operation. This paper exhibit the OPF formulation with factors involved in the intermittency of wind power. Weibull distribution is adopted to find the stochastic wind speed and power distribution. The reserve requirement is evaluated based on the wind distribution and risk of under/over estimation of the wind power. In addition, the Wind Energy Conversion System (WECS) is represented by Doubly Fed Induction Generator (DFIG) based wind farms. The reactive power capability for DFIG based wind farm is also analyzed. The study is performed on IEEE-30 bus system with wind farm located at different buses and with different wind profiles. Also the reactive power capacity to be installed in the wind farm to maintain a satisfactory voltage profile under the various wind flow scenario is demonstrated.

A review of the effectiveness of speed control measures in roadwork zones

Noncompliance with speed limits is one of the major safety concerns in roadwork zones. Although numerous studies have attempted to evaluate the effectiveness of safety measures on speed limit compliance, many report inconsistent findings. This paper aims to review the effectiveness of four categories of roadwork zone speed control measures: Informational, Physical, Enforcement, and Educational measures. While informational measures (static signage, variable message signage) evidently have small to moderate effects on speed reduction, physical measures (rumble strips, optical speed bars) are found ineffective for transient and moving work zones. Enforcement measures (speed camera, police presence) have the greatest effects, while educational measures also have significant potential to improve public awareness of roadworker safety and to encourage slower speeds in work zones. Inadequate public understanding of roadwork risks and hazards, failure to notice signs, and poor appreciation of safety measures are the major causes of noncompliance with speed limits.

An elicitation of speeding behaviour beliefs in school zones in Australia

This elicitation study was designed to explore salient behavioural, normative, and control beliefs in accordance with the Theory Planned Behaviour (TPB) and in relation to drivers’ speeding behaviour in school zones. The study also explored mindfulness and habit as additional constructs in the TPB framework. The aim of this study was to identify those beliefs which influenced drivers’ speeding behaviour in school zones and thus gain greater insight into the motivating factors underpinning the behaviour which may inform interventions to reduce this behaviour. Seventeen Australian drivers participated in one of a series of focus group discussions. Overall, conceptual content analysis revealed some similar issues across the groups. In particular, highlighting the influence of behavioural and normative beliefs, there was much agreement that there were no real advantages to speeding in school zones with the behaviour considered dangerous and unacceptable and likely to also be regarded as such by important others. In addition, given the public concern about safety of school children, acknowledgment of such concern represented an important factor discouraging one’s likelihood of engaging in speeding in school zones (i.e., complying with the school zone speed limit). However, despite normative support not to speed, and the need to ensure children’s safety as an important factor discouraging speeding, the study also found that there was a tendency for drivers to report unintentionally speeding in a school zone. Instances of unintentional speeding were reported as occurring due to several reasons including a driver’s current affective state (e.g., more likely to speed in a school zone if they were in a bad mood), the extent to which they were familiar with the environment (i.e., more likely to drive mindlessly – on ‘autopilot’ - in more familiar contexts) and when feeling fatigued. The theoretical implications of including mindfulness and habit with TPB constructs and the practical implications in terms of suggested interventions are discussed.

Agronomic and economic evaluation of irrigation strategies on cotton lint yield in Australia

Cotton is one of the most important irrigated crops in subtropical Australia. In recent years, cotton production has been severely affected by the worst drought in recorded history, with the 2007–08 growing season recording the lowest average cotton yield in 30 years. The use of a crop simulation model to simulate the long-term temporal distribution of cotton yields under different levels of irrigation and the marginal value for each unit of water applied is important in determining the economic feasibility of current irrigation practices. The objectives of this study were to: (i) evaluate the CROPGRO-Cotton simulation model for studying crop growth under deficit irrigation scenarios across ten locations in New South Wales (NSW) and Queensland (Qld); (ii) evaluate agronomic and economic responses to water inputs across the ten locations; and (iii) determine the economically optimal irrigation level. The CROPGRO-Cotton simulation model was evaluated using 2 years of experimental data collected at Kingsthorpe, Qld. The model was further evaluated using data from nine locations between northern NSW and southern Qld. Long-term simulations were based on the prevalent furrowirrigation practice of refilling the soil profile when the plant -available soil water content is<50%. The model closely estimated lint yield for all locations evaluated. Our results showed that the amounts of water needed to maximise profit and maximise yield are different, which has economic and environmental implications. Irrigation needed to maximise profits varied with both agronomic and economic factors, which can be quite variable with season and location. Therefore, better tools and information that consider the agronomic and economic implications of irrigation decisions need to be developed and made available to growers.

Increasing disaster resilience of people and property through fostering collaboration in coastal high hazard zones

As evidenced with the 2011 floods the state of Queensland in Australia is quite vulnerable to this kind of disaster. Climate change will increase the frequency and magnitude of such events and will have a variety of other impacts. To deal with these governments at all levels need to be prepared and work together. Since most of the population of the state is located in the coastal areas and these areas are more vulnerable to the impacts of climate change this paper examines climate change adaptation efforts in coastal Queensland. The paper is part of a more comprehensive project which looks at the critical linkages between land use and transport planning in coastal Queensland, especially in light of increased frequencies of cyclonic activity and other impacts associated with climate change. The aim is improving coordination between local and state government in addressing land use and transport planning in coastal high hazard areas. By increasing the ability of local governments and state agencies to coordinate planning activities, we can help adapt to impacts of climate change. Towards that end, we will look at the ways that these groups currently interact, especially with regard to issues involving uncertainty related to climate change impacts. Through surveys and interviews of Queensland coastal local governments and state level planning agencies on how they coordinate their planning activities at different levels as well as how much they take into account the linkage of transportation and land use we aim to identify the weaknesses of the current planning system in responding to the challenges of climate change adaptation. The project will identify opportunities for improving the ways we plan and coordinate planning, and make recommendations to improve resilience in advance of disasters so as to help speed up recovery when they occur.

Maintenance optimisation of a multi-state series-parallel system considering economic dependence and state-dependent inspection intervals

This paper presents a maintenance optimisation method for a multi-state series-parallel system considering economic dependence and state-dependent inspection intervals. The objective function considered in the paper is the average revenue per unit time calculated based on the semi-regenerative theory and the universal generating function (UGF). A new algorithm using the stochastic ordering is also developed in this paper to reduce the search space of maintenance strategies and to enhance the efficiency of optimisation algorithms. A numerical simulation is presented in the study to evaluate the efficiency of the proposed maintenance strategy and optimisation algorithms. The simulation result reveals that maintenance strategies with opportunistic maintenance and state-dependent inspection intervals are more cost-effective when the influence of economic dependence and inspection cost is significant. The study further demonstrates that the optimisation algorithm proposed in this paper has higher computational efficiency than the commonly employed heuristic algorithms.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Networking of shear zones at the brittle-to-viscous transition (Cap de Creus, NE Spain)

A crustal-scale shear zone network at the fossil brittle-to-viscous transition exposed at Cap de Creus, NE Spain evolved by coeval fracturing and viscous, mylonitic overprinting of an existing foliation. Initial fracturing led to mylonitic shearing as rock softened in ductilely deformed zones surrounding the fractures. Mylonitic shear zones widened by lateral branching of fractures from these shear zones and by synthetic rotation of the existing foliation between the fractures and shear zones. Shear zones lengthened by a combination of fracturing and mylonitic shearing in front of the shear zone tips. Shear zones interconnected along and across their shearing planes, separating rhomb-shaped lozenges of less deformed rock. Lozenges were subsequently incorporated into the mylonitic shear zones by widening in the manner described above. In this way, deformation became homogeneous on the scale of initial fracturing (metre- to decametre-scale). In contrast, the shear zone network represents localisation of strain on a decametre-length scale. The strength of the continental crust at the time of coeval fracturing and viscous shearing is inferred to have decreased with time and strain, as fracturing evolved to mylonitic shearing, and as the shear zones coalesced to form a through-going network subparallel to the shearing plane. Crustal strength must therefore be considered as strain- and scale-dependent.

Why do policy decision-makers opt for command and control environmental regulation? An economic analysis with special reference to Sri Lanka

This chapter examines why policy decision-makers opt for command and control environmental regulation despite the availability of a plethora of market-based instruments which are more efficient and cost-effective. Interestingly, Sri Lanka has adopted a wholly command and control system, during both the pre and post liberalisation economic policies. This chapter first examines the merits and demerits of command and control and market-based approaches and then looks at Sri Lanka’s extensive environmental regulatory framework. The chapter then examines the likely reasons as to why the country has gone down the path of inflexible regulatory measures and has become entrenched in them. The various hypotheses are discussed and empirical evidence is provided. The chapter also discusses the consequences of an environmentally slack economy and policy implications stemming from adopting a wholly regulatory approach. The chapter concludes with a discussion of the main results.

Economic growth and inequality patterns in the presence of costly technology adoption and uncertainty

We develop a stochastic endogenous growth model to explain the diversity in growth and inequality patterns and the non-convergence of incomes in transitional economies where an underdeveloped financial sector imposes an implicit, fixed cost on the diversification of idiosyncratic risk. In the model endogenous growth occurs through physical and human capital deepening, with the latter being the more dominant element. We interpret the fixed cost as a ‘learning by doing’ cost for entrepreneurs who undertake risk in the absence of well developed financial markets and institutions that help diversify such risk. As such, this cost may be interpreted as the implicit returns foregone due to the lack of diversification opportunities that would otherwise have been available, had such institutions been present. The analytical and numerical results of the model suggest three growth outcomes depending on the productivity differences between the projects and the fixed cost associated with the more productive project. We label these outcomes as poverty trap, dual economy and balanced growth. Further analysis of these three outcomes highlights the existence of a diversity within diversity. Specifically, within the ‘poverty trap’ and ‘dual economy’ scenarios growth and inequality patterns differ, depending on the initial conditions. This additional diversity allows the model to capture a richer range of outcomes that are consistent with the empirical experience of several transitional economies.