996 resultados para working paper


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This discussion paper is intended to provide background material for the workshop organised by Queensland University Technology (QUT) on 17 October 2014. The overall purpose of the workshop is to better understand the relationship between the precautionary principle and endangered species management in Australia. In particular, we are looking for real life examples (or hypotheticals) of where the principle is (or is not) being applied in relation to Australia’s endangered species. A wide variety of participants have been invited to the workshop including scientists, representatives of NGOs, lawyers and academics. Whilst some very general information is outlined below, we encourage all participants to bring their own thoughts on how the precautionary principle should operate and to reflect on examples of where you have seen it work (or not work) in Australia. The sharing of your own case studies is thus encouraged.

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With organisations facing significant challenges to remain competitive, Business Process Improvement (BPI) initiatives are often conducted to improve the efficiency and effectiveness of their business processes, focussing on time, cost, and quality improvements. Event logs which contain a detailed record of business operations over a certain time period, recorded by an organisation's information systems, are the first step towards initiating evidence-based BPI activities. Given an (original) event log as a starting point, an approach to explore better ways to execute a business process was developed, resulting in an improved (perturbed) event log. Identifying the differences between the original event log and the perturbed event log can provide valuable insights, helping organisations to improve their processes. However, there is a lack of automated techniques to detect the differences between two event logs. Therefore, this research aims to develop visualisation techniques to provide targeted analysis of resource reallocation and activity rescheduling. The differences between two event logs are first identified. The changes between the two event logs are conceptualised and realised with a number of visualisations. With the proposed visualisations, analysts will then be able to identify the changes related to resource and time, resulting in a more efficient business process. Ultimately, analysts can make use of this comparative information to initiate evidence-based BPI activities.

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A model based on the cluster process representation of the self-exciting process model in White and Porter 2013 and Ruggeri and Soyer 2008is derived to allow for variation in the excitation effects for terrorist events in a self-exciting or cluster process model. The details of the model derivation and implementation are given and applied to data from the Global Terrorism Database from 2000–2012. Results are discussed in terms of practical interpretation along with implications for a theoretical model paralleling existing criminological theory.

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The aim of this manual is to provide a practical guide to the Plant Breeder's Rights Act 1994 (Cth). It is a resource of information about the legislation, its administration, and its operation. This commentary is intended to assist plant breeders, scientific researchers, and business managers who want to make a more effective use of the Plant Breeder's Rights Act 1994 (Cth) in the management and commercialisation of their intellectual property rights. It is also designed to enhance the understanding of the legislation among lawyers, patent attorneys, qualified persons, and policy-makers.

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In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the semi-automatic approximate Bayesian computation (ABC) summary statistics are selected. After a pilot run of ABC, the likelihood-free parametric bootstrap approach requires very few model simulations to produce an approximate posterior, which can be a useful approximation in its own right. An alternative is to use this approximation as a proposal distribution in ABC algorithms to make them more efficient. In this paper, the parametric bootstrap approximation is used to form the initial importance distribution for the sequential Monte Carlo and the ABC importance and rejection sampling algorithms. The new approach is illustrated through a simulation study of the univariate g-and- k quantile distribution, and is used to infer parameter values of a stochastic model describing expanding melanoma cell colonies.

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Multinational financial institutions (MNFIs) play a significant role in financing the activities of their clients in developing nations. Consistent with the ‘follow-the-customer’ phenomenon which explains financial institution expansion, these entities are increasingly profiting from activities associated with this growing market. However, not only are MNFIs persistent users of tax havens, but also, more than other industries, have the opportunity to reduce tax through transfer pricing measures. This paper establishes a case for an industry-specific adoption of unitary taxation with formulary apportionment as a viable alternative to the current regime. In doing so, it considers the practicalities of implementing this by examining both definitional issues and possible formulas for MNFIs. This paper argues that, while there would be implementation difficulties to overcome, the current domestic models of formulary apportionment provide important guidance as to how the unitary business and business activities of MNFIs should be defined, as well as the factors that should be included in an allocation formula, and the appropriate weighting. This paper concludes that unitary taxation with formulary apportionment is a viable industry-specific alternative for MNFIs.

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Developed economies are moving from an economy of corporations to an economy of people. More than ever, people produce and share value amongst themselves, and create value for corporations through co-creation and by sharing their data. This data remains in the hands of corporations and governments, but people want to regain control. Digital identity 3.0 gives people that control, and much more. In this paper we describe a concept for a digital identity platform that substantially goes beyond common concepts providing authentication services. Instead, the notion of digital identity 3.0 empowers people to decide who creates, updates, reads and deletes their data, and to bring their own data into interactions with organisations, governments and peers. To the extent that the user allows, this data is updated and expanded based on automatic, integrated and predictive learning, enabling trusted third party providers (e.g., retailers, banks, public sector) to proactively provide services. Consumers can also add to their digital identity desired meta-data and attribute values allowing them to design their own personal data record and to facilitate individualised experiences. We discuss the essential features of digital identity 3.0, reflect on relevant stakeholders and outline possible usage scenarios in selected industries.

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A discussion of the question of context, its boundaries and limitations in educational research - set against the backdrop of the Wittgenstein/Popper debate.

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A longitudinal qualitative study was conducted with CEOs of 12 fundraising organisations across Australia to answer the question - how mights a change in the CEO's fundraising knowledge improve fundraising activity and outcomes for their organisation? The CEOs along with the inaugural Australian Grantmaker of the Year, Caitriona Fay from Perpetual and lead researcher Dr Wendy Scaife travelled to San Antonio, Texas, USA to attend the annual Association of Fundraising Professionals (AFP) conference in March 2014. Participants identified five main success factors for such group learning initiatives about fundraising: - Getting away from the day to day business of running the organisation - Informal, social time to debrief and get to know others - Diversity of organisations whereby no one was in direct competition to others - Commitment, openness and willingness of individuals to participate - Group facilitation This research has been supported by the Perpetual Foundation – Trustees Endowment, The Edward Corbould Charitable Trust, and the Samuel and Eileen Gluyas Charitable Trust under the management of Perpetual Trustee Company Ltd.

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Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

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Worldwide, no fewer than 50 million people a year are now fleeing dangerous and often life threatening situations in their countries of origin (UNHCR, 2014c). As one part of this movement, thousands risk journeys through dangerous waters hoping to obtain asylum in Australia. However, Australian Government policies adopted since 2013 aim to ensure that no asylum seeker nor any of the 3,500 detainees held in offshore detention centres will ever be settled on the mainland. To this has now been added a declaration that none of the recent refugees or 6200 asylum seekers waiting in Indonesia in centres run by the United Nations High Commissioner for Refugees (UNHCR) will gain entry (Whyte, 2014a). These immigration policies differ dramatically from those adopted in earlier decades that produced the country’s decidedly multicultural identity. This article reviews these changing perspectives of Australian governments and communities within the context of international obligations and expectations; the experiences of those directly involved in border policing practices and in detention centres; and the attitudes of national media. Relations and conflicts among the interests of the different parties are discussed and the scope for less punitive responses to the plight of asylum seekers is examined. The authors then focus on alternative processes to better address the interests and objectives of legitimately interested parties by processes which successively examine, optimise and reconcile the concerns of each. In so doing, they aim to demonstrate that such methods of sequential problem solving can respond effectively to the multiple concerns of the many significant stakeholders involved in increasingly significant global issues, whereas recourse to such single-goal, top-down programs as are expressed in the government’s current determination to “Stop the boats” at all costs are unlikely to prove sustainable.

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This paper empirically examines the effect of current tax policy on home ownership, specifically looking at how developer contributions impact house prices. Developer contributions are a commonly used mechanism for local governments to pay for new urban infrastructure. This research applies a hedonic house price model to 4,699 new and 25,053 existing house sales in Brisbane from 2005 to 2011. The findings of is research are consistent with international studies that support the proposition that developer contributions are over passed. This study has provided evidence that suggest developer contributions are over passed to both new and existing homes in the order of around 400%. These findings suggest that developer contributions are thus a significant contributor to increasing house prices, reduced housing supply and are thus an inefficient and inequitable tax. By testing this effect on both new and existing homes, this research provides evidence in support of the proposition that not only are developer contributions over passed to new home buyers but also to buyers of existing homes. Thus the price inflationary effect of these developer contributions are being felt by all home buyers across the community, resulting in increased mortgage repayments of close to $1,000 per month in Australia. This is the first study to empirically examine the impact of developer contributions on house prices in Australia. These results are important as they inform governments on the outcomes of current tax policy on home ownership, providing the first evidence of its kind in Australia. This is an important contribution to the tax reform agenda in Australia.

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This submission addresses the problem of housing price inflation, the chronic under-supply of new housing stock, and the resultant decline in housing affordability for low and middle income households. It specifically focusses on the supply of medium density housing (multi-unit development) in Melbourne, although we believe that the observations made about housing in supply in Melbourne are relevant in other urban centres and to other types of housing supply. In terms of medium density housing (MDH) our concern also extends to the poor quality and design. Why the market tends to deliver generic apartments of poor quality and design which are uncompetitive with lower density housing and amenity despite planning objectives, and how this apparently intractable problem can be overcome is the topic of this submission...

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Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.