834 resultados para Users of Financial Statements


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Audit report on Iowa Public Television for the year ended June 30, 2009

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The new edition of this widely used and respected introductory accounting textbook continues to provide students and academics with a well written and accessible resource, with ample illustrations and applications to business for a first study of accounting. The text effectively maintains the balance between a 'user' and 'preparer' perspective by integrating real financial information and business decisions throughout. Through the use of real company information and financial statements students will quickly appreciate the use and users of accounting information. The textbook clearly outlines to students how a financial statement - such as a balance sheet, income statement, cash flow statement - communicates the financing, operating, and investing activities of a business. The text builds a strong conceptual understanding and develops skills in the application of accounting principles and techniques, providing students with a solid foundation for further studies in accounting. The integral role of financial statements for decision making is also emphasised in this text and is reinforced throughout by the Decision Toolkit in each chapter. Students are provided with an extensive set of tools necessary to make business decisions based on financial information.

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Data were collected from 269 Australian primary school children in grades 3 to 7. Self-report questionnaires measuring students' perceptions of the frequency of positive and negative statements directed to them by their teacher, their positive and negative self-talk; and their reading, mathematics and learning self-concepts were administered. Positive statements made by teachers were found to be directly related to positive self-talk and to maths and learning self-concepts. Teachers' positive statements were also indirectly related to reading self-concept through positive self-talk. Negative statements made by teachers were not predictive of self-talk or self-concepts for the total sample but were predictive of maths self-concept for girls and negative self-talk for boys. Implications for teachers and educational psychologists are discussed.

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"This book investigates the origins and implications of the securitization crisis, described by the chief executive of ANZ as a "financial services bloodbath". Based on extensive interviews it offers an integrated series of case studies drawn from the United States, the United Kingdom and Australia. A central purpose is to not only chart what went wrong with the investment houses and why the regulatory systems failed, but also provide policy guidance. The book therefore combines the empirical with the normative. In so doing, it provides a route map to navigate one of the most significant financial and regulatory failures in modern times."

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Practitioners and academics often assume that investments in innovation will lead to organizational improvements. However, previous research has often shown that implemented innovations fail to realise these potential improvements. On the other hand, organisation, perhaps, has been growing and productive because of the innovation, but traditional measurements have failed to capture that growth. In order to help organizations capture their innovation performance effectively, this study examined the organizations which employ different types of performance measurement and their perception of innovation effectiveness.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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Asset management in local government is an emerging discipline and over a decade has become a crucial aspect towards a more efficient and effective organisation. One crucial feature in the public asset management is performance measurement toward the public real estates. This measurement critically at the important component of public wealth and seeks to apply a standard of economic efficiency and effective organisational management especially in such global financial crisis condition. This paper aims to identify global economic crisis effect and proposes alternative solution for local governments to softening the impact of the crisis to the local governments organisation. This study found that the most suitable solution for local government to solve the global economic crisis in Indonesia is application of performance measurement in its asset management. Thus, it is important to develop performance measurement system in local government asset management process. This study provides suggestions from published documents and literatures. The paper also discusses the elements of public real estate performance measurement. The measurement of performance has become an essential component of the strategic thinking of assets owners and managers. Without having a formal measurement system for performance, it is difficult to plan, control and improve local government real estate management system. A close look at best practices in public sectors reveals that in most cases these practices were transferred from private sector reals estate management under the direction of real estate experts retained by government. One of the most significant advances in government property performance measurement resulted from recognition that the methodology used by private sector, non real estate corporations for managing their real property offered a valuable prototype for local governments. In general, there are two approaches most frequently used to measure performance of public organisations. Those are subjective and objective measures. Finally, findings from this study provides useful input for the local government policy makers, scholars and asset management practitioners to establish a public real estate performance measurement system toward more efficient and effective local governments in managing their assets as well as increasing public services quality in order to soften the impact of global financial crisis.

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In 2008, a three-year pilot ‘pay for performance’ (P4P) program, known as ‘Clinical Practice Improvement Payment’ (CPIP) was introduced into Queensland Health (QHealth). QHealth is a large public health sector provider of acute, community, and public health services in Queensland, Australia. The organisation has recently embarked on a significant reform agenda including a review of existing funding arrangements (Duckett et al., 2008). Partly in response to this reform agenda, a casemix funding model has been implemented to reconnect health care funding with outcomes. CPIP was conceptualised as a performance-based scheme that rewarded quality with financial incentives. This is the first time such a scheme has been implemented into the public health sector in Australia with a focus on rewarding quality, and it is unique in that it has a large state-wide focus and includes 15 Districts. CPIP initially targeted five acute and community clinical areas including Mental Health, Discharge Medication, Emergency Department, Chronic Obstructive Pulmonary Disease, and Stroke. The CPIP scheme was designed around key concepts including the identification of clinical indicators that met the set criteria of: high disease burden, a well defined single diagnostic group or intervention, significant variations in clinical outcomes and/or practices, a good evidence, and clinician control and support (Ward, Daniels, Walker & Duckett, 2007). This evaluative research targeted Phase One of implementation of the CPIP scheme from January 2008 to March 2009. A formative evaluation utilising a mixed methodology and complementarity analysis was undertaken. The research involved three research questions and aimed to determine the knowledge, understanding, and attitudes of clinicians; identify improvements to the design, administration, and monitoring of CPIP; and determine the financial and economic costs of the scheme. Three key studies were undertaken to ascertain responses to the key research questions. Firstly, a survey of clinicians was undertaken to examine levels of knowledge and understanding and their attitudes to the scheme. Secondly, the study sought to apply Statistical Process Control (SPC) to the process indicators to assess if this enhanced the scheme and a third study examined a simple economic cost analysis. The CPIP Survey of clinicians elicited 192 clinician respondents. Over 70% of these respondents were supportive of the continuation of the CPIP scheme. This finding was also supported by the results of a quantitative altitude survey that identified positive attitudes in 6 of the 7 domains-including impact, awareness and understanding and clinical relevance, all being scored positive across the combined respondent group. SPC as a trending tool may play an important role in the early identification of indicator weakness for the CPIP scheme. This evaluative research study supports a previously identified need in the literature for a phased introduction of Pay for Performance (P4P) type programs. It further highlights the value of undertaking a formal risk assessment of clinician, management, and systemic levels of literacy and competency with measurement and monitoring of quality prior to a phased implementation. This phasing can then be guided by a P4P Design Variable Matrix which provides a selection of program design options such as indicator target and payment mechanisms. It became evident that a clear process is required to standardise how clinical indicators evolve over time and direct movement towards more rigorous ‘pay for performance’ targets and the development of an optimal funding model. Use of this matrix will enable the scheme to mature and build the literacy and competency of clinicians and the organisation as implementation progresses. Furthermore, the research identified that CPIP created a spotlight on clinical indicators and incentive payments of over five million from a potential ten million was secured across the five clinical areas in the first 15 months of the scheme. This indicates that quality was rewarded in the new QHealth funding model, and despite issues being identified with the payment mechanism, funding was distributed. The economic model used identified a relative low cost of reporting (under $8,000) as opposed to funds secured of over $300,000 for mental health as an example. Movement to a full cost effectiveness study of CPIP is supported. Overall the introduction of the CPIP scheme into QHealth has been a positive and effective strategy for engaging clinicians in quality and has been the catalyst for the identification and monitoring of valuable clinical process indicators. This research has highlighted that clinicians are supportive of the scheme in general; however, there are some significant risks that include the functioning of the CPIP payment mechanism. Given clinician support for the use of a pay–for-performance methodology in QHealth, the CPIP scheme has the potential to be a powerful addition to a multi-faceted suite of quality improvement initiatives within QHealth.

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Generic, flexible social media spaces such as Facebook and Twitter constitute an increasingly important element in our overall media repertoires. They provide a technological basis for instant and world-wide, ad hoc, many-to-many communication, and their effect on global communication patterns has already been highlighted. The short-messaging platform Twitter, for example, caters for uses ranging from interpersonal and quasi-private phatic exchanges to ‘ambient journalism’: ad hoc new reporting and dissemination as major events break. Many such uses have themselves emerged through user-driven processes: even standard Twitter conventions such as the @reply (to publicly address a fellow user) or the #hashtag(to collect related messages in an easily accessible space) are user inventions, in fact, and were incorporated into Twitter’s own infrastructure only subsequently. This demonstrates the substantial potential of social, user-led innovation in social media spaces.

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There has never been a better time to strengthen financial reporting in Fiji. With increased interest shown by prospective companies in capital market participation, the pressing problems in the public sector reporting and accountability and global emphasis on the increasing need to strengthen the corporate governance structure, this is perhaps the opportune time to consider the potential of XBRL.