The objective of this study is to introduce a more refined methodological approach for signalling corporate collapse. The proposed methodological approach provides informed stakeholders in a corporation with a tool that would help them signal impending collapse with a higher degree of accuracy than the existing mainstream methodology. By doing so, the proposed methodological approach helps stakeholders take appropriate measures, if possible, to save their company from collapse. The motivation behind this study emanates from a need in the literature in relation to coming up with a new methodological approach that is superior to what is available. For example, Jones and Hensher (2004), one of the most recent studies in the field, stated that over the past three decades there has been a conspicuous absence of modelling innovation in the literature on financial distress prediction, as well as a failure to keep abreast of important methodological developments emerging in other fields of the social sciences. Specifically, this study introduces a new ratio-based multivariate methodological approach for signalling corporate collapse, called Multi-Level Modelling (MLM). Moreover, this study demonstrated that MLM provides informed stakeholders in a corporation with a tool that would help them signal impending collapse with a higher degree of accuracy than Multiple Discriminant Analysis (MDA), which is the mainstream benchmark methodological approach. By doing so, MLM helps stakeholders take appropriate measures, if possible, to save their company from collapse. The empirical results depicted the superiority of MLM over MDA. MLM generated better overall predictive power and dramatically reduced the occurrence of Type I error (classifying a collapsed company as non-collapsed). Moreover, MLM achieved those results while at the same time capturing variations in industry sectors among the data sample of companies. This is something that MDA was not capable of.

To this point in time humanity has successfully responded to the challenges to its existence. A viewpoint becoming widespread is that humanity will have to respond to even greater challenges to its existence in the future. If adequate responses are not formulated to these emerging challenges then a dystopian future for humanity is a strong possibility. While experience can teach us how to act in the future it is the express intent of this research that we should not have to experience dystopia in order to learn how to prevent it. The innate human capacity for foresight has played a pivotal role in responding to past challenges, however, a more extensive form of foresight will need to be developed to respond to these future challenges. That form of foresight will need to be both individual and social in nature. Part I of this thesis generates an original theory of how foresight could develop in individuals beyond our innate capacities. The theory argues that foresight ca- pacities develop through the expansion of individual consciousness, particularly the individual's sense of `self'. The theory is synthesised from the work of a num- ber of psychological researchers including Jean Piaget, Jane Loevinger, Lawrence Kohlberg, Clare Graves, Susan Cook-Greuter and Ken Wilber. Part II is a two year study of students undertaking a postgraduate course in strategic foresight. The study is utilised to add preliminary empirical support to the theory proposed in Part I. Part III integrates the previous two parts to further elaborate the attributes and dynamics of individual foresight development before describing how social foresight capacity can emerge from individual development. Expanded individual and so- cial foresight capacities are achievable, but cannot be assumed. The contribution of this thesis is to give a theoretical base to such development and to outline fur- ther research. The development of individual foresight and the emergence of social expressions of foresight can offer preferable, and not dystopian, futures for both current and future generations.

隨著社會、經濟環境的變遷，使用者對資訊的需求日切，鑑於資訊的時效性，證管會在民國八十年度規定，公開發行公司應建立書面預算制度，按月編製現金、生產、銷售及資本預算，以為編製財務預測之參考。應證管會的要求，凡上市（櫃）公司募集與發行轉換公司債、現金增資，將申請上市（櫃）或公司自願，此四種情況，皆應附送財務預測報告（經會計師核閱）及有關文件。 　　本研究旨在分析目前國內上市公司，發佈經會計師核閱的財務預測，其對實際營業淨利及稅前淨利之準確性如何及何種因素影響其準確性。並分別以郵寄問卷調查方式蒐集資料，再以統計方法進行分析，了解財務預測資訊對我國機構投資者與企業財務主管的決策影響程度；會計師、證管會稽核人員及證券交易所上市部審查人員對財務預測實用性的看法。 　　分析結果顯示，目前所採行的預測制度，經會計師核閱，對決策有重要幫助，但由於許多外在環境影響及現行揭露預測規定，造成核閱者、編製者與閱表者皆不滿意現行之制度，且不確定（或不知道）企業公告的財務預測資訊有無其價值！

Demographic changes and economic growth are inextricably linked. However, the complex role of demographic system, specifically its temporal features have not been treated with rigor till recently. This dissertation undertakes such an attempt to explain cross-country growth variations and focuses on longterm growth projections by explicitly treating demographic system in a stochastic shocks framework. We exploit the temporal characteristics of demographic system to shed light on its evolution, study its complex interaction with economic system and analyze the long-run effect on economic growth/development. The dissertation contains four chapters. After outlining the motivation of the thesis and an overview of the chapter scheme in the first chapter, we investigate in Chapter 2 how the effects of demographic components viz., age specific population have changed over the decades. Following the standard practice of assuming `stationary' features of population growth, we first evaluate and extend the popular empirical economic growth models. We find that decadal changes have brought forth variations in economic growth of developed and developing economies. We argue that accounting for temporal features of the demographic and economic growth system would provide clear insights into persistent growth fluctuations. In Chapter 3 we develop a new mechanism to characterize stochastic nature of demographic shocks in which population series with large temporal dimension is assumed to be governed by certain degree of stochastic shocks. By doing so, the conventional `stationary' assumption underlying the current theoretical and empirical exploration is relaxed and more dynamic information about the persistence of shocks is accommodated in the economic growth models. To this end, we first provide an analytical framework to show that long-memory shocks in demographic age structure or population might induce long-memory in economic growth. An empirical illustration of both developed and developing countries is carried out to demonstrate that population age structure in these countries are characterized by long-memory. The causality of stochastic demographic shocks' influence and economic growth (and the converse) is also examined. Following the theoretical development and empirical illustration in Chapter 3, in Chapter 4 we propose to forecast total and age-structured population employing fractionally integrated ARMA (in short, ARFIMA) technique. The conventional methods of population forecasting is discussed in this chapter evaluating the advantages and potential weaknesses of these methods. Our approach to population forecasting can be considered as a shift from the conventional `low, medium, and high' variant and the recently used ARMA projections (assuming stationarity or first difference stationarity of aggregate population) and is a departure from the stochastic population forecast based on Leslie matrix as used in the extant population forecasting literature. In Chapter 5 we incorporate the memory properties of demographic age- distribution to forecast Gross Domestic Product (or National income) of some developed and developing countries. We relax the stationary age-structure and population growth assumption in the model while performing long term income projections. We argue that the growth of total age-structured population need not be stationary and that any degree of stochastic shocks in these series can affect forecasting performance. Given that a long-memory panel method is yet to be comprehensively built for forecasting, we perform forecast of demography-based income in the univariate context assuming a stochastic long-memory process for age-structured population growth. Finally, Chapter 6 summarizes the main findings of the thesis and outlines some possible directions for further research. / Les changements démographiques et la croissance économique sont intimement liées. Cependant, le complexe rôle du système démographique, particulièrement son aspect temporel, n'a pas encore été analysé avec rigueur jusqu'aujourd'hui. Cette dissertation tente d'aborder cette question afin d'expliquer les changements de croissance des pays. Elle insiste particulièrement sur les projections de croissance de long terme en traitant explicitement les systèmes démographiques dans une structure de chocs stochastiques. Nous exploitons les caractéristiques temporelles des systèmes démographiques pour analyser leur évolution, étudier sa complexe interaction avec le système économique ainsi que les effets de long terme sur la croissance économique. Dans le chapitre 2, nous nous intéressons sur les effets des composantes démographiques , plus précisément comment l'âge d'une population spécifique a changé avec le temps. Suivant la pratique standard qui suppose une « stationnarité » de la croissance de la population, nous évaluons et étendons les modèles empiriques populaires de croissance économique. Nous trouvons que les changements décennaux ont apporté quatre changements dans la croissance économique des pays aussi bien développés qu'en développement. Nous montrons que le fait de tenir compte de l'aspect temporel des systèmes de croissance économique et démographique améliore les résultats sur la persistance des fluctuations de la croissance. Dans le chapitre 3, nous développons un nouveau mécanisme pour caractériser la nature stochastique des chocs démographiques dans laquelle les séries de population avec une large dimension temporelle sont supposées régies par un certain nombre de chocs stochastiques. En procédant de cette manière, la supposition conventionnelle de « stationnarité » qui sous-tend l'exploration théorique et empirique courante est relâchée et beaucoup plus d'informations sur la persistance des chocs sont données dans les modèles de croissance économique. Dans la croissance économique endogène avec un changement endogène de population, ce chapitre construit un modèle « long-memory » de population et de ses composantes (structure par âges) pour montrer les effets des changements démographiques sur les économies tant développées qu'en développement. Pour ce faire, nous donnons d'abord une formulation théorique pour montrer que les chocs « long-memory » dans la structure démographique de la population peut induire une croissance. Une illustration empirique est développée pour montrer que la structure de la population est caractérisée de « long-memory ». Suite au développement théorique et à l'illustration empirique du chapitre 3, le chapitre 4 propose une prévision de la population totale et de la structure démographique en employant de manière fractionnée la technique intégrée ARMA ( ARFIMA en bref). Les méthodes conventionnelles de prévision de la population sont discutées dans ce chapitre valuant les avantages et les faiblesses potentielles de ces méthodes. Notre approche peut être considérée comme un changement de la variante de la méthode conventionnelle « faible, moyenne et élevée » par rapport à la récente projection ARIMA utilisée récemment (qui suppose stationnarité ou différence première de la population agrégée). De plus, notre approche est un départ de la prévision de la population stochastique basée sur la matrice de Leslie. Nous avons aussi examiné un départ de la prévision stochastique basée sur la matrice de Leslie. Dans ce chapitre, nous avons aussi analysé pourquoi les techniques de prévision en démographie n'ont pas beaucoup évolué alors que les méthodes ne sont pas restées si traditionnelles. Dans le chapitre 5, nous incorporons les propriétés démographiques « memory » âge - distribution pour prévoir le Produit Intérieur Brut (ou revenu national) de quelques économies développées et en développement. Nous relâchons l'hypothèse de stationnarité âge-structure et croissance de la population dans le modèle en faisant les projections du revenu de long terme. Nous montrons que la croissance de la population totale n'a pas besoin d'être stationnaire et que tout degré de chocs stochastiques dans ces séries peut affecter la performance de prévision. Etant donné que la méthode de panel “long memory” est encore à construire pour une bonne prévision, nous faisons une prévision du revenu basée sur la démographie dans un contexte uni varié qui suppose une procédure stochastique « long- memory » pour une croissance de la population structurée suivant l'âge. Finalement, le chapitre 6 résume les resultants principaux de la thèse et montre quelques directions possibles pour des recherches futures.

Thesis (M.A.)--Ohio University, June, 2006. / Title from PDF t.p. Includes bibliographical references (leaves 67-69)

Thesis (Ph. D.)--University of Rhode Island, 2005. / Typescript. Includes bibliographical references (v. 2: leaves 582-593).

Thesis (Ph. D.)--Texas State University-San Marcos, 2006. / Vita. Appendices: leaves 119-142. Includes bibliographical references (leaves 143-147).

This study examines the dynamics and predictability of the mesoscale convective vortex (MCV) event of 10-13 June 2003 which occurred during the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX). The MCV formed from a preexisting upper-level disturbance over the southwest United States on 10 June and matured as it traveled northeastward. The BAMEX field campaign provided a relatively dense collection of upper air observations through dropsondes on 11 June during the mature stage of the vortex. While several previous studies have focused on analysis of the dynamics and thermodynamics of observed and simulated vortices, few have addressed the ability to predict MCVs using numerical models. This event is of particular interest to the study of MCV dynamics and predictability given the anomalously strong and long-lived nature of the circulation and the dense data set. The first part of this study explores the dynamics of this MCV through an in-depth analysis of data from the profiler network and BAMEX dropsonde observations, in addition to the conventional surface and sounding observations as well as radar and satellite images. Next, issues relating to model performance are addressed through anevaluation of two state-of-the-art mesoscale models with varying resolutions. It is determined that the ability of a forecast model to accurately predict this MCV event is directly related to its ability to simulate convection. It is also shown that the convective-resolving Weather Research and Forecast (WRF) model with horizontal grid increments of 4 km displays superior performance in its simulation of this MCV event. Finally, an ensemble of 20 forecasts using mesoscale model MM5 with horizontal grid increments of 10 km are employed to evaluate probabilistically the dynamics and predictability of the MCV through the examination of the ensemble spread as well as the correlations between different forecast variables among ensemble members. It is shown that after MCV development, the ensemble mean performs poorly while individual ensemble members with good forecasts of convection at all stages of the MCV also forecast the midlevel vortex well. Furthermore, correlations among ensemble members generally support the findings in the observational analysis and in previous literature.

One of the most important aspects of coastal management and planning programs that needs to be investigated is shoreline dynamics. Long-term coastal analysis uses historical data to identify the sectors along the coast where the shoreline position has changed. Among the information that can be obtained from these studies are the general trend of coasts, either advancing or retreating. The erosion or accretion rates at each location can be used to forecast future shoreline positions. The current techniques used to study shoreline evolution are generally based on transects perpendicular to a baseline at selected points. But these techniques proved to be less efficient along more complex shorelines, and need to be refined. A new and more reliable method, the topologically constrained transect method (TCTM), was developed for this study and tested using data available for three sectors of the Texas Gulf Coast. Output data generated from TCTM also allowed performing shoreline evolution analysis and forecasting based on historical positions. Using topological constrained transects, this study provides a new method to estimate total areas of accretion or erosion at each segment of the coastline. Reliable estimates of future gains or losses of land along the coast will be extremely useful for planning and management decisions, especially those related to infrastructure and environmental impacts, and in the development of coastal models. Especially important is the potential to quickly identify areas of significant change, which eliminates the need for preliminary random sample surveying, and concentrate higher-resolution analyses in the most significant places. The results obtained in this research using the new methodology show that the Texas coast generally experiences erosion, with anthropogenic factors responsible for accretion. Accretion areas are located near coastal infrastructure, especially jetties that block the along shore sediment transport. The maximum erosion rate obtained in the study area is 5.48 m/year. This value helps make us aware of the powerful dynamic of the sector.

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