Under the going-concern concept, an entity is assumed to be a going concern when it is able and willing to continue operations in the foreseeable future. Although substantial agreement exists as to the meaning and role of the going-concern concept, it is difficult to make going-concern assessments in the course of an audit. In particular, existing auditing guidelines contained in SAS No. 34 are inadequate and existing going-concern prediction models are flawed. In view of this, the objective of the dissertation is to construct a going-concern prediction model (hereafter called the Koh model) that is based upon improved statistical techniques and methodology. A sample of 165 companies that filed for bankruptcy during the period 1980 to 1985 and a matched sample of 165 non-bankrupt companies are used to construct and test the Koh model. Following the lead taken by the proposed SAS on going-concern assessments, a non-going concern is operationalized as a bankrupt company. For each of the sample companies, six financial ratios as specified by the proposed theory of bankruptcy are obtained. Probit analysis with the weighted exogenous sample maximum likelihood procedure is used to estimate the coefficients of the Koh model. Using the Lachenbruch U method, the hold-out accuracy rates of the Koh model are computed. They are 85.45% for non-going concerns, 100.00% for going concerns, and 99.91% overall. With these accuracy rates, the Koh model compares favorably with other going-concern prediction models suggested in the literature and the auditors. The effects of misclassification costs of Type I and Type II errors on the Koh model are also considered. It is found that the optimal cut-off probability for the Koh model is very insensitive to varying relative misclassification costs. Coupled with its high predictive ability and stability, the Koh model can be an effective prediction model, analytical tool, and defensive device for auditors. Further, the methodology developed and employed in the dissertation can contribute to the current state-of-the-art in constructing prediction models such as going-concern or bankruptcy prediction models, takeover/acquisition prediction models, and loan default prediction models. / Ph. D.

In this thesis, we study brand choice problem via the following three perspectives: a company's market share management, introduction of customers with different perspectives, and an analysis of an application domain which is illustrative of these issues. Our contributions following these perspectives include: (1) development of a stochastic differential-jump game (SDJG) model for brand competition in a specific situation wherein market share is modeled by a jump-diffusion process, (2) a robust hierarchical logit/probit model for market heterogeneity, and (3) applications of logit/probit model to the dynamic pricing problem occurring in production-inventory systems with jump events. Our research explores the use of quantitative method of operations research to control the dynamics of market share and provides a precise estimation method to integrate more detail information in discrete brand choice models.

Thesis (Ph. D.)--University of California, San Diego, 2004. / Vita. Includes bibliographical references (leaves 275-285).

The focus of this dissertation is the theory of qualitative response models and its application to forestry related problems. Qualitative response models constitute a class of regression models used for predicting the result in one of a discrete number of mutually exclusive outcomes. These models, also known as discrete regression models, differ from the usual continuous regression models in that the response variable takes only discrete values. In forestry applications the use of such models has been largely confirmed to mortality studies where only the simplest kind of qualitative response models - a dichotomous (binary) dependent variable model - is applied. However, it is common in forestry to deal with many variables which are either discrete or recorded discretely and need to be formulated by more complex models involving polychotomous dependent variables. The estimation of such complex qualitative response models only recently has been made possible by the development of advanced computer technology. The first objective of this study was to specify dichotomous and polychotomous response models that appear to be suitable for forestry applications and present methods of statistical analysis for these models. The models considered in this study were: the linear probability model, binary logit and probit, ordered and unordered multinomiallogit and probit and McFadden's conditionallogit. Special attention was paid to the following problems: i) how to motivate a qualitative response model which is theoretically correct and statistically manageable, ii) how to estimate and draw inferences about the model parameters, iii) what criteria to use when choosing among competing models and iv) how to detect outlying, high leverage and highly influential observations. The second objective was to exemplify the utility of the above models by considering two, forestry related, case studies. Assessing the merchantability of loblolly pine trees growing on plantations in southern United States and modelling the incidence and spread of fusifonn rust on loblolly and slash pine plantations in east Texas. The results demonstrated the potential of qualitative response models for meaningful implementation in a variety of forestry applications and also, suggested topics for future research work. / Ph. D.

Québec Université Laval, Bibliothèque 2015

La « Grande Récession » de 2008-2009 ou encore l'aggravation de la crise des dettes souveraines et de la dette publique dans la zone euro à l'été 2011, constituent de récents événements qui ont cristallisé les enjeux de l'analyse conjoncturelle, ceux relatifs notamment à la datation et à la prévision des inflexions cycliques de l'activité réelle. L'objet de cette thèse s'inscrit fondamentalement au sein de ces deux approches complémentaires du cycle économique.Le chapitre 1 dresse un portrait du cycle autour de trois conceptions distinctes de ses points de retournement : le cycle classique, le cycle de croissance et le cycle d'accélération. Nous discutons également de sa mesure eu égard aux diverses représentations possibles de l'activité agrégée d'un pays, ainsi qu'aux deux traditions existantes dans lesquelles s'inscrivent les modèles de datation. Nous mettons par ailleurs en lumière l'influence grandissante de l'environnement financier sur la dynamique cyclique des économies. Le chapitre 2 nous amène à développer deux algorithmes non-paramétriques dans le but de repérer les inflexions propres à chacun des cycles auparavant conceptualisés, mais aussipour en mesurer leurs principales caractéristiques. Le premier (resp. le second) algorithme repose sur une représentation univariée (resp. multivariée) de l'activité économique globale ; in fine, nous les appliquons aux données de la conjoncture française entre 1970 et 2010. Le chapitre 3 tire parti de nos résultats en matière de datation conjoncturelle afin de prévoir les récessions françaises depuis 1974. Au moyen de modèles probits, nous illustrons le rôle de variables financières et monétaires en tant qu'indicateurs avancés des fluctuations du cycle des affaires français. Nous montrons de plus que nos modèles prédictifs assurent uneparfaite détection des récessions pour un horizon égal à deux trimestres.Le chapitre 4 prolonge l'ensemble de l'analyse à plusieurs États membres de la zoneeuro, ces derniers étant observés depuis 1979. Nous construisons d'abord une chronologie de leurs cycles classiques respectifs puis, nous proposons un examen de leurs caractéristiques moyennes et de leur degré de synchronisation. Enfin, en s'appuyant sur des indicateurs financiers et monétaires dans le cadre d'un probit dynamique à effets fixes, nous parvenons à anticiper - jusqu'à un horizon de deux trimestres - les épisodes récessifs survenus dans les économies considérées. / The « Great Recession » of 2008-2009 and the sovereign and public debt crises which strengthened in the euro area in the summer of 2011 are recent events that have crystallized the challenges facing economic analysis, especially those related to dating and predicting cyclical inflections of real activity. The purpose of this thesis is to study these two complementary approaches to the economic cycle. Chapter 1 provides a portrait of the cycle using three distinct conceptions of its turning points: the classical cycle, the growth cycle and the acceleration cycle. We also discuss the measurement of the cycle with respect to various possible representations of aggregate activity of a country, as well as to two existing traditions which encompass dating models. Moreover, we highlight the growing influence of the financial environment over business cycle fluctuations.In chapter 2, we develop two non-parametric algorithms in order to identify theinflections that are particular to each of the previously conceptualized cycles, but also to measure their main characteristics. The first algorithm is based on a univariate representation of overall economic activity, the second on its ultivariate representation; ultimately, we apply the algorithms to the data of the French economy between 1970 and 2010. Chapter 3 builds on our results for cyclical dating to predict French recessions since 1974. Using probit models, we illustrate the role of monetary and financial variables as leading indicators of French business cycle fluctuations. In addition, we show that our models accurately detect recessions for a forecasting lag of two-quarters. Chapter 4 extends the entire analysis to several member states of the euro zone, with observations beginning in 1979. We first construct a chronology of their classical cycles, and then we propose an analysis of their main characteristics and their degree of synchronization.Finally, based on financial and monetary indicators in the context of a dynamic probit with fixed effects, we can anticipate the recessionary episodes which occurred in these economies with a horizon of two quarters.