Background: Great strides have been made in combating malaria, however, the indicators in sub Saharan Africa still do not show promise for elimination in the near future as malaria infections still result in high morbidity and mortality among children. The abundance of the malaria-transmitting mosquito vectors in these regions are driven by climate suitability. In order to achieve malaria elimination by 2030, strengthening of surveillance systems have been advocated. Based on malaria surveillance and climate monitoring, forecasting models may be developed for early warnings. Therefore, in this thesis, we strived to illustrate the use malaria surveillance and climate data for policy and decision making by assessing the association between weather variability (from ground and remote sensing sources) and malaria mortality, and by building malaria admission forecasting models. We further propose an economic framework for integrating forecasts into operational surveillance system for evidence based decisionmaking and resource allocation.  Methods: The studies were based in Asembo, Gem and Karemo areas of the KEMRI/CDC Health and Demographic Surveillance System in Western Kenya. Lagged association of rainfall and temperature with malaria mortality was modeled using general additive models, while distributed lag non-linear models were used to explore relationship between remote sensing variables, land surface temperature(LST), normalized difference vegetation index(NDVI) and rainfall on weekly malaria mortality. General additive models, with and without boosting, were used to develop malaria admissions forecasting models for lead times one to three months. We developed a framework for incorporating forecast output into economic evaluation of response strategies at different lead times including uncertainties. The forecast output could either be an alert based on a threshold, or absolute predicted cases. In both situations, interventions at each lead time could be evaluated by the derived net benefit function and uncertainty incorporated by simulation.  Results: We found that the environmental factors correlated with malaria mortality with varying latencies. In the first paper, where we used ground weather data, the effect of mean temperature was significant from lag of 9 weeks, with risks higher for mean temperatures above 250C. The effect of cumulative precipitation was delayed and began from 5 weeks. Weekly total rainfall of more than 120 mm resulted in increased risk for mortality. In the second paper, using remotely sensed data, the effect of precipitation was consistent in the three areas, with increasing effect with weekly total rainfall of over 40 mm, and then declined at 80 mm of weekly rainfall. NDVI below 0.4 increased the risk of malaria mortality, while day LST above 350C increased the risk of malaria mortality with shorter lags for high LST weeks. The lag effect of precipitation was more delayed for precipitation values below 20 mm starting at week 5 while shorter lag effect for higher precipitation weeks. The effect of higher NDVI values above 0.4 were more delayed and protective while shorter lag effect for NDVI below 0.4. For all the lead times, in the malaria admissions forecasting modelling in the third paper, the boosted regression models provided better prediction accuracy. The economic framework in the fourth paper presented a probability function of the net benefit of response measures, where the best response at particular lead time corresponded to the one with the highest probability, and absolute value, of a net benefit surplus.  Conclusion: We have shown that lagged relationship between environmental variables and malaria health outcomes follow the expected biological mechanism, where presentation of cases follow the onset of specific weather conditions and climate variability. This relationship guided the development of predictive models showcased with the malaria admissions model. Further, we developed an economic framework connecting the forecasts to response measures in situations with considerable uncertainties. Thus, the thesis work has contributed to several important components of early warning systems including risk assessment; utilizing surveillance data for prediction; and a method to identifying cost-effective response strategies. We recommend economic evaluation becomes standard in implementation of early warning system to guide long-term sustainability of such health protection programs.

本文以事件研究法探討在公司治理程度不同的公司發布盈餘預測時， 不同類型的投資人在事件窗期中所反映的投資行為。首先以獨立董事與監 察人佔董監席次比例、董監事持股比例、大股東持股比例、經理人持股比 例、機構投資人持股比例、盈餘股份比以及董事長是否兼任總經理作為判 別公司治理程度的指標。再以公司發布盈餘預測的時點做區別，分別以當 年度首度預測是否由公司本身發布，與之後調高以及調低預測做為事件日。 實證結果顯示，當公司治理佳者發布盈餘預測時，外資會出現較多的買超 行為且獲得較高的異常報酬，散戶則持相反動作；而公司治理差者發布盈 餘預測時，散戶的買賣超變化量一般而言會較法人大，出現短期進出的情 形較多，且外資在其調高盈餘預測時，也不會馬上進行買進。整體而言， 外資在公司發布盈餘預測時所做出的交易行為，大致上與公司的治理程度 有正向關係，散戶則大多報持短線進出的態度。 / This study examines how different types of investors behave when entities with different corporate governances announce earnings forecasts. Using seven corporate governance indicators to categorize all of the samples and analyzing how the abnormal return, the results suggests foreign institutional investors are gaining more abnormal return by buying more stocks after earnings announcements of the entities with better corporate governance, and would not interact right after earnings announcements of the entities with worse corporate governance, when the individual investors are going the opposite way to the foreign institutional investors.

Reservoir economic performance is based upon future cash flows which can be generated from a reservoir. Future cash flows are a function of hydrocarbon volumetric flow rates which a reservoir can produce, and the market conditions. Both of these functions of future cash flows are associated with uncertainties. There is uncertainty associated in estimates of future hydrocarbon flow rates due to uncertainty in geological model, limited availability and type of data, and the complexities involved in the reservoir modeling process. The second source of uncertainty associated with future cash flows come from changing oil prices, rate of return etc., which are all functions of market dynamics. Robust integration of these two sources of uncertainty, i.e. future hydrocarbon flow rates and market dynamics, in a model to predict cash flows from a reservoir is an essential part of risk assessment, but a difficult task. Current practices to assess a reservoir’s economic performance by using Deterministic Cash Flow (DCF) methods have been unsuccessful in their predictions because of lack in parametric capability to robustly and completely incorporate these both types of uncertainties. This thesis presents a procedure which accounts for uncertainty in hydrocarbon production forecasts due to incomplete geologic information, and a novel real options methodology to assess the project economics for upstream petroleum industry. The modeling approach entails determining future hydrocarbon production rates due to incomplete geologic information with and without secondary information. The price of hydrocarbons is modeled separately, and the costs to produce them are determined based on market dynamics. A real options methodology is used to assess the effective cash flows from the reservoir, and hence, to determine the project economics. This methodology associates realistic probabilities, which are quantified using the method’s parameters, with benefits and costs. The results from this methodology are compared against the results from DCF methodology to examine if the real options methodology can identify some hidden potential of a reservoir’s performance which DCF might not be able to uncover. This methodology is then applied to various case studies and strategies for planning and decision making. / text

會計盈餘是企業向投資人傳達營運績效的指標，又投資人視公司達成分析師預測門檻與否為企業前景的重要訊號。當公司宣告策略聯盟決策時，資本市場給予正面評價，不過策略聯盟協議可能使管理當局存在機會主義與盈餘管理活動，過去文獻發現，有策略聯盟的公司，其盈餘品質較低。本文探究企業執行策略聯盟對於跨越盈餘門檻的關聯性，觀察策略聯盟事件是否為管理當局進行盈餘管理或是預期管理的工具，以迎合或擊敗分析師之盈餘預測門檻。本文實證發現策略聯盟與否及策略聯盟多寡與分析師預測門檻具有顯著正相關，而執行策略聯盟之公司從事向下引導分析師預測的機率較低，此外，實證結果亦發現，策略聯盟會降低公司管理當局採取向上調整裁決性應計數的可能性。綜上研究顯示，有策略聯盟之企業達成分析師預測門檻的機會較高，然而，其管理當局較不會選擇應計項目盈餘管理或預期管理方式來迎合或擊敗分析師之盈餘預測門檻。

This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks, is capable of explaining the highly positive correlation across the industrialized countries' inflation even though their cross-country correlation in money growth rate is negligible. The structure of this model generates cross-country correlations of inflation, output and consumption that appear to closely correspond to the data. Additionally, this model can explain the internal correlation between inflation and output observed in the data. The second essay presents two important results. First, gains from monetary policy cooperation are different from zero when the elasticity of substitution between domestic and imported goods consumption is different from one. Second, when monetary policy is endogenous in a two-country model, the only Nash equilibria supported by this model are those that are symmetrical. That is, all exporting firms in both countries choose to price in their own currency, or all exporting firms in both countries choose to price in the importer's currency. The last essay provides both conditional and unconditional predictive ability evaluations of the aluminum futures contracts prices, by using five different econometric models, in forecasting the aluminum spot price monthly return 3, 15, and 27-months ahead for the sample period 1989.01-2010.10. From these evaluations, the best model in forecasting the aluminum spot price monthly return 3 and 15 months ahead is followed by a (VAR) model whose variables are aluminum futures contracts price, aluminum spot price and risk free interest rate, whereas for the aluminum spot price monthly return 27 months ahead is a single equation model in which the aluminum spot price today is explained by the aluminum futures price 27 months earlier. Finally, it shows that iterated multiperiod-ahead time series forecasts have a better conditional out-of-sample forecasting performance of the aluminum spot price monthly return when an estimated (VAR) model is used as a forecasting tool.

Exponential smoothing algorithms are very attractive for the practical world such as in industry. When considering bivariate exponential smoothing methods, in addition to the properties of univariate methods, additional properties give insight to relationships between the two components of a process, and also to the overall structure of the model. It is important to study these properties, but even with the merits the bivariate exponential smoothing algorithms have, exponential smoothing algorithms are nonstatistical/nonstochastic and to study the properties within exponential smoothing may be worthless. As an alternative approach, the (bivariate) ARIMA and the structural models which are classes of statistical models, are shown to generalize the exponential smoothing algorithms. We study these properties within these classes as they will have implications on exponential smoothing algorithms. Forecast properties are studied using the state space model and the Kalman filter. Comparison of ARIMA and structural model completes the study. / Mathematical Sciences / M. Sc. (Statistics)

This thesis examines regional integration in Southern Africa and the evolution of SADC. Regional developments are evaluated with the yardsticks of integration theory, against the background of international regionalisation, and in terms of the region's practical record, its rhetoric and future agenda. The extent to which economic integration is progressing, is determined, after which the thesis focuses on political integration within SADC - both de Jure and de facto. Finally, developments within the region are evaluated in light of normative prerequisites for increased political integration. The thesis finds that the integration process in SADC does not fit into traditional integration theory, and concludes that successful economic integration in the region is not necessarily a prerequisite to political integration, but would facilitate it. The research finally concludes that there is evidence of embryonic political integration within SADC, which will wane or grow depending primarily on the political will of its constituents / Political Science / M.A. (Politics)

本研究以日本東京證券交易所上市公司為研究對象，探討董事會成員年齡與強制性盈餘預測之關聯性。本研究將董事會成員年齡區分為五種：董事長的年齡、董事會成員的平均年齡、董事會成員年齡的標準差、董事會成員最高年齡跟最低年齡的差距及董事長年齡是否高於董事會成員平均年齡，以測試其所發布盈餘預測準確度與盈餘預測偏差之關聯性。而實證結果發現董事長的年齡越大、董事會成員的平均年齡越大、董事長年齡高於董事會成員平均年齡時，所發布的盈餘預測準確度也就越高，且傾向較為保守的盈餘預測。而董事會成員年齡的標準差越大、董事會成員最高年齡與最低年齡差距越大時，所發布的盈餘預測準確度較低，且傾向較為樂觀的盈餘預測。

L’objectif des travaux de la thèse est d’étudier les propriétés statistiques de correction des prévisionsde température et de les appliquer au système des prévisions d’ensemble (SPE) de MétéoFrance. Ce SPE est utilisé dans la gestion du système électrique, à EDF R&D, il contient 51membres (prévisions par pas de temps) et fournit des prévisions à 14 jours. La thèse comportetrois parties. Dans la première partie on présente les SPE, dont le principe est de faire tournerplusieurs scénarios du même modèle avec des données d’entrée légèrement différentes pour simulerl’incertitude. On propose après des méthodes statistiques (la méthode du meilleur membre etla méthode bayésienne) que l’on implémente pour améliorer la précision ou la fiabilité du SPEdont nous disposons et nous mettons en place des critères de comparaison des résultats. Dansla deuxième partie nous présentons la théorie des valeurs extrêmes et les modèles de mélange etnous proposons des modèles de mélange contenant le modèle présenté dans la première partieet des fonctions de distributions des extrêmes. Dans la troisième partie nous introduisons larégression quantile pour mieux estimer les queues de distribution. / The thesis has for objective to study new statistical methods to correct temperature predictionsthat may be implemented on the ensemble prediction system (EPS) of Meteo France so toimprove its use for the electric system management, at EDF France. The EPS of Meteo Francewe are working on contains 51 members (forecasts by time-step) and gives the temperaturepredictions for 14 days. The thesis contains three parts: in the first one we present the EPSand we implement two statistical methods improving the accuracy or the spread of the EPS andwe introduce criteria for comparing results. In the second part we introduce the extreme valuetheory and the mixture models we use to combine the model we build in the first part withmodels for fitting the distributions tails. In the third part we introduce the quantile regressionas another way of studying the tails of the distribution.

Cette thèse analyse les conséquences et les implications des annonces de dividendes sur le marché boursier français dans un contexte de crise financière. Elle comporte quatre chapitres dont un premier, théorique qui trace les orientations des trois études empiriques réalisées. À l’issue de ce chapitre, il est proposé un cadre d’analyse de l’impact de la crise sur la politique de dividendes. Le deuxième chapitre traite de l’impact de la crise sur les réactions du marché. Il a testé et validé l’hypothèse d’une réaction différenciée des investisseurs aux annonces de dividendes en fonction du contexte économique. De surcroît, il met en évidence des réactions asymétriques des investisseurs en période de crise. Le troisième chapitre fournit une nouvelle explication à ces réactions asymétriques à travers la théorie de l’ambiguïté. L’hypothèse selon laquelle la nature et le degré d’incertitude de l’environnement macroéconomique auraient un impact sur la manière dont les investisseurs réagissent suite aux annonces de dividendes a été testée et validée. Le quatrième chapitre analyse la prévision des bénéfices comptables par les dividendes en période de crise, au regard de la théorie du signal. Nos résultats valident globalement les théories du signal et de l’ambiguïté. Même si la crise a affecté les réactions du marché français, elle n’a pas eu d’impact sur la relation significative qui existe entre les changements de dividendes et les variations de bénéfices futurs. Cette thèse analyse les conséquences et les implications des annonces de dividendes sur le marché boursier français dans un contexte de crise financière. Elle comporte quatre chapitres dont un premier, théorique qui trace les orientations des trois études empiriques réalisées. À l’issue de ce chapitre, il est proposé un cadre d’analyse de l’impact de la crise sur la politique de dividendes. Le deuxième chapitre traite de l’impact de la crise sur les réactions du marché. Il a testé et validé l’hypothèse d’une réaction différenciée des investisseurs aux annonces de dividendes en fonction du contexte économique. De surcroît, il met en évidence des réactions asymétriques des investisseurs en période de crise. Le troisième chapitre fournit une nouvelle explication à ces réactions asymétriques à travers la théorie de l’ambiguïté. L’hypothèse selon laquelle la nature et le degré d’incertitude de l’environnement macroéconomique auraient un impact sur la manière dont les investisseurs réagissent suite aux annonces de dividendes a été testée et validée. Le quatrième chapitre analyse la prévision des bénéfices comptables par les dividendes en période de crise, au regard de la théorie du signal. Nos résultats valident globalement les théories du signal et de l’ambiguïté. Même si la crise a affecté les réactions du marché français, elle n’a pas eu d’impact sur la relation significative qui existe entre les changements de dividendes et les variations de bénéfices futurs. / This dissertation investigates the consequences and implications of dividend announcements on French stock market in a context of financial crisis. It consists of four chapters including a first theoretical chapter that draws directions of the three empirical studies we realised. After this chapter, we provide an analysis framework of the impact of the crisis on the dividend policy. The second chapter discusses the impact of the financial crisis on french market reactions following dividend announcements. It tested and validated the hypothesis of a differentiated reaction of investors to dividend announcements based on the economic environment. Furthermore, it highlights asymmetric reactions of investors in times of crisis. The third chapter provides a new explanation for these asymmetric reactions through the ambiguity theory. The hypothesis according to which the nature and the degree of uncertainty of the macroeconomic environment has an impact on the way in which capital market prices react to dividend announcements was tested and validated. The fourth chapter analyses earnings forecast by dividends in times of crisis, according to the signaling theory. Our findings generally support the signaling and ambiguity theories. But, although the crisis affected the French market reactions to dividend announcements, it has no impact on the significant relationship between dividends changes and future earnings variations.